Application of the EIIP/ISM bioinformatics platform in discovery of novel therapeutic targets and potential therapeutic molecules

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Application of the EIIP/ISM bioinformatics platform in discovery of novel therapeutic targets and potential therapeutic molecules (en)
Примена EIIP/ISM биоинформатичке платформе у откривању нових терапеутских таргета и потенцијалних терапеутских молекула (sr)
Primena EIIP/ISM bioinformatičke platforme u otkrivanju novih terapeutskih targeta i potencijalnih terapeutskih molekula (sr_RS)
Authors

Publications

Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies

Gemović, Branislava S.; Perović, Vladimir R.; Davidović, Radoslav S.; Drljača, Tamara; Veljković, Nevena V.

(2021)

TY  - JOUR
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Davidović, Radoslav S.
AU  - Drljača, Tamara
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8894
AB  - For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm–Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php.
T2  - PLOS One
T1  - Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies
VL  - 16
IS  - 1
SP  - e0244948
DO  - 10.1371/journal.pone.0244948
ER  - 
@article{
author = "Gemović, Branislava S. and Perović, Vladimir R. and Davidović, Radoslav S. and Drljača, Tamara and Veljković, Nevena V.",
year = "2021",
abstract = "For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm–Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php.",
journal = "PLOS One",
title = "Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies",
volume = "16",
number = "1",
pages = "e0244948",
doi = "10.1371/journal.pone.0244948"
}
Gemović, B. S., Perović, V. R., Davidović, R. S., Drljača, T.,& Veljković, N. V.. (2021). Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies. in PLOS One, 16(1), e0244948.
https://doi.org/10.1371/journal.pone.0244948
Gemović BS, Perović VR, Davidović RS, Drljača T, Veljković NV. Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies. in PLOS One. 2021;16(1):e0244948.
doi:10.1371/journal.pone.0244948 .
Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Drljača, Tamara, Veljković, Nevena V., "Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies" in PLOS One, 16, no. 1 (2021):e0244948,
https://doi.org/10.1371/journal.pone.0244948 . .
2

Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action

Bondžić, Aleksandra M.; Senćanski, Milan V.; Vujačić Nikezić, Ana V.; Kirillova, Marina V.; André, Vania; Kirillov, Alexander M.; Bondžić, Bojan P.

(2020)

TY  - JOUR
AU  - Bondžić, Aleksandra M.
AU  - Senćanski, Milan V.
AU  - Vujačić Nikezić, Ana V.
AU  - Kirillova, Marina V.
AU  - André, Vania
AU  - Kirillov, Alexander M.
AU  - Bondžić, Bojan P.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8806
AB  - Three coordination compounds featuring different types of tetracopper(II) cores, namely [O ⊂ Cu4N(CH2CH2O)34(BOH)4][BF4]2 (1), [Cu4(μ4-H2edte)(μ5-H2edte)(sal)2]n·7nH2O, (H4edte = N,N,N′,N′-tetrakis(2-hydroxyethyl)ethylenediamine, H2sal = salicylic acid) (2), and [Cu4(μ3-Hbes)4(μ-hba)K(H2O)3]n, H3bes = N,N-bis(2-hydroxyethyl)-2-aminoethanesulfonic acid (3), were assayed for their potency to inhibit the acetyl (AChE) and butyrylcholinesterase (BuChE) enzymes aiming to test these compounds as potential dual inhibitors in the treatment of Alzheimer's disease. All the investigated compounds showed a strong inhibitory potency toward both enzymes with IC50 values in micromolar range of concentration; compound 1 displayed the most potent inhibitory behaviour toward both enzymes. The mechanism of the AChE and BuChE inhibition was examined by enzyme kinetic measurements. The obtained kinetic parameters, Vmax and Km indicated an uncompetitive type of inhibition of both enzymes by compound 1. For the other two compounds a non-competitive inhibition mode was observed. To get further insight into the mechanism of action and to elucidate binding modes in details we examined the interactions of 1–3 with acetylcholinesterase, using molecular docking approach. Grid based docking studies indicated that these compounds can bind to peripheral anionic site (PAS) of the AChE with Ki values in micromolar range. Moreover, blind docking revealed the capability of investigated compounds to bind to new allosteric site (i.e. binding site II) distinct from PAS. Showing that these Cu-based compounds can act as new allosteric inhibitors of AChE and identifying novel allosteric binding site on AChE represents a significant contribution toward the design of novel and more effective inhibitors of AChE. © 2020 Elsevier Inc.
T2  - Journal of Inorganic Biochemistry
T1  - Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action
VL  - 205
SP  - 110990
DO  - 10.1016/j.jinorgbio.2019.110990
ER  - 
@article{
author = "Bondžić, Aleksandra M. and Senćanski, Milan V. and Vujačić Nikezić, Ana V. and Kirillova, Marina V. and André, Vania and Kirillov, Alexander M. and Bondžić, Bojan P.",
year = "2020",
abstract = "Three coordination compounds featuring different types of tetracopper(II) cores, namely [O ⊂ Cu4N(CH2CH2O)34(BOH)4][BF4]2 (1), [Cu4(μ4-H2edte)(μ5-H2edte)(sal)2]n·7nH2O, (H4edte = N,N,N′,N′-tetrakis(2-hydroxyethyl)ethylenediamine, H2sal = salicylic acid) (2), and [Cu4(μ3-Hbes)4(μ-hba)K(H2O)3]n, H3bes = N,N-bis(2-hydroxyethyl)-2-aminoethanesulfonic acid (3), were assayed for their potency to inhibit the acetyl (AChE) and butyrylcholinesterase (BuChE) enzymes aiming to test these compounds as potential dual inhibitors in the treatment of Alzheimer's disease. All the investigated compounds showed a strong inhibitory potency toward both enzymes with IC50 values in micromolar range of concentration; compound 1 displayed the most potent inhibitory behaviour toward both enzymes. The mechanism of the AChE and BuChE inhibition was examined by enzyme kinetic measurements. The obtained kinetic parameters, Vmax and Km indicated an uncompetitive type of inhibition of both enzymes by compound 1. For the other two compounds a non-competitive inhibition mode was observed. To get further insight into the mechanism of action and to elucidate binding modes in details we examined the interactions of 1–3 with acetylcholinesterase, using molecular docking approach. Grid based docking studies indicated that these compounds can bind to peripheral anionic site (PAS) of the AChE with Ki values in micromolar range. Moreover, blind docking revealed the capability of investigated compounds to bind to new allosteric site (i.e. binding site II) distinct from PAS. Showing that these Cu-based compounds can act as new allosteric inhibitors of AChE and identifying novel allosteric binding site on AChE represents a significant contribution toward the design of novel and more effective inhibitors of AChE. © 2020 Elsevier Inc.",
journal = "Journal of Inorganic Biochemistry",
title = "Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action",
volume = "205",
pages = "110990",
doi = "10.1016/j.jinorgbio.2019.110990"
}
Bondžić, A. M., Senćanski, M. V., Vujačić Nikezić, A. V., Kirillova, M. V., André, V., Kirillov, A. M.,& Bondžić, B. P.. (2020). Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action. in Journal of Inorganic Biochemistry, 205, 110990.
https://doi.org/10.1016/j.jinorgbio.2019.110990
Bondžić AM, Senćanski MV, Vujačić Nikezić AV, Kirillova MV, André V, Kirillov AM, Bondžić BP. Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action. in Journal of Inorganic Biochemistry. 2020;205:110990.
doi:10.1016/j.jinorgbio.2019.110990 .
Bondžić, Aleksandra M., Senćanski, Milan V., Vujačić Nikezić, Ana V., Kirillova, Marina V., André, Vania, Kirillov, Alexander M., Bondžić, Bojan P., "Aminoalcoholate-driven tetracopper(II) cores as dual acetyl and butyrylcholinesterase inhibitors: Experimental and theoretical elucidation of mechanism of action" in Journal of Inorganic Biochemistry, 205 (2020):110990,
https://doi.org/10.1016/j.jinorgbio.2019.110990 . .
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Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field

Đikić, Teodora; Vučićević, Jelica; Laurila, Jonne; Radi, Marco; Veljković, Nevena V.; Xhaard, Henri; Nikolić, Katarina M.

(2020)

TY  - JOUR
AU  - Đikić, Teodora
AU  - Vučićević, Jelica
AU  - Laurila, Jonne
AU  - Radi, Marco
AU  - Veljković, Nevena V.
AU  - Xhaard, Henri
AU  - Nikolić, Katarina M.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8887
AB  - Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors – rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α2- adrenoceptors.
T2  - Molecular Informatics
T1  - Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field
VL  - 39
IS  - 7
SP  - 1900165
DO  - 10.1002/minf.201900165
ER  - 
@article{
author = "Đikić, Teodora and Vučićević, Jelica and Laurila, Jonne and Radi, Marco and Veljković, Nevena V. and Xhaard, Henri and Nikolić, Katarina M.",
year = "2020",
abstract = "Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors – rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α2- adrenoceptors.",
journal = "Molecular Informatics",
title = "Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field",
volume = "39",
number = "7",
pages = "1900165",
doi = "10.1002/minf.201900165"
}
Đikić, T., Vučićević, J., Laurila, J., Radi, M., Veljković, N. V., Xhaard, H.,& Nikolić, K. M.. (2020). Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field. in Molecular Informatics, 39(7), 1900165.
https://doi.org/10.1002/minf.201900165
Đikić T, Vučićević J, Laurila J, Radi M, Veljković NV, Xhaard H, Nikolić KM. Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field. in Molecular Informatics. 2020;39(7):1900165.
doi:10.1002/minf.201900165 .
Đikić, Teodora, Vučićević, Jelica, Laurila, Jonne, Radi, Marco, Veljković, Nevena V., Xhaard, Henri, Nikolić, Katarina M., "Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field" in Molecular Informatics, 39, no. 7 (2020):1900165,
https://doi.org/10.1002/minf.201900165 . .
1
1
1

Tally-2.0: upgraded validator of tandem repeat detection in protein sequences

Perović, Vladimir R.; Leclercq, Jeremy Y; Šumonja, Neven; Richard, Francois D; Veljković, Nevena V.; Kajava, Andrey V.

(2020)

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Leclercq, Jeremy Y
AU  - Šumonja, Neven
AU  - Richard, Francois D
AU  - Veljković, Nevena V.
AU  - Kajava, Andrey V.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8997
AB  - Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs. Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%.
T2  - Bioinformatics
T1  - Tally-2.0: upgraded validator of tandem repeat detection in protein sequences
VL  - 36
IS  - 10
SP  - 3260
EP  - 3262
DO  - 10.1093/bioinformatics/btaa121
ER  - 
@article{
author = "Perović, Vladimir R. and Leclercq, Jeremy Y and Šumonja, Neven and Richard, Francois D and Veljković, Nevena V. and Kajava, Andrey V.",
year = "2020",
abstract = "Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs. Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%.",
journal = "Bioinformatics",
title = "Tally-2.0: upgraded validator of tandem repeat detection in protein sequences",
volume = "36",
number = "10",
pages = "3260-3262",
doi = "10.1093/bioinformatics/btaa121"
}
Perović, V. R., Leclercq, J. Y., Šumonja, N., Richard, F. D., Veljković, N. V.,& Kajava, A. V.. (2020). Tally-2.0: upgraded validator of tandem repeat detection in protein sequences. in Bioinformatics, 36(10), 3260-3262.
https://doi.org/10.1093/bioinformatics/btaa121
Perović VR, Leclercq JY, Šumonja N, Richard FD, Veljković NV, Kajava AV. Tally-2.0: upgraded validator of tandem repeat detection in protein sequences. in Bioinformatics. 2020;36(10):3260-3262.
doi:10.1093/bioinformatics/btaa121 .
Perović, Vladimir R., Leclercq, Jeremy Y, Šumonja, Neven, Richard, Francois D, Veljković, Nevena V., Kajava, Andrey V., "Tally-2.0: upgraded validator of tandem repeat detection in protein sequences" in Bioinformatics, 36, no. 10 (2020):3260-3262,
https://doi.org/10.1093/bioinformatics/btaa121 . .
1
2
1
1

DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis

Davidović, Radoslav S.; Perović, Vladimir R.; Gemović, Branislava S.; Veljković, Nevena V.

(2020)

TY  - JOUR
AU  - Davidović, Radoslav S.
AU  - Perović, Vladimir R.
AU  - Gemović, Branislava S.
AU  - Veljković, Nevena V.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9666
AB  - Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design.DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php.Supplementary data are available at Bioinformatics online.
T2  - Bioinformatics
T1  - DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis
VL  - 36
IS  - 6
SP  - 1981
EP  - 1982
DO  - 10.1093/bioinformatics/btz836
ER  - 
@article{
author = "Davidović, Radoslav S. and Perović, Vladimir R. and Gemović, Branislava S. and Veljković, Nevena V.",
year = "2020",
abstract = "Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design.DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php.Supplementary data are available at Bioinformatics online.",
journal = "Bioinformatics",
title = "DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis",
volume = "36",
number = "6",
pages = "1981-1982",
doi = "10.1093/bioinformatics/btz836"
}
Davidović, R. S., Perović, V. R., Gemović, B. S.,& Veljković, N. V.. (2020). DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis. in Bioinformatics, 36(6), 1981-1982.
https://doi.org/10.1093/bioinformatics/btz836
Davidović RS, Perović VR, Gemović BS, Veljković NV. DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis. in Bioinformatics. 2020;36(6):1981-1982.
doi:10.1093/bioinformatics/btz836 .
Davidović, Radoslav S., Perović, Vladimir R., Gemović, Branislava S., Veljković, Nevena V., "DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis" in Bioinformatics, 36, no. 6 (2020):1981-1982,
https://doi.org/10.1093/bioinformatics/btz836 . .
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2

In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine

Matejin, Stanislava; Bukreyeva, Natalya; Radošević, Draginja; Senćanski, Milan V.; Mantlo, Emily; Veljković, Veljko; Glišić, Sanja; Paessler, Slobodan

(2020)

TY  - JOUR
AU  - Matejin, Stanislava
AU  - Bukreyeva, Natalya
AU  - Radošević, Draginja
AU  - Senćanski, Milan V.
AU  - Mantlo, Emily
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Paessler, Slobodan
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9036
AB  - Background: Due to the limitations of current antiviral therapies because of drug resistance and the emergence of new circulating viral strains, novel effective antivirals are urgently needed. Results of the previous drug repurposing by virtual screening of DrugBank revealed the anticholinergic drug cycrimine as a possible inhibitor of the influenza virus infection. Methods: In this study we examined the potential antiviral activity of cycrimine in vitro. Results: The experimental results showed the anti-influenza activity of cycrimine against two different influenza A subtypes in cell culture. Conclusions: The findings of this study suggest cycrimine as a potential therapeutic agent for influenza. ©2019 International Medical Press.
T2  - Antiviral Therapy
T1  - In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine
VL  - 24
IS  - 8
SP  - 589
EP  - 593
DO  - 10.3851/IMP3348
ER  - 
@article{
author = "Matejin, Stanislava and Bukreyeva, Natalya and Radošević, Draginja and Senćanski, Milan V. and Mantlo, Emily and Veljković, Veljko and Glišić, Sanja and Paessler, Slobodan",
year = "2020",
abstract = "Background: Due to the limitations of current antiviral therapies because of drug resistance and the emergence of new circulating viral strains, novel effective antivirals are urgently needed. Results of the previous drug repurposing by virtual screening of DrugBank revealed the anticholinergic drug cycrimine as a possible inhibitor of the influenza virus infection. Methods: In this study we examined the potential antiviral activity of cycrimine in vitro. Results: The experimental results showed the anti-influenza activity of cycrimine against two different influenza A subtypes in cell culture. Conclusions: The findings of this study suggest cycrimine as a potential therapeutic agent for influenza. ©2019 International Medical Press.",
journal = "Antiviral Therapy",
title = "In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine",
volume = "24",
number = "8",
pages = "589-593",
doi = "10.3851/IMP3348"
}
Matejin, S., Bukreyeva, N., Radošević, D., Senćanski, M. V., Mantlo, E., Veljković, V., Glišić, S.,& Paessler, S.. (2020). In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine. in Antiviral Therapy, 24(8), 589-593.
https://doi.org/10.3851/IMP3348
Matejin S, Bukreyeva N, Radošević D, Senćanski MV, Mantlo E, Veljković V, Glišić S, Paessler S. In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine. in Antiviral Therapy. 2020;24(8):589-593.
doi:10.3851/IMP3348 .
Matejin, Stanislava, Bukreyeva, Natalya, Radošević, Draginja, Senćanski, Milan V., Mantlo, Emily, Veljković, Veljko, Glišić, Sanja, Paessler, Slobodan, "In vitro anti-influenza activity of in silico repurposed candidate drug Cycrimine" in Antiviral Therapy, 24, no. 8 (2020):589-593,
https://doi.org/10.3851/IMP3348 . .
1
1

Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors

Senćanski, Milan V.; Glišić, Sanja

(2020)

TY  - CHAP
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9689
AB  - The hepatitis C virus (HCV) infection is a major and rising global health problem, affecting more than 71 million people worldwide. HCV is connected with several hepatic and extrahepatic disorders, containing several malignancies. Improved HCV detection with combined simple, well-tolerated treatments could reduce the need for liver transplantation and HCV related mortality. The latest therapeutic advances might convert chronic HCV into a routinely treatable disease. The introduction of direct-acting antivirals (DAAs) has improved efficacy and tolerance of treatments with high cure rates. DAAs target specific nonstructural proteins of the HCV with consequential interference with viral replication and consequently infection. The majority of the FDA approved drugs for HCV and those pending approval are small molecule drugs, especially those that utilize the viral inhibitor mechanisms of action and favor the HCV nonstructural proteins as their targets. Therefore, DAAs represent the most promising anti-HCV drugs that carry the least risk of drug failure during clinical trials. NS3/4a protease inhibitors have become the basis for HCV treatment as most new therapies contain an inhibitor from this class. It is reported that the approach for combating chronic viral infections is best achieved by a combination of several strategies, by means of inhibiting several targets. Moreover, the best promising strategy for fighting HCV is most similar to the anti-HIV therapy. A literature review was conducted to identify published clinical trial results regarding DAA combination therapy with third generation NS3/4a protease inhibitors. Detailed attention is given to the chemistry of the approved NS3/4a drugs and candidate therapeutics in the advanced stages of development. In this regard, a review of key drug design and organic synthesis stages is presented for anti-NS3/4A DAAs. © 2020 Bentham Science Publishers. All rights reserved.
T2  - Frontiers in Clinical Drug Research - Anti Infectives
T1  - Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors
VL  - 6
IS  - 1
SP  - 1
EP  - 48
DO  - 10.2174/9789811425745120060001
ER  - 
@inbook{
author = "Senćanski, Milan V. and Glišić, Sanja",
year = "2020",
abstract = "The hepatitis C virus (HCV) infection is a major and rising global health problem, affecting more than 71 million people worldwide. HCV is connected with several hepatic and extrahepatic disorders, containing several malignancies. Improved HCV detection with combined simple, well-tolerated treatments could reduce the need for liver transplantation and HCV related mortality. The latest therapeutic advances might convert chronic HCV into a routinely treatable disease. The introduction of direct-acting antivirals (DAAs) has improved efficacy and tolerance of treatments with high cure rates. DAAs target specific nonstructural proteins of the HCV with consequential interference with viral replication and consequently infection. The majority of the FDA approved drugs for HCV and those pending approval are small molecule drugs, especially those that utilize the viral inhibitor mechanisms of action and favor the HCV nonstructural proteins as their targets. Therefore, DAAs represent the most promising anti-HCV drugs that carry the least risk of drug failure during clinical trials. NS3/4a protease inhibitors have become the basis for HCV treatment as most new therapies contain an inhibitor from this class. It is reported that the approach for combating chronic viral infections is best achieved by a combination of several strategies, by means of inhibiting several targets. Moreover, the best promising strategy for fighting HCV is most similar to the anti-HIV therapy. A literature review was conducted to identify published clinical trial results regarding DAA combination therapy with third generation NS3/4a protease inhibitors. Detailed attention is given to the chemistry of the approved NS3/4a drugs and candidate therapeutics in the advanced stages of development. In this regard, a review of key drug design and organic synthesis stages is presented for anti-NS3/4A DAAs. © 2020 Bentham Science Publishers. All rights reserved.",
journal = "Frontiers in Clinical Drug Research - Anti Infectives",
booktitle = "Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors",
volume = "6",
number = "1",
pages = "1-48",
doi = "10.2174/9789811425745120060001"
}
Senćanski, M. V.,& Glišić, S.. (2020). Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors. in Frontiers in Clinical Drug Research - Anti Infectives, 6(1), 1-48.
https://doi.org/10.2174/9789811425745120060001
Senćanski MV, Glišić S. Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors. in Frontiers in Clinical Drug Research - Anti Infectives. 2020;6(1):1-48.
doi:10.2174/9789811425745120060001 .
Senćanski, Milan V., Glišić, Sanja, "Direct-acting antiviral drugs for treatment of hepatitis C virus infection-clinical trials data and chemistry of NS3/4A protease inhibitors" in Frontiers in Clinical Drug Research - Anti Infectives, 6, no. 1 (2020):1-48,
https://doi.org/10.2174/9789811425745120060001 . .
1
1

Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones

Isca, Vera M. S.; Senćanski, Milan V.; Filipović, Nenad R.; Dos Santos, Daniel J. V. A.; Čipak Gašparović, Ana; Saraiva, Lucilia; Afonso, Carlos A M; Rijo, Patrícia; Garcia-Sosa, Alfonso T

(2020)

TY  - JOUR
AU  - Isca, Vera M. S.
AU  - Senćanski, Milan V.
AU  - Filipović, Nenad R.
AU  - Dos Santos, Daniel J. V. A.
AU  - Čipak Gašparović, Ana
AU  - Saraiva, Lucilia
AU  - Afonso, Carlos A M
AU  - Rijo, Patrícia
AU  - Garcia-Sosa, Alfonso T
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9017
AB  - Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes.
AB  - Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes.
T2  - International Journal of Molecular Sciences
T1  - Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones
VL  - 21
IS  - 10
SP  - 3671
DO  - 10.3390/ijms21103671
ER  - 
@article{
author = "Isca, Vera M. S. and Senćanski, Milan V. and Filipović, Nenad R. and Dos Santos, Daniel J. V. A. and Čipak Gašparović, Ana and Saraiva, Lucilia and Afonso, Carlos A M and Rijo, Patrícia and Garcia-Sosa, Alfonso T",
year = "2020",
abstract = "Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes., Plants have been used for centuries to treat several illnesses. The Plectranthus genus has a vast variety of species that has allowed the isolation of cytotoxic compounds with notable activities. The abietane diterpenes 6,7-dehydroroyleanone (DeRoy, 1), 7α-acetoxy-6β-hydroxyroyleanone (Roy, 2), and Parvifloron D (ParvD, 3) were obtained from Plectranthus spp. and showed promising biological activities, such as cytotoxicity. The inhibitory effects of the different natural abietanes (1-3) were compared in MFC7, SkBr3, and SUM159 cell lines, as well as SUM159 grown in cancer stem cell-inducing conditions. Based on the royleanones’ bioactivity, the derivatives RoyBz (4), RoyBzCl (5), RoyPr2 (6), and DihydroxyRoy (7), previously obtained from 2, were selected for further studies. Protein kinases C (PKCs) are involved in several carcinogenic processes. Thus, PKCs are potential targets for cancer therapy. To date, the portfolio of available PKC modulators remains very limited due to the difficulty of designing isozyme-selective PKC modulators. As such, molecular docking was used to evaluate royleanones 1-6 as predicted isozyme-selective PKC binders. Subtle changes in the binding site of each PKC isoform change the predicted interaction profiles of the ligands. Subtle changes in royleanone substitution patterns, such as a double substitution only with non-substituted phenyls, or hydroxybenzoate at position four that flips the binding mode of ParvD (3), can increase the predicted interactions in certain PKC subtypes.",
journal = "International Journal of Molecular Sciences",
title = "Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones",
volume = "21",
number = "10",
pages = "3671",
doi = "10.3390/ijms21103671"
}
Isca, V. M. S., Senćanski, M. V., Filipović, N. R., Dos Santos, D. J. V. A., Čipak Gašparović, A., Saraiva, L., Afonso, C. A. M., Rijo, P.,& Garcia-Sosa, A. T.. (2020). Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones. in International Journal of Molecular Sciences, 21(10), 3671.
https://doi.org/10.3390/ijms21103671
Isca VMS, Senćanski MV, Filipović NR, Dos Santos DJVA, Čipak Gašparović A, Saraiva L, Afonso CAM, Rijo P, Garcia-Sosa AT. Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones. in International Journal of Molecular Sciences. 2020;21(10):3671.
doi:10.3390/ijms21103671 .
Isca, Vera M. S., Senćanski, Milan V., Filipović, Nenad R., Dos Santos, Daniel J. V. A., Čipak Gašparović, Ana, Saraiva, Lucilia, Afonso, Carlos A M, Rijo, Patrícia, Garcia-Sosa, Alfonso T, "Activity to Breast Cancer Cell Lines of Different Malignancy and Predicted Interaction with Protein Kinase C Isoforms of Royleanones" in International Journal of Molecular Sciences, 21, no. 10 (2020):3671,
https://doi.org/10.3390/ijms21103671 . .
6
7
4
5

DisProt: intrinsic protein disorder annotation in 2020

Hatos, András; Hajdu-Soltész, Borbála; Monzon, Alexander M; Palopoli, Nicolas; Álvarez, Lucía; Aykac-Fas, Burcu; Bassot, Claudio; Benítez, Guillermo I; Bevilacqua, Martina; Chasapi, Anastasia; Chemes, Lucia; Davey, Norman E; Davidović, Radoslav S.; Dunker, A Keith; Elofsson, Arne; Gobeill, Julien; Foutel, Nicolás S González; Sudha, Govindarajan; Guharoy, Mainak; Horvath, Tamas; Iglesias, Valentin; Kajava, Andrey V.; Kovacs, Orsolya P; Lamb, John; Lambrughi, Matteo; Lazar, Tamas; Leclercq, Jeremy Y; Leonardi, Emanuela; Macedo-Ribeiro, Sandra; Macossay-Castillo, Mauricio; Maiani, Emiliano; Manso, José A; Marino-Buslje, Cristina; Martínez-Pérez, Elizabeth; Mészáros, Bálint; Mičetić, Ivan; Minervini, Giovanni; Murvai, Nikoletta; Necci, Marco; Ouzounis, Christos A; Pajkos, Mátyás; Paladin, Lisanna; Pancsa, Rita; Papaleo, Elena; Parisi, Gustavo; Pasche, Emilie; Barbosa Pereira, Pedro J; Promponas, Vasilis J; Pujols, Jordi; Quaglia, Federica; Ruch, Patrick; Salvatore, Marco; Schad, Eva; Szabo, Beata; Szaniszló, Tamás; Tamana, Stella; Tantos, Agnes; Veljković, Nevena V.; Ventura, Salvador; Vranken, Wim; Dosztányi, Zsuzsanna; Tompa, Peter; Tosatto, Silvio C E; Piovesan, Damiano

(2019)

TY  - JOUR
AU  - Hatos, András
AU  - Hajdu-Soltész, Borbála
AU  - Monzon, Alexander M
AU  - Palopoli, Nicolas
AU  - Álvarez, Lucía
AU  - Aykac-Fas, Burcu
AU  - Bassot, Claudio
AU  - Benítez, Guillermo I
AU  - Bevilacqua, Martina
AU  - Chasapi, Anastasia
AU  - Chemes, Lucia
AU  - Davey, Norman E
AU  - Davidović, Radoslav S.
AU  - Dunker, A Keith
AU  - Elofsson, Arne
AU  - Gobeill, Julien
AU  - Foutel, Nicolás S González
AU  - Sudha, Govindarajan
AU  - Guharoy, Mainak
AU  - Horvath, Tamas
AU  - Iglesias, Valentin
AU  - Kajava, Andrey V.
AU  - Kovacs, Orsolya P
AU  - Lamb, John
AU  - Lambrughi, Matteo
AU  - Lazar, Tamas
AU  - Leclercq, Jeremy Y
AU  - Leonardi, Emanuela
AU  - Macedo-Ribeiro, Sandra
AU  - Macossay-Castillo, Mauricio
AU  - Maiani, Emiliano
AU  - Manso, José A
AU  - Marino-Buslje, Cristina
AU  - Martínez-Pérez, Elizabeth
AU  - Mészáros, Bálint
AU  - Mičetić, Ivan
AU  - Minervini, Giovanni
AU  - Murvai, Nikoletta
AU  - Necci, Marco
AU  - Ouzounis, Christos A
AU  - Pajkos, Mátyás
AU  - Paladin, Lisanna
AU  - Pancsa, Rita
AU  - Papaleo, Elena
AU  - Parisi, Gustavo
AU  - Pasche, Emilie
AU  - Barbosa Pereira, Pedro J
AU  - Promponas, Vasilis J
AU  - Pujols, Jordi
AU  - Quaglia, Federica
AU  - Ruch, Patrick
AU  - Salvatore, Marco
AU  - Schad, Eva
AU  - Szabo, Beata
AU  - Szaniszló, Tamás
AU  - Tamana, Stella
AU  - Tantos, Agnes
AU  - Veljković, Nevena V.
AU  - Ventura, Salvador
AU  - Vranken, Wim
AU  - Dosztányi, Zsuzsanna
AU  - Tompa, Peter
AU  - Tosatto, Silvio C E
AU  - Piovesan, Damiano
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8799
AB  - The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.
T2  - Nucleic Acids Research
T1  - DisProt: intrinsic protein disorder annotation in 2020
VL  - 48
IS  - D1
SP  - D269
EP  - D276
DO  - 10.1093/nar/gkz975
ER  - 
@article{
author = "Hatos, András and Hajdu-Soltész, Borbála and Monzon, Alexander M and Palopoli, Nicolas and Álvarez, Lucía and Aykac-Fas, Burcu and Bassot, Claudio and Benítez, Guillermo I and Bevilacqua, Martina and Chasapi, Anastasia and Chemes, Lucia and Davey, Norman E and Davidović, Radoslav S. and Dunker, A Keith and Elofsson, Arne and Gobeill, Julien and Foutel, Nicolás S González and Sudha, Govindarajan and Guharoy, Mainak and Horvath, Tamas and Iglesias, Valentin and Kajava, Andrey V. and Kovacs, Orsolya P and Lamb, John and Lambrughi, Matteo and Lazar, Tamas and Leclercq, Jeremy Y and Leonardi, Emanuela and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Maiani, Emiliano and Manso, José A and Marino-Buslje, Cristina and Martínez-Pérez, Elizabeth and Mészáros, Bálint and Mičetić, Ivan and Minervini, Giovanni and Murvai, Nikoletta and Necci, Marco and Ouzounis, Christos A and Pajkos, Mátyás and Paladin, Lisanna and Pancsa, Rita and Papaleo, Elena and Parisi, Gustavo and Pasche, Emilie and Barbosa Pereira, Pedro J and Promponas, Vasilis J and Pujols, Jordi and Quaglia, Federica and Ruch, Patrick and Salvatore, Marco and Schad, Eva and Szabo, Beata and Szaniszló, Tamás and Tamana, Stella and Tantos, Agnes and Veljković, Nevena V. and Ventura, Salvador and Vranken, Wim and Dosztányi, Zsuzsanna and Tompa, Peter and Tosatto, Silvio C E and Piovesan, Damiano",
year = "2019",
abstract = "The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.",
journal = "Nucleic Acids Research",
title = "DisProt: intrinsic protein disorder annotation in 2020",
volume = "48",
number = "D1",
pages = "D269-D276",
doi = "10.1093/nar/gkz975"
}
Hatos, A., Hajdu-Soltész, B., Monzon, A. M., Palopoli, N., Álvarez, L., Aykac-Fas, B., Bassot, C., Benítez, G. I., Bevilacqua, M., Chasapi, A., Chemes, L., Davey, N. E., Davidović, R. S., Dunker, A. K., Elofsson, A., Gobeill, J., Foutel, N. S. G., Sudha, G., Guharoy, M., Horvath, T., Iglesias, V., Kajava, A. V., Kovacs, O. P., Lamb, J., Lambrughi, M., Lazar, T., Leclercq, J. Y., Leonardi, E., Macedo-Ribeiro, S., Macossay-Castillo, M., Maiani, E., Manso, J. A., Marino-Buslje, C., Martínez-Pérez, E., Mészáros, B., Mičetić, I., Minervini, G., Murvai, N., Necci, M., Ouzounis, C. A., Pajkos, M., Paladin, L., Pancsa, R., Papaleo, E., Parisi, G., Pasche, E., Barbosa Pereira, P. J., Promponas, V. J., Pujols, J., Quaglia, F., Ruch, P., Salvatore, M., Schad, E., Szabo, B., Szaniszló, T., Tamana, S., Tantos, A., Veljković, N. V., Ventura, S., Vranken, W., Dosztányi, Z., Tompa, P., Tosatto, S. C. E.,& Piovesan, D.. (2019). DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research, 48(D1), D269-D276.
https://doi.org/10.1093/nar/gkz975
Hatos A, Hajdu-Soltész B, Monzon AM, Palopoli N, Álvarez L, Aykac-Fas B, Bassot C, Benítez GI, Bevilacqua M, Chasapi A, Chemes L, Davey NE, Davidović RS, Dunker AK, Elofsson A, Gobeill J, Foutel NSG, Sudha G, Guharoy M, Horvath T, Iglesias V, Kajava AV, Kovacs OP, Lamb J, Lambrughi M, Lazar T, Leclercq JY, Leonardi E, Macedo-Ribeiro S, Macossay-Castillo M, Maiani E, Manso JA, Marino-Buslje C, Martínez-Pérez E, Mészáros B, Mičetić I, Minervini G, Murvai N, Necci M, Ouzounis CA, Pajkos M, Paladin L, Pancsa R, Papaleo E, Parisi G, Pasche E, Barbosa Pereira PJ, Promponas VJ, Pujols J, Quaglia F, Ruch P, Salvatore M, Schad E, Szabo B, Szaniszló T, Tamana S, Tantos A, Veljković NV, Ventura S, Vranken W, Dosztányi Z, Tompa P, Tosatto SCE, Piovesan D. DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research. 2019;48(D1):D269-D276.
doi:10.1093/nar/gkz975 .
Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M, Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I, Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E, Davidović, Radoslav S., Dunker, A Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P, Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y, Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A, Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J, Promponas, Vasilis J, Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljković, Nevena V., Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C E, Piovesan, Damiano, "DisProt: intrinsic protein disorder annotation in 2020" in Nucleic Acids Research, 48, no. D1 (2019):D269-D276,
https://doi.org/10.1093/nar/gkz975 . .
22
208
98
174

Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes

Gemović, Branislava S.; Šumonja, Neven; Davidović, Radoslav; Perović, Vladimir; Veljković, Nevena V.

(2019)

TY  - JOUR
AU  - Gemović, Branislava S.
AU  - Šumonja, Neven
AU  - Davidović, Radoslav
AU  - Perović, Vladimir
AU  - Veljković, Nevena V.
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10775
AB  - Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology.

Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions.

Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions.

Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs.

Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.
T2  - Current Medicinal Chemistry
T1  - Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes
VL  - 26
IS  - 21
SP  - 3890
EP  - 3910
DO  - 10.2174/0929867325666180214113704
ER  - 
@article{
author = "Gemović, Branislava S. and Šumonja, Neven and Davidović, Radoslav and Perović, Vladimir and Veljković, Nevena V.",
year = "2019",
abstract = "Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology.

Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions.

Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions.

Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs.

Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.",
journal = "Current Medicinal Chemistry",
title = "Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes",
volume = "26",
number = "21",
pages = "3890-3910",
doi = "10.2174/0929867325666180214113704"
}
Gemović, B. S., Šumonja, N., Davidović, R., Perović, V.,& Veljković, N. V.. (2019). Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes. in Current Medicinal Chemistry, 26(21), 3890-3910.
https://doi.org/10.2174/0929867325666180214113704
Gemović BS, Šumonja N, Davidović R, Perović V, Veljković NV. Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes. in Current Medicinal Chemistry. 2019;26(21):3890-3910.
doi:10.2174/0929867325666180214113704 .
Gemović, Branislava S., Šumonja, Neven, Davidović, Radoslav, Perović, Vladimir, Veljković, Nevena V., "Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes" in Current Medicinal Chemistry, 26, no. 21 (2019):3890-3910,
https://doi.org/10.2174/0929867325666180214113704 . .
1
9
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9

Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets

Stevanović, Strahinja; Senćanski, Milan V.; Danel, Mathieu; Menendez, Christophe; Belguedj, Roumaissa; Bouraiou, Abdelmalek; Nikolić, Katarina M.; Cojean, Sandrine; Loiseau, Philippe Marie; Glišić, Sanja; Baltas, Michel; García-Sosa, Alfonso T.

(2019)

TY  - JOUR
AU  - Stevanović, Strahinja
AU  - Senćanski, Milan V.
AU  - Danel, Mathieu
AU  - Menendez, Christophe
AU  - Belguedj, Roumaissa
AU  - Bouraiou, Abdelmalek
AU  - Nikolić, Katarina M.
AU  - Cojean, Sandrine
AU  - Loiseau, Philippe Marie
AU  - Glišić, Sanja
AU  - Baltas, Michel
AU  - García-Sosa, Alfonso T.
PY  - 2019
UR  - https://www.mdpi.com/1420-3049/24/7/1282
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8137
AB  - Due to the lack of approved vaccines against human leishmaniasis and the limitations of the current chemotherapy inducing side effects and drug resistance, development of new, effective chemotherapeutic agents is essential. This study describes the synthesis of a series of novel oxadiazoles and indolizine-containing compounds. The compounds were screened in silico using an EIIP/AQVN filter followed by ligand-based virtual screening and molecular docking to parasite arginase. Top hits were further screened versus human arginase and finally against an anti-target battery to tag their possible interactions with proteins essential for the metabolism and clearance of many substances. Eight candidate compounds were selected for further experimental testing. The results show measurable in vitro anti-leishmanial activity for three compounds. One compound with an IC50 value of 2.18 µM on Leishmania donovani intramacrophage amastigotes is clearly better positioned than the others as an interesting molecular template for further development of new anti-leishmanial agents.
T2  - Molecules
T1  - Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets
VL  - 24
IS  - 7
SP  - 1282
DO  - 10.3390/molecules24071282
ER  - 
@article{
author = "Stevanović, Strahinja and Senćanski, Milan V. and Danel, Mathieu and Menendez, Christophe and Belguedj, Roumaissa and Bouraiou, Abdelmalek and Nikolić, Katarina M. and Cojean, Sandrine and Loiseau, Philippe Marie and Glišić, Sanja and Baltas, Michel and García-Sosa, Alfonso T.",
year = "2019",
abstract = "Due to the lack of approved vaccines against human leishmaniasis and the limitations of the current chemotherapy inducing side effects and drug resistance, development of new, effective chemotherapeutic agents is essential. This study describes the synthesis of a series of novel oxadiazoles and indolizine-containing compounds. The compounds were screened in silico using an EIIP/AQVN filter followed by ligand-based virtual screening and molecular docking to parasite arginase. Top hits were further screened versus human arginase and finally against an anti-target battery to tag their possible interactions with proteins essential for the metabolism and clearance of many substances. Eight candidate compounds were selected for further experimental testing. The results show measurable in vitro anti-leishmanial activity for three compounds. One compound with an IC50 value of 2.18 µM on Leishmania donovani intramacrophage amastigotes is clearly better positioned than the others as an interesting molecular template for further development of new anti-leishmanial agents.",
journal = "Molecules",
title = "Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets",
volume = "24",
number = "7",
pages = "1282",
doi = "10.3390/molecules24071282"
}
Stevanović, S., Senćanski, M. V., Danel, M., Menendez, C., Belguedj, R., Bouraiou, A., Nikolić, K. M., Cojean, S., Loiseau, P. M., Glišić, S., Baltas, M.,& García-Sosa, A. T.. (2019). Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets. in Molecules, 24(7), 1282.
https://doi.org/10.3390/molecules24071282
Stevanović S, Senćanski MV, Danel M, Menendez C, Belguedj R, Bouraiou A, Nikolić KM, Cojean S, Loiseau PM, Glišić S, Baltas M, García-Sosa AT. Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets. in Molecules. 2019;24(7):1282.
doi:10.3390/molecules24071282 .
Stevanović, Strahinja, Senćanski, Milan V., Danel, Mathieu, Menendez, Christophe, Belguedj, Roumaissa, Bouraiou, Abdelmalek, Nikolić, Katarina M., Cojean, Sandrine, Loiseau, Philippe Marie, Glišić, Sanja, Baltas, Michel, García-Sosa, Alfonso T., "Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets" in Molecules, 24, no. 7 (2019):1282,
https://doi.org/10.3390/molecules24071282 . .
3
16
8
16

Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors

Radošević, Draginja; Senćanski, Milan V.; Perović, Vladimir R.; Veljković, Nevena V.; Prljić, Jelena; Veljković, Veljko; Mantlo, Emily; Bukreyeva, Natalya; Paessler, Slobodan; Glišić, Sanja

(2019)

TY  - JOUR
AU  - Radošević, Draginja
AU  - Senćanski, Milan V.
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
AU  - Prljić, Jelena
AU  - Veljković, Veljko
AU  - Mantlo, Emily
AU  - Bukreyeva, Natalya
AU  - Paessler, Slobodan
AU  - Glišić, Sanja
PY  - 2019
UR  - https://www.frontiersin.org/article/10.3389/fcimb.2019.00067/full
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8163
AB  - Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture. © 2019 Radosevic, Sencanski, Perovic, Veljkovic, Prljic, Veljkovic, Mantlo, Bukreyeva, Paessler and Glisic.
T2  - Frontiers in Cellular and Infection Microbiology
T1  - Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors
VL  - 9
SP  - 67
DO  - 10.3389/fcimb.2019.00067
ER  - 
@article{
author = "Radošević, Draginja and Senćanski, Milan V. and Perović, Vladimir R. and Veljković, Nevena V. and Prljić, Jelena and Veljković, Veljko and Mantlo, Emily and Bukreyeva, Natalya and Paessler, Slobodan and Glišić, Sanja",
year = "2019",
abstract = "Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture. © 2019 Radosevic, Sencanski, Perovic, Veljkovic, Prljic, Veljkovic, Mantlo, Bukreyeva, Paessler and Glisic.",
journal = "Frontiers in Cellular and Infection Microbiology",
title = "Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors",
volume = "9",
pages = "67",
doi = "10.3389/fcimb.2019.00067"
}
Radošević, D., Senćanski, M. V., Perović, V. R., Veljković, N. V., Prljić, J., Veljković, V., Mantlo, E., Bukreyeva, N., Paessler, S.,& Glišić, S.. (2019). Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors. in Frontiers in Cellular and Infection Microbiology, 9, 67.
https://doi.org/10.3389/fcimb.2019.00067
Radošević D, Senćanski MV, Perović VR, Veljković NV, Prljić J, Veljković V, Mantlo E, Bukreyeva N, Paessler S, Glišić S. Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors. in Frontiers in Cellular and Infection Microbiology. 2019;9:67.
doi:10.3389/fcimb.2019.00067 .
Radošević, Draginja, Senćanski, Milan V., Perović, Vladimir R., Veljković, Nevena V., Prljić, Jelena, Veljković, Veljko, Mantlo, Emily, Bukreyeva, Natalya, Paessler, Slobodan, Glišić, Sanja, "Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors" in Frontiers in Cellular and Infection Microbiology, 9 (2019):67,
https://doi.org/10.3389/fcimb.2019.00067 . .
1
19
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18

Automated feature engineering improves prediction of protein–protein interactions

Šumonja, Neven; Gemović, Branislava S.; Veljković, Nevena V.; Perović, Vladimir R.

(2019)

TY  - JOUR
AU  - Šumonja, Neven
AU  - Gemović, Branislava S.
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8395
AB  - Over the last decade, various machine learning (ML) and statistical approaches for protein–protein interaction (PPI) predictions have been developed to help annotating functional interactions among proteins, essential for our system-level understanding of life. Efficient ML approaches require informative and non-redundant features. In this paper, we introduce novel types of expert-crafted sequence, evolutionary and graph features and apply automatic feature engineering to further expand feature space to improve predictive modeling. The two-step automatic feature-engineering process encompasses the hybrid method for feature generation and unsupervised feature selection, followed by supervised feature selection through a genetic algorithm (GA). The optimization of both steps allows the feature-engineering procedure to operate on a large transformed feature space with no considerable computational cost and to efficiently provide newly engineered features. Based on GA and correlation filtering, we developed a stacking algorithm GA-STACK for automatic ensembling of different ML algorithms to improve prediction performance. We introduced a unified method, HP-GAS, for the prediction of human PPIs, which incorporates GA-STACK and rests on both expert-crafted and 40% of newly engineered features. The extensive cross validation and comparison with the state-of-the-art methods showed that HP-GAS represents currently the most efficient method for proteome-wide forecasting of protein interactions, with prediction efficacy of 0.93 AUC and 0.85 accuracy. We implemented the HP-GAS method as a free standalone application which is a time-efficient and easy-to-use tool. HP-GAS software with supplementary data can be downloaded from: http://www.vinca.rs/180/tools/HP-GAS.php. © 2019, Springer-Verlag GmbH Austria, part of Springer Nature.
T2  - Amino Acids
T1  - Automated feature engineering improves prediction of protein–protein interactions
VL  - 51
IS  - 8
SP  - 1187
EP  - 1200
DO  - 10.1007/s00726-019-02756-9
ER  - 
@article{
author = "Šumonja, Neven and Gemović, Branislava S. and Veljković, Nevena V. and Perović, Vladimir R.",
year = "2019",
abstract = "Over the last decade, various machine learning (ML) and statistical approaches for protein–protein interaction (PPI) predictions have been developed to help annotating functional interactions among proteins, essential for our system-level understanding of life. Efficient ML approaches require informative and non-redundant features. In this paper, we introduce novel types of expert-crafted sequence, evolutionary and graph features and apply automatic feature engineering to further expand feature space to improve predictive modeling. The two-step automatic feature-engineering process encompasses the hybrid method for feature generation and unsupervised feature selection, followed by supervised feature selection through a genetic algorithm (GA). The optimization of both steps allows the feature-engineering procedure to operate on a large transformed feature space with no considerable computational cost and to efficiently provide newly engineered features. Based on GA and correlation filtering, we developed a stacking algorithm GA-STACK for automatic ensembling of different ML algorithms to improve prediction performance. We introduced a unified method, HP-GAS, for the prediction of human PPIs, which incorporates GA-STACK and rests on both expert-crafted and 40% of newly engineered features. The extensive cross validation and comparison with the state-of-the-art methods showed that HP-GAS represents currently the most efficient method for proteome-wide forecasting of protein interactions, with prediction efficacy of 0.93 AUC and 0.85 accuracy. We implemented the HP-GAS method as a free standalone application which is a time-efficient and easy-to-use tool. HP-GAS software with supplementary data can be downloaded from: http://www.vinca.rs/180/tools/HP-GAS.php. © 2019, Springer-Verlag GmbH Austria, part of Springer Nature.",
journal = "Amino Acids",
title = "Automated feature engineering improves prediction of protein–protein interactions",
volume = "51",
number = "8",
pages = "1187-1200",
doi = "10.1007/s00726-019-02756-9"
}
Šumonja, N., Gemović, B. S., Veljković, N. V.,& Perović, V. R.. (2019). Automated feature engineering improves prediction of protein–protein interactions. in Amino Acids, 51(8), 1187-1200.
https://doi.org/10.1007/s00726-019-02756-9
Šumonja N, Gemović BS, Veljković NV, Perović VR. Automated feature engineering improves prediction of protein–protein interactions. in Amino Acids. 2019;51(8):1187-1200.
doi:10.1007/s00726-019-02756-9 .
Šumonja, Neven, Gemović, Branislava S., Veljković, Nevena V., Perović, Vladimir R., "Automated feature engineering improves prediction of protein–protein interactions" in Amino Acids, 51, no. 8 (2019):1187-1200,
https://doi.org/10.1007/s00726-019-02756-9 . .
1
17
7
15

Functional characterization of β2-adrenergic and insulin receptor heteromers

Susec, Maja; Senćanski, Milan V.; Glišić, Sanja; Veljković, Nevena V.; Pedersen, Christina; Drinovec, Luka; Stojan, Jurij; Nøhr, Jane; Vrecl, Milka

(2019)

TY  - JOUR
AU  - Susec, Maja
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
AU  - Veljković, Nevena V.
AU  - Pedersen, Christina
AU  - Drinovec, Luka
AU  - Stojan, Jurij
AU  - Nøhr, Jane
AU  - Vrecl, Milka
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8490
AB  - This study aimed to functionally characterize β2-adrenergic (β2AR) and insulin receptor (IR) heteromers in regard to β-arrestin 2 (βarr2) recruitment and cAMP signaling and to examine the involvement of the cytoplasmic portion of the IR β chain in heteromerization with β2AR. Evidence for β2AR:IR:βarr2 complex formation and the specificity of the IR:βarr2 interaction was first provided by bioinfomatics analysis. Receptor-heteromer investigation technology (HIT) then provided functional evidence of β2AR:IR heterodimerization by showing isoproterenol-induced but not insulin-induced GFP2-βarr2 recruitment to the β2AR:IR complex; the IR:βarr2 interaction was found to only be constitutive. The constitutive IR:βarr2 BRET signal (BRETconst) was significantly smaller in cells coexpressing IR-RLuc8 and a GFP2-βarr2 1–185 mutant lacking the proposed IR binding domain. β2AR:IR heteromerization also influenced the pharmacological phenotype of β2AR, i.e., its efficacy in recruiting βarr2 and activating cAMP signaling. Evidence suggesting involvement of the cytoplasmic portion of the IR β chain in the interaction with β2AR was provided by BRET2 saturation and HIT assays using an IR 1–1271 stop mutant lacking the IR C-terminal tail region. For the complex consisting of IR 1–1271–RLuc8:β2AR-GFP2, saturation was not reached, most likely reflecting random collisions between IR 1–1271 and β2AR. Furthermore, in the HIT assay, no substantial agonist-induced increase in the BRET2 signal was detected that would be indicative of βarr2 recruitment to the IR 1–1271:β2AR heteromer. Complementary 3D visualization of β2AR:IR provided supporting evidence for stability of the heterotetramer complex and identified amino acid residues involved in β2AR:IR heteromerization. © 2019
T2  - Neuropharmacology
T1  - Functional characterization of β2-adrenergic and insulin receptor heteromers
VL  - 152
SP  - 78
EP  - 89
DO  - 10.1016/j.neuropharm.2019.01.025
ER  - 
@article{
author = "Susec, Maja and Senćanski, Milan V. and Glišić, Sanja and Veljković, Nevena V. and Pedersen, Christina and Drinovec, Luka and Stojan, Jurij and Nøhr, Jane and Vrecl, Milka",
year = "2019",
abstract = "This study aimed to functionally characterize β2-adrenergic (β2AR) and insulin receptor (IR) heteromers in regard to β-arrestin 2 (βarr2) recruitment and cAMP signaling and to examine the involvement of the cytoplasmic portion of the IR β chain in heteromerization with β2AR. Evidence for β2AR:IR:βarr2 complex formation and the specificity of the IR:βarr2 interaction was first provided by bioinfomatics analysis. Receptor-heteromer investigation technology (HIT) then provided functional evidence of β2AR:IR heterodimerization by showing isoproterenol-induced but not insulin-induced GFP2-βarr2 recruitment to the β2AR:IR complex; the IR:βarr2 interaction was found to only be constitutive. The constitutive IR:βarr2 BRET signal (BRETconst) was significantly smaller in cells coexpressing IR-RLuc8 and a GFP2-βarr2 1–185 mutant lacking the proposed IR binding domain. β2AR:IR heteromerization also influenced the pharmacological phenotype of β2AR, i.e., its efficacy in recruiting βarr2 and activating cAMP signaling. Evidence suggesting involvement of the cytoplasmic portion of the IR β chain in the interaction with β2AR was provided by BRET2 saturation and HIT assays using an IR 1–1271 stop mutant lacking the IR C-terminal tail region. For the complex consisting of IR 1–1271–RLuc8:β2AR-GFP2, saturation was not reached, most likely reflecting random collisions between IR 1–1271 and β2AR. Furthermore, in the HIT assay, no substantial agonist-induced increase in the BRET2 signal was detected that would be indicative of βarr2 recruitment to the IR 1–1271:β2AR heteromer. Complementary 3D visualization of β2AR:IR provided supporting evidence for stability of the heterotetramer complex and identified amino acid residues involved in β2AR:IR heteromerization. © 2019",
journal = "Neuropharmacology",
title = "Functional characterization of β2-adrenergic and insulin receptor heteromers",
volume = "152",
pages = "78-89",
doi = "10.1016/j.neuropharm.2019.01.025"
}
Susec, M., Senćanski, M. V., Glišić, S., Veljković, N. V., Pedersen, C., Drinovec, L., Stojan, J., Nøhr, J.,& Vrecl, M.. (2019). Functional characterization of β2-adrenergic and insulin receptor heteromers. in Neuropharmacology, 152, 78-89.
https://doi.org/10.1016/j.neuropharm.2019.01.025
Susec M, Senćanski MV, Glišić S, Veljković NV, Pedersen C, Drinovec L, Stojan J, Nøhr J, Vrecl M. Functional characterization of β2-adrenergic and insulin receptor heteromers. in Neuropharmacology. 2019;152:78-89.
doi:10.1016/j.neuropharm.2019.01.025 .
Susec, Maja, Senćanski, Milan V., Glišić, Sanja, Veljković, Nevena V., Pedersen, Christina, Drinovec, Luka, Stojan, Jurij, Nøhr, Jane, Vrecl, Milka, "Functional characterization of β2-adrenergic and insulin receptor heteromers" in Neuropharmacology, 152 (2019):78-89,
https://doi.org/10.1016/j.neuropharm.2019.01.025 . .
6
3
6

Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)

Senćanski, Milan V.; Glišić, Sanja; Šnajder, Marko; Veljković, Nevena V.; Poklar Ulrih, Nataša; Mavri, Janez; Vrecl, Milka

(2019)

TY  - JOUR
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
AU  - Šnajder, Marko
AU  - Veljković, Nevena V.
AU  - Poklar Ulrih, Nataša
AU  - Mavri, Janez
AU  - Vrecl, Milka
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8648
AB  - This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).
T2  - Scientific Reports
T1  - Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)
VL  - 9
IS  - 1
SP  - 16555
DO  - 10.1038/s41598-019-52934-8
ER  - 
@article{
author = "Senćanski, Milan V. and Glišić, Sanja and Šnajder, Marko and Veljković, Nevena V. and Poklar Ulrih, Nataša and Mavri, Janez and Vrecl, Milka",
year = "2019",
abstract = "This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).",
journal = "Scientific Reports",
title = "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)",
volume = "9",
number = "1",
pages = "16555",
doi = "10.1038/s41598-019-52934-8"
}
Senćanski, M. V., Glišić, S., Šnajder, M., Veljković, N. V., Poklar Ulrih, N., Mavri, J.,& Vrecl, M.. (2019). Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR). in Scientific Reports, 9(1), 16555.
https://doi.org/10.1038/s41598-019-52934-8
Senćanski MV, Glišić S, Šnajder M, Veljković NV, Poklar Ulrih N, Mavri J, Vrecl M. Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR). in Scientific Reports. 2019;9(1):16555.
doi:10.1038/s41598-019-52934-8 .
Senćanski, Milan V., Glišić, Sanja, Šnajder, Marko, Veljković, Nevena V., Poklar Ulrih, Nataša, Mavri, Janez, Vrecl, Milka, "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)" in Scientific Reports, 9, no. 1 (2019):16555,
https://doi.org/10.1038/s41598-019-52934-8 . .
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The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Zhou, Naihui; Jiang, Yuxiang; Bergquist, Timothy R; Lee, Alexandra J; Kacsoh, Balint Z; Crocker, Alex W; Lewis, Kimberley A; Georghiou, George; Nguyen, Huy N; Hamid, Md Nafiz; Davis, Larry; Dogan, Tunca; Atalay, Volkan; Rifaioglu, Ahmet S; Dalkıran, Alperen; Cetin Atalay, Rengul; Zhang, Chengxin; Hurto, Rebecca L; Freddolino, Peter L; Zhang, Yang; Bhat, Prajwal; Supek, Fran; Fernández, José M; Gemović, Branislava S.; Perović, Vladimir R.; Davidović, Radoslav S.; Šumonja, Neven; Veljković, Nevena V.; Asgari, Ehsaneddin; Mofrad, Mohammad R.K.; Profiti, Giuseppe; Savojardo, Castrense; Martelli, Pier Luigi; Casadio, Rita; Boecker, Florian; Schoof, Heiko; Kahanda, Indika; Thurlby, Natalie; McHardy, Alice C; Renaux, Alexandre; Saidi, Rabie; Gough, Julian; Freitas, Alex A; Antczak, Magdalena; Fabris, Fabio; Wass, Mark N; Hou, Jie; Cheng, Jianlin; Wang, Zheng; Romero, Alfonso E; Paccanaro, Alberto; Yang, Haixuan; Goldberg, Tatyana; Zhao, Chenguang; Holm, Liisa; Törönen, Petri; Medlar, Alan J; Zosa, Elaine; Borukhov, Itamar; Novikov, Ilya; Wilkins, Angela; Lichtarge, Olivier; Chi, Po-Han; Tseng, Wei-Cheng; Linial, Michal; Rose, Peter W; Dessimoz, Christophe; Vidulin, Vedrana; Dzeroski, Saso; Sillitoe, Ian; Das, Sayoni; Lees, Jonathan Gill; Jones, David T; Wan, Cen; Cozzetto, Domenico; Fa, Rui; Torres, Mateo; Warwick Vesztrocy, Alex; Rodriguez, Jose Manuel; Tress, Michael L; Frasca, Marco; Notaro, Marco; Grossi, Giuliano; Petrini, Alessandro; Re, Matteo; Valentini, Giorgio; Mesiti, Marco; Roche, Daniel B; Reeb, Jonas; Ritchie, David W; Aridhi, Sabeur; Alborzi, Seyed Ziaeddin; Devignes, Marie-Dominique; Koo, Da Chen Emily; Bonneau, Richard; Gligorijević, Vladimir; Barot, Meet; Fang, Hai; Toppo, Stefano; Lavezzo, Enrico; Falda, Marco; Berselli, Michele; Tosatto, Silvio C.E.; Carraro, Marco; Piovesan, Damiano; Ur Rehman, Hafeez; Mao, Qizhong; Zhang, Shanshan; Vucetic, Slobodan; Black, Gage S; Jo, Dane; Suh, Erica; Dayton, Jonathan B; Larsen, Dallas J; Omdahl, Ashton R; McGuffin, Liam J; Brackenridge, Danielle A; Babbitt, Patricia C; Yunes, Jeffrey M; Fontana, Paolo; Zhang, Feng; Zhu, Shanfeng; You, Ronghui; Zhang, Zihan; Dai, Suyang; Yao, Shuwei; Tian, Weidong; Cao, Renzhi; Chandler, Caleb; Amezola, Miguel; Johnson, Devon; Chang, Jia-Ming; Liao, Wen-Hung; Liu, Yi-Wei; Pascarelli, Stefano; Frank, Yotam; Hoehndorf, Robert; Kulmanov, Maxat; Boudellioua, Imane; Politano, Gianfranco; Di Carlo, Stefano; Benso, Alfredo; Hakala, Kai; Ginter, Filip; Mehryary, Farrokh; Kaewphan, Suwisa; Björne, Jari; Moen, Hans; Tolvanen, Martti E.E.; Salakoski, Tapio; Kihara, Daisuke; Jain, Aashish; Šmuc, Tomislav; Altenhoff, Adrian; Ben-Hur, Asa; Rost, Burkhard; Brenner, Steven E; Orengo, Christine A; Jeffery, Constance J; Bosco, Giovanni; Hogan, Deborah A; Martin, Maria J; O’Donovan, Claire; Mooney, Sean D; Greene, Casey S; Radivojac, Predrag; Friedberg, Iddo

(2019)

TY  - JOUR
AU  - Zhou, Naihui
AU  - Jiang, Yuxiang
AU  - Bergquist, Timothy R
AU  - Lee, Alexandra J
AU  - Kacsoh, Balint Z
AU  - Crocker, Alex W
AU  - Lewis, Kimberley A
AU  - Georghiou, George
AU  - Nguyen, Huy N
AU  - Hamid, Md Nafiz
AU  - Davis, Larry
AU  - Dogan, Tunca
AU  - Atalay, Volkan
AU  - Rifaioglu, Ahmet S
AU  - Dalkıran, Alperen
AU  - Cetin Atalay, Rengul
AU  - Zhang, Chengxin
AU  - Hurto, Rebecca L
AU  - Freddolino, Peter L
AU  - Zhang, Yang
AU  - Bhat, Prajwal
AU  - Supek, Fran
AU  - Fernández, José M
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Davidović, Radoslav S.
AU  - Šumonja, Neven
AU  - Veljković, Nevena V.
AU  - Asgari, Ehsaneddin
AU  - Mofrad, Mohammad R.K.
AU  - Profiti, Giuseppe
AU  - Savojardo, Castrense
AU  - Martelli, Pier Luigi
AU  - Casadio, Rita
AU  - Boecker, Florian
AU  - Schoof, Heiko
AU  - Kahanda, Indika
AU  - Thurlby, Natalie
AU  - McHardy, Alice C
AU  - Renaux, Alexandre
AU  - Saidi, Rabie
AU  - Gough, Julian
AU  - Freitas, Alex A
AU  - Antczak, Magdalena
AU  - Fabris, Fabio
AU  - Wass, Mark N
AU  - Hou, Jie
AU  - Cheng, Jianlin
AU  - Wang, Zheng
AU  - Romero, Alfonso E
AU  - Paccanaro, Alberto
AU  - Yang, Haixuan
AU  - Goldberg, Tatyana
AU  - Zhao, Chenguang
AU  - Holm, Liisa
AU  - Törönen, Petri
AU  - Medlar, Alan J
AU  - Zosa, Elaine
AU  - Borukhov, Itamar
AU  - Novikov, Ilya
AU  - Wilkins, Angela
AU  - Lichtarge, Olivier
AU  - Chi, Po-Han
AU  - Tseng, Wei-Cheng
AU  - Linial, Michal
AU  - Rose, Peter W
AU  - Dessimoz, Christophe
AU  - Vidulin, Vedrana
AU  - Dzeroski, Saso
AU  - Sillitoe, Ian
AU  - Das, Sayoni
AU  - Lees, Jonathan Gill
AU  - Jones, David T
AU  - Wan, Cen
AU  - Cozzetto, Domenico
AU  - Fa, Rui
AU  - Torres, Mateo
AU  - Warwick Vesztrocy, Alex
AU  - Rodriguez, Jose Manuel
AU  - Tress, Michael L
AU  - Frasca, Marco
AU  - Notaro, Marco
AU  - Grossi, Giuliano
AU  - Petrini, Alessandro
AU  - Re, Matteo
AU  - Valentini, Giorgio
AU  - Mesiti, Marco
AU  - Roche, Daniel B
AU  - Reeb, Jonas
AU  - Ritchie, David W
AU  - Aridhi, Sabeur
AU  - Alborzi, Seyed Ziaeddin
AU  - Devignes, Marie-Dominique
AU  - Koo, Da Chen Emily
AU  - Bonneau, Richard
AU  - Gligorijević, Vladimir
AU  - Barot, Meet
AU  - Fang, Hai
AU  - Toppo, Stefano
AU  - Lavezzo, Enrico
AU  - Falda, Marco
AU  - Berselli, Michele
AU  - Tosatto, Silvio C.E.
AU  - Carraro, Marco
AU  - Piovesan, Damiano
AU  - Ur Rehman, Hafeez
AU  - Mao, Qizhong
AU  - Zhang, Shanshan
AU  - Vucetic, Slobodan
AU  - Black, Gage S
AU  - Jo, Dane
AU  - Suh, Erica
AU  - Dayton, Jonathan B
AU  - Larsen, Dallas J
AU  - Omdahl, Ashton R
AU  - McGuffin, Liam J
AU  - Brackenridge, Danielle A
AU  - Babbitt, Patricia C
AU  - Yunes, Jeffrey M
AU  - Fontana, Paolo
AU  - Zhang, Feng
AU  - Zhu, Shanfeng
AU  - You, Ronghui
AU  - Zhang, Zihan
AU  - Dai, Suyang
AU  - Yao, Shuwei
AU  - Tian, Weidong
AU  - Cao, Renzhi
AU  - Chandler, Caleb
AU  - Amezola, Miguel
AU  - Johnson, Devon
AU  - Chang, Jia-Ming
AU  - Liao, Wen-Hung
AU  - Liu, Yi-Wei
AU  - Pascarelli, Stefano
AU  - Frank, Yotam
AU  - Hoehndorf, Robert
AU  - Kulmanov, Maxat
AU  - Boudellioua, Imane
AU  - Politano, Gianfranco
AU  - Di Carlo, Stefano
AU  - Benso, Alfredo
AU  - Hakala, Kai
AU  - Ginter, Filip
AU  - Mehryary, Farrokh
AU  - Kaewphan, Suwisa
AU  - Björne, Jari
AU  - Moen, Hans
AU  - Tolvanen, Martti E.E.
AU  - Salakoski, Tapio
AU  - Kihara, Daisuke
AU  - Jain, Aashish
AU  - Šmuc, Tomislav
AU  - Altenhoff, Adrian
AU  - Ben-Hur, Asa
AU  - Rost, Burkhard
AU  - Brenner, Steven E
AU  - Orengo, Christine A
AU  - Jeffery, Constance J
AU  - Bosco, Giovanni
AU  - Hogan, Deborah A
AU  - Martin, Maria J
AU  - O’Donovan, Claire
AU  - Mooney, Sean D
AU  - Greene, Casey S
AU  - Radivojac, Predrag
AU  - Friedberg, Iddo
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8655
AB  - Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).
T2  - Genome Biology
T1  - The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
VL  - 20
IS  - 1
SP  - 244
DO  - 10.1186/s13059-019-1835-8
ER  - 
@article{
author = "Zhou, Naihui and Jiang, Yuxiang and Bergquist, Timothy R and Lee, Alexandra J and Kacsoh, Balint Z and Crocker, Alex W and Lewis, Kimberley A and Georghiou, George and Nguyen, Huy N and Hamid, Md Nafiz and Davis, Larry and Dogan, Tunca and Atalay, Volkan and Rifaioglu, Ahmet S and Dalkıran, Alperen and Cetin Atalay, Rengul and Zhang, Chengxin and Hurto, Rebecca L and Freddolino, Peter L and Zhang, Yang and Bhat, Prajwal and Supek, Fran and Fernández, José M and Gemović, Branislava S. and Perović, Vladimir R. and Davidović, Radoslav S. and Šumonja, Neven and Veljković, Nevena V. and Asgari, Ehsaneddin and Mofrad, Mohammad R.K. and Profiti, Giuseppe and Savojardo, Castrense and Martelli, Pier Luigi and Casadio, Rita and Boecker, Florian and Schoof, Heiko and Kahanda, Indika and Thurlby, Natalie and McHardy, Alice C and Renaux, Alexandre and Saidi, Rabie and Gough, Julian and Freitas, Alex A and Antczak, Magdalena and Fabris, Fabio and Wass, Mark N and Hou, Jie and Cheng, Jianlin and Wang, Zheng and Romero, Alfonso E and Paccanaro, Alberto and Yang, Haixuan and Goldberg, Tatyana and Zhao, Chenguang and Holm, Liisa and Törönen, Petri and Medlar, Alan J and Zosa, Elaine and Borukhov, Itamar and Novikov, Ilya and Wilkins, Angela and Lichtarge, Olivier and Chi, Po-Han and Tseng, Wei-Cheng and Linial, Michal and Rose, Peter W and Dessimoz, Christophe and Vidulin, Vedrana and Dzeroski, Saso and Sillitoe, Ian and Das, Sayoni and Lees, Jonathan Gill and Jones, David T and Wan, Cen and Cozzetto, Domenico and Fa, Rui and Torres, Mateo and Warwick Vesztrocy, Alex and Rodriguez, Jose Manuel and Tress, Michael L and Frasca, Marco and Notaro, Marco and Grossi, Giuliano and Petrini, Alessandro and Re, Matteo and Valentini, Giorgio and Mesiti, Marco and Roche, Daniel B and Reeb, Jonas and Ritchie, David W and Aridhi, Sabeur and Alborzi, Seyed Ziaeddin and Devignes, Marie-Dominique and Koo, Da Chen Emily and Bonneau, Richard and Gligorijević, Vladimir and Barot, Meet and Fang, Hai and Toppo, Stefano and Lavezzo, Enrico and Falda, Marco and Berselli, Michele and Tosatto, Silvio C.E. and Carraro, Marco and Piovesan, Damiano and Ur Rehman, Hafeez and Mao, Qizhong and Zhang, Shanshan and Vucetic, Slobodan and Black, Gage S and Jo, Dane and Suh, Erica and Dayton, Jonathan B and Larsen, Dallas J and Omdahl, Ashton R and McGuffin, Liam J and Brackenridge, Danielle A and Babbitt, Patricia C and Yunes, Jeffrey M and Fontana, Paolo and Zhang, Feng and Zhu, Shanfeng and You, Ronghui and Zhang, Zihan and Dai, Suyang and Yao, Shuwei and Tian, Weidong and Cao, Renzhi and Chandler, Caleb and Amezola, Miguel and Johnson, Devon and Chang, Jia-Ming and Liao, Wen-Hung and Liu, Yi-Wei and Pascarelli, Stefano and Frank, Yotam and Hoehndorf, Robert and Kulmanov, Maxat and Boudellioua, Imane and Politano, Gianfranco and Di Carlo, Stefano and Benso, Alfredo and Hakala, Kai and Ginter, Filip and Mehryary, Farrokh and Kaewphan, Suwisa and Björne, Jari and Moen, Hans and Tolvanen, Martti E.E. and Salakoski, Tapio and Kihara, Daisuke and Jain, Aashish and Šmuc, Tomislav and Altenhoff, Adrian and Ben-Hur, Asa and Rost, Burkhard and Brenner, Steven E and Orengo, Christine A and Jeffery, Constance J and Bosco, Giovanni and Hogan, Deborah A and Martin, Maria J and O’Donovan, Claire and Mooney, Sean D and Greene, Casey S and Radivojac, Predrag and Friedberg, Iddo",
year = "2019",
abstract = "Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).",
journal = "Genome Biology",
title = "The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens",
volume = "20",
number = "1",
pages = "244",
doi = "10.1186/s13059-019-1835-8"
}
Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M. N., Davis, L., Dogan, T., Atalay, V., Rifaioglu, A. S., Dalkıran, A., Cetin Atalay, R., Zhang, C., Hurto, R. L., Freddolino, P. L., Zhang, Y., Bhat, P., Supek, F., Fernández, J. M., Gemović, B. S., Perović, V. R., Davidović, R. S., Šumonja, N., Veljković, N. V., Asgari, E., Mofrad, M. R.K., Profiti, G., Savojardo, C., Martelli, P. L., Casadio, R., Boecker, F., Schoof, H., Kahanda, I., Thurlby, N., McHardy, A. C., Renaux, A., Saidi, R., Gough, J., Freitas, A. A., Antczak, M., Fabris, F., Wass, M. N., Hou, J., Cheng, J., Wang, Z., Romero, A. E., Paccanaro, A., Yang, H., Goldberg, T., Zhao, C., Holm, L., Törönen, P., Medlar, A. J., Zosa, E., Borukhov, I., Novikov, I., Wilkins, A., Lichtarge, O., Chi, P., Tseng, W., Linial, M., Rose, P. W., Dessimoz, C., Vidulin, V., Dzeroski, S., Sillitoe, I., Das, S., Lees, J. G., Jones, D. T., Wan, C., Cozzetto, D., Fa, R., Torres, M., Warwick Vesztrocy, A., Rodriguez, J. M., Tress, M. L., Frasca, M., Notaro, M., Grossi, G., Petrini, A., Re, M., Valentini, G., Mesiti, M., Roche, D. B., Reeb, J., Ritchie, D. W., Aridhi, S., Alborzi, S. Z., Devignes, M., Koo, D. C. E., Bonneau, R., Gligorijević, V., Barot, M., Fang, H., Toppo, S., Lavezzo, E., Falda, M., Berselli, M., Tosatto, S. C.E., Carraro, M., Piovesan, D., Ur Rehman, H., Mao, Q., Zhang, S., Vucetic, S., Black, G. S., Jo, D., Suh, E., Dayton, J. B., Larsen, D. J., Omdahl, A. R., McGuffin, L. J., Brackenridge, D. A., Babbitt, P. C., Yunes, J. M., Fontana, P., Zhang, F., Zhu, S., You, R., Zhang, Z., Dai, S., Yao, S., Tian, W., Cao, R., Chandler, C., Amezola, M., Johnson, D., Chang, J., Liao, W., Liu, Y., Pascarelli, S., Frank, Y., Hoehndorf, R., Kulmanov, M., Boudellioua, I., Politano, G., Di Carlo, S., Benso, A., Hakala, K., Ginter, F., Mehryary, F., Kaewphan, S., Björne, J., Moen, H., Tolvanen, M. E.E., Salakoski, T., Kihara, D., Jain, A., Šmuc, T., Altenhoff, A., Ben-Hur, A., Rost, B., Brenner, S. E., Orengo, C. A., Jeffery, C. J., Bosco, G., Hogan, D. A., Martin, M. J., O’Donovan, C., Mooney, S. D., Greene, C. S., Radivojac, P.,& Friedberg, I.. (2019). The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. in Genome Biology, 20(1), 244.
https://doi.org/10.1186/s13059-019-1835-8
Zhou N, Jiang Y, Bergquist TR, Lee AJ, Kacsoh BZ, Crocker AW, Lewis KA, Georghiou G, Nguyen HN, Hamid MN, Davis L, Dogan T, Atalay V, Rifaioglu AS, Dalkıran A, Cetin Atalay R, Zhang C, Hurto RL, Freddolino PL, Zhang Y, Bhat P, Supek F, Fernández JM, Gemović BS, Perović VR, Davidović RS, Šumonja N, Veljković NV, Asgari E, Mofrad MR, Profiti G, Savojardo C, Martelli PL, Casadio R, Boecker F, Schoof H, Kahanda I, Thurlby N, McHardy AC, Renaux A, Saidi R, Gough J, Freitas AA, Antczak M, Fabris F, Wass MN, Hou J, Cheng J, Wang Z, Romero AE, Paccanaro A, Yang H, Goldberg T, Zhao C, Holm L, Törönen P, Medlar AJ, Zosa E, Borukhov I, Novikov I, Wilkins A, Lichtarge O, Chi P, Tseng W, Linial M, Rose PW, Dessimoz C, Vidulin V, Dzeroski S, Sillitoe I, Das S, Lees JG, Jones DT, Wan C, Cozzetto D, Fa R, Torres M, Warwick Vesztrocy A, Rodriguez JM, Tress ML, Frasca M, Notaro M, Grossi G, Petrini A, Re M, Valentini G, Mesiti M, Roche DB, Reeb J, Ritchie DW, Aridhi S, Alborzi SZ, Devignes M, Koo DCE, Bonneau R, Gligorijević V, Barot M, Fang H, Toppo S, Lavezzo E, Falda M, Berselli M, Tosatto SC, Carraro M, Piovesan D, Ur Rehman H, Mao Q, Zhang S, Vucetic S, Black GS, Jo D, Suh E, Dayton JB, Larsen DJ, Omdahl AR, McGuffin LJ, Brackenridge DA, Babbitt PC, Yunes JM, Fontana P, Zhang F, Zhu S, You R, Zhang Z, Dai S, Yao S, Tian W, Cao R, Chandler C, Amezola M, Johnson D, Chang J, Liao W, Liu Y, Pascarelli S, Frank Y, Hoehndorf R, Kulmanov M, Boudellioua I, Politano G, Di Carlo S, Benso A, Hakala K, Ginter F, Mehryary F, Kaewphan S, Björne J, Moen H, Tolvanen ME, Salakoski T, Kihara D, Jain A, Šmuc T, Altenhoff A, Ben-Hur A, Rost B, Brenner SE, Orengo CA, Jeffery CJ, Bosco G, Hogan DA, Martin MJ, O’Donovan C, Mooney SD, Greene CS, Radivojac P, Friedberg I. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. in Genome Biology. 2019;20(1):244.
doi:10.1186/s13059-019-1835-8 .
Zhou, Naihui, Jiang, Yuxiang, Bergquist, Timothy R, Lee, Alexandra J, Kacsoh, Balint Z, Crocker, Alex W, Lewis, Kimberley A, Georghiou, George, Nguyen, Huy N, Hamid, Md Nafiz, Davis, Larry, Dogan, Tunca, Atalay, Volkan, Rifaioglu, Ahmet S, Dalkıran, Alperen, Cetin Atalay, Rengul, Zhang, Chengxin, Hurto, Rebecca L, Freddolino, Peter L, Zhang, Yang, Bhat, Prajwal, Supek, Fran, Fernández, José M, Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Šumonja, Neven, Veljković, Nevena V., Asgari, Ehsaneddin, Mofrad, Mohammad R.K., Profiti, Giuseppe, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita, Boecker, Florian, Schoof, Heiko, Kahanda, Indika, Thurlby, Natalie, McHardy, Alice C, Renaux, Alexandre, Saidi, Rabie, Gough, Julian, Freitas, Alex A, Antczak, Magdalena, Fabris, Fabio, Wass, Mark N, Hou, Jie, Cheng, Jianlin, Wang, Zheng, Romero, Alfonso E, Paccanaro, Alberto, Yang, Haixuan, Goldberg, Tatyana, Zhao, Chenguang, Holm, Liisa, Törönen, Petri, Medlar, Alan J, Zosa, Elaine, Borukhov, Itamar, Novikov, Ilya, Wilkins, Angela, Lichtarge, Olivier, Chi, Po-Han, Tseng, Wei-Cheng, Linial, Michal, Rose, Peter W, Dessimoz, Christophe, Vidulin, Vedrana, Dzeroski, Saso, Sillitoe, Ian, Das, Sayoni, Lees, Jonathan Gill, Jones, David T, Wan, Cen, Cozzetto, Domenico, Fa, Rui, Torres, Mateo, Warwick Vesztrocy, Alex, Rodriguez, Jose Manuel, Tress, Michael L, Frasca, Marco, Notaro, Marco, Grossi, Giuliano, Petrini, Alessandro, Re, Matteo, Valentini, Giorgio, Mesiti, Marco, Roche, Daniel B, Reeb, Jonas, Ritchie, David W, Aridhi, Sabeur, Alborzi, Seyed Ziaeddin, Devignes, Marie-Dominique, Koo, Da Chen Emily, Bonneau, Richard, Gligorijević, Vladimir, Barot, Meet, Fang, Hai, Toppo, Stefano, Lavezzo, Enrico, Falda, Marco, Berselli, Michele, Tosatto, Silvio C.E., Carraro, Marco, Piovesan, Damiano, Ur Rehman, Hafeez, Mao, Qizhong, Zhang, Shanshan, Vucetic, Slobodan, Black, Gage S, Jo, Dane, Suh, Erica, Dayton, Jonathan B, Larsen, Dallas J, Omdahl, Ashton R, McGuffin, Liam J, Brackenridge, Danielle A, Babbitt, Patricia C, Yunes, Jeffrey M, Fontana, Paolo, Zhang, Feng, Zhu, Shanfeng, You, Ronghui, Zhang, Zihan, Dai, Suyang, Yao, Shuwei, Tian, Weidong, Cao, Renzhi, Chandler, Caleb, Amezola, Miguel, Johnson, Devon, Chang, Jia-Ming, Liao, Wen-Hung, Liu, Yi-Wei, Pascarelli, Stefano, Frank, Yotam, Hoehndorf, Robert, Kulmanov, Maxat, Boudellioua, Imane, Politano, Gianfranco, Di Carlo, Stefano, Benso, Alfredo, Hakala, Kai, Ginter, Filip, Mehryary, Farrokh, Kaewphan, Suwisa, Björne, Jari, Moen, Hans, Tolvanen, Martti E.E., Salakoski, Tapio, Kihara, Daisuke, Jain, Aashish, Šmuc, Tomislav, Altenhoff, Adrian, Ben-Hur, Asa, Rost, Burkhard, Brenner, Steven E, Orengo, Christine A, Jeffery, Constance J, Bosco, Giovanni, Hogan, Deborah A, Martin, Maria J, O’Donovan, Claire, Mooney, Sean D, Greene, Casey S, Radivojac, Predrag, Friedberg, Iddo, "The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens" in Genome Biology, 20, no. 1 (2019):244,
https://doi.org/10.1186/s13059-019-1835-8 . .
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202

Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans

Milivojević, Dušan; Šumonja, Neven; Medić, Strahinja; Pavić, Aleksandar B.; Morić, Ivana; Vasiljević, Branka; Senerović, Lidija; Nikodinović-Runić, Jasmina

(2018)

TY  - JOUR
AU  - Milivojević, Dušan
AU  - Šumonja, Neven
AU  - Medić, Strahinja
AU  - Pavić, Aleksandar B.
AU  - Morić, Ivana
AU  - Vasiljević, Branka
AU  - Senerović, Lidija
AU  - Nikodinović-Runić, Jasmina
PY  - 2018
UR  - https://academic.oup.com/femspd/article/doi/10.1093/femspd/fty041/4978417
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7822
AB  - Pseudomonas aeruginosa has been amongst the top 10 'superbugs' worldwide and is causing infections with poor outcomes in both humans and animals. From 202 P. aeruginosa isolates (n = 121 animal and n = 81 human), 40 were selected on the basis of biofilm-forming ability and were comparatively characterized in terms of virulence determinants to the type strain P. aeruginosa PAO1. Biofilm formation, pyocyanin and hemolysin production, and bacterial motility patterns were compared with the ability to kill human cell line A549 in vitro. On average, there was no significant difference between levels of animal and human cytotoxicity, while human isolates produced higher amounts of pyocyanin, hemolysins and showed increased swimming ability. Non-parametric statistical analysis identified the highest positive correlation between hemolysis and the swarming ability. For the first time an ensemble machine learning approach used on the in vitro virulence data determined the highest relative predictive importance of the submerged biofilm formation for the cytotoxicity, as an indicator of the infection ability. The findings from the in vitro study were validated in vivo using zebrafish (Danio rerio) embryos. This study highlighted no major differences between P. aeruginosa species isolated from animal and human infections and the importance of pyocyanin production in cytotoxicity and infection ability. © FEMS 2018.
T2  - Pathogens and Disease
T1  - Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans
VL  - 76
IS  - 4
SP  - fty041
DO  - 10.1093/femspd/fty041
ER  - 
@article{
author = "Milivojević, Dušan and Šumonja, Neven and Medić, Strahinja and Pavić, Aleksandar B. and Morić, Ivana and Vasiljević, Branka and Senerović, Lidija and Nikodinović-Runić, Jasmina",
year = "2018",
abstract = "Pseudomonas aeruginosa has been amongst the top 10 'superbugs' worldwide and is causing infections with poor outcomes in both humans and animals. From 202 P. aeruginosa isolates (n = 121 animal and n = 81 human), 40 were selected on the basis of biofilm-forming ability and were comparatively characterized in terms of virulence determinants to the type strain P. aeruginosa PAO1. Biofilm formation, pyocyanin and hemolysin production, and bacterial motility patterns were compared with the ability to kill human cell line A549 in vitro. On average, there was no significant difference between levels of animal and human cytotoxicity, while human isolates produced higher amounts of pyocyanin, hemolysins and showed increased swimming ability. Non-parametric statistical analysis identified the highest positive correlation between hemolysis and the swarming ability. For the first time an ensemble machine learning approach used on the in vitro virulence data determined the highest relative predictive importance of the submerged biofilm formation for the cytotoxicity, as an indicator of the infection ability. The findings from the in vitro study were validated in vivo using zebrafish (Danio rerio) embryos. This study highlighted no major differences between P. aeruginosa species isolated from animal and human infections and the importance of pyocyanin production in cytotoxicity and infection ability. © FEMS 2018.",
journal = "Pathogens and Disease",
title = "Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans",
volume = "76",
number = "4",
pages = "fty041",
doi = "10.1093/femspd/fty041"
}
Milivojević, D., Šumonja, N., Medić, S., Pavić, A. B., Morić, I., Vasiljević, B., Senerović, L.,& Nikodinović-Runić, J.. (2018). Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans. in Pathogens and Disease, 76(4), fty041.
https://doi.org/10.1093/femspd/fty041
Milivojević D, Šumonja N, Medić S, Pavić AB, Morić I, Vasiljević B, Senerović L, Nikodinović-Runić J. Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans. in Pathogens and Disease. 2018;76(4):fty041.
doi:10.1093/femspd/fty041 .
Milivojević, Dušan, Šumonja, Neven, Medić, Strahinja, Pavić, Aleksandar B., Morić, Ivana, Vasiljević, Branka, Senerović, Lidija, Nikodinović-Runić, Jasmina, "Biofilm-forming ability and infection potential of Pseudomonas aeruginosa strains isolated from animals and humans" in Pathogens and Disease, 76, no. 4 (2018):fty041,
https://doi.org/10.1093/femspd/fty041 . .
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32

Genetic Markers for Coronary Artery Disease

Veljković, Nevena V.; Zarić, Božidarka; Đurić, Ilona; Obradović, Milan M.; Sudar-Milovanović, Emina; Radak, Đorđe J.; Isenović, Esma R.

(2018)

TY  - JOUR
AU  - Veljković, Nevena V.
AU  - Zarić, Božidarka
AU  - Đurić, Ilona
AU  - Obradović, Milan M.
AU  - Sudar-Milovanović, Emina
AU  - Radak, Đorđe J.
AU  - Isenović, Esma R.
PY  - 2018
UR  - http://www.mdpi.com/1010-660X/54/3/36
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7878
AB  - Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
T2  - Medicina
T1  - Genetic Markers for Coronary Artery Disease
VL  - 54
IS  - 3
SP  - 36
DO  - 10.3390/medicina54030036
ER  - 
@article{
author = "Veljković, Nevena V. and Zarić, Božidarka and Đurić, Ilona and Obradović, Milan M. and Sudar-Milovanović, Emina and Radak, Đorđe J. and Isenović, Esma R.",
year = "2018",
abstract = "Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.",
journal = "Medicina",
title = "Genetic Markers for Coronary Artery Disease",
volume = "54",
number = "3",
pages = "36",
doi = "10.3390/medicina54030036"
}
Veljković, N. V., Zarić, B., Đurić, I., Obradović, M. M., Sudar-Milovanović, E., Radak, Đ. J.,& Isenović, E. R.. (2018). Genetic Markers for Coronary Artery Disease. in Medicina, 54(3), 36.
https://doi.org/10.3390/medicina54030036
Veljković NV, Zarić B, Đurić I, Obradović MM, Sudar-Milovanović E, Radak ĐJ, Isenović ER. Genetic Markers for Coronary Artery Disease. in Medicina. 2018;54(3):36.
doi:10.3390/medicina54030036 .
Veljković, Nevena V., Zarić, Božidarka, Đurić, Ilona, Obradović, Milan M., Sudar-Milovanović, Emina, Radak, Đorđe J., Isenović, Esma R., "Genetic Markers for Coronary Artery Disease" in Medicina, 54, no. 3 (2018):36,
https://doi.org/10.3390/medicina54030036 . .
10
10
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10

Ibuprofen as a template molecule for drug design against Ebola virus

Paessler, Slobodan; Huang, Cheng; Senćanski, Milan V.; Veljković, Nevena V.; Perović, Vladimir R.; Glišić, Sanja; Veljković, Veljko

(2018)

TY  - JOUR
AU  - Paessler, Slobodan
AU  - Huang, Cheng
AU  - Senćanski, Milan V.
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
AU  - Glišić, Sanja
AU  - Veljković, Veljko
PY  - 2018
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7695
AB  - The Ebola virus outbreak in West Africa 2015 and Congo 2017, point out an urgent need for development of drugs against this important pathogen. Previously, by repurposing virtual screening of 6438 drugs from DrugBank, ibuprofen was selected as a possible inhibitor of the Ebola virus infection. The results of an additional docking analysis as well as experimental results showing measurable anti-Ebola effect of ibuprofen in cell culture suggest ibuprofen as a promising molecular template for the development of drugs for treatment of the infection by Ebola virus.
T2  - Frontiers in Bioscience - Landmark
T1  - Ibuprofen as a template molecule for drug design against Ebola virus
VL  - 23
IS  - 5
SP  - 947
EP  - 953
UR  - https://hdl.handle.net/21.15107/rcub_vinar_7695
ER  - 
@article{
author = "Paessler, Slobodan and Huang, Cheng and Senćanski, Milan V. and Veljković, Nevena V. and Perović, Vladimir R. and Glišić, Sanja and Veljković, Veljko",
year = "2018",
abstract = "The Ebola virus outbreak in West Africa 2015 and Congo 2017, point out an urgent need for development of drugs against this important pathogen. Previously, by repurposing virtual screening of 6438 drugs from DrugBank, ibuprofen was selected as a possible inhibitor of the Ebola virus infection. The results of an additional docking analysis as well as experimental results showing measurable anti-Ebola effect of ibuprofen in cell culture suggest ibuprofen as a promising molecular template for the development of drugs for treatment of the infection by Ebola virus.",
journal = "Frontiers in Bioscience - Landmark",
title = "Ibuprofen as a template molecule for drug design against Ebola virus",
volume = "23",
number = "5",
pages = "947-953",
url = "https://hdl.handle.net/21.15107/rcub_vinar_7695"
}
Paessler, S., Huang, C., Senćanski, M. V., Veljković, N. V., Perović, V. R., Glišić, S.,& Veljković, V.. (2018). Ibuprofen as a template molecule for drug design against Ebola virus. in Frontiers in Bioscience - Landmark, 23(5), 947-953.
https://hdl.handle.net/21.15107/rcub_vinar_7695
Paessler S, Huang C, Senćanski MV, Veljković NV, Perović VR, Glišić S, Veljković V. Ibuprofen as a template molecule for drug design against Ebola virus. in Frontiers in Bioscience - Landmark. 2018;23(5):947-953.
https://hdl.handle.net/21.15107/rcub_vinar_7695 .
Paessler, Slobodan, Huang, Cheng, Senćanski, Milan V., Veljković, Nevena V., Perović, Vladimir R., Glišić, Sanja, Veljković, Veljko, "Ibuprofen as a template molecule for drug design against Ebola virus" in Frontiers in Bioscience - Landmark, 23, no. 5 (2018):947-953,
https://hdl.handle.net/21.15107/rcub_vinar_7695 .
18

IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins

Perović, Vladimir R.; Šumonja, Neven; Marsh, Lindsey A.; Radovanović, Sandro; Vukićević, Milan; Roberts, Stefan G. E.; Veljković, Nevena V.

(2018)

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Marsh, Lindsey A.
AU  - Radovanović, Sandro
AU  - Vukićević, Milan
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2018
UR  - http://www.nature.com/articles/s41598-018-28815-x
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7811
AB  - Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).
T2  - Scientific Reports
T1  - IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins
VL  - 8
IS  - 1
SP  - 10563
DO  - 10.1038/s41598-018-28815-x
ER  - 
@article{
author = "Perović, Vladimir R. and Šumonja, Neven and Marsh, Lindsey A. and Radovanović, Sandro and Vukićević, Milan and Roberts, Stefan G. E. and Veljković, Nevena V.",
year = "2018",
abstract = "Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).",
journal = "Scientific Reports",
title = "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins",
volume = "8",
number = "1",
pages = "10563",
doi = "10.1038/s41598-018-28815-x"
}
Perović, V. R., Šumonja, N., Marsh, L. A., Radovanović, S., Vukićević, M., Roberts, S. G. E.,& Veljković, N. V.. (2018). IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports, 8(1), 10563.
https://doi.org/10.1038/s41598-018-28815-x
Perović VR, Šumonja N, Marsh LA, Radovanović S, Vukićević M, Roberts SGE, Veljković NV. IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports. 2018;8(1):10563.
doi:10.1038/s41598-018-28815-x .
Perović, Vladimir R., Šumonja, Neven, Marsh, Lindsey A., Radovanović, Sandro, Vukićević, Milan, Roberts, Stefan G. E., Veljković, Nevena V., "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins" in Scientific Reports, 8, no. 1 (2018):10563,
https://doi.org/10.1038/s41598-018-28815-x . .
4
21
7
16

Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)

Senćanski, Milan; Vrecl, Milka; Veljković, Nevena V.; Glišić, Sanja

(Department of Biology and Ecology : Faculty of Sciences University of Novi Sad, 2018)

TY  - CONF
AU  - Senćanski, Milan
AU  - Vrecl, Milka
AU  - Veljković, Nevena V.
AU  - Glišić, Sanja
PY  - 2018
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11013
AB  - Stabilization of specific G-protein coupled receptor (GPCR) conformation is achieved by ligand binding to orthosteric or allosteric sites on a GPCRs. A crucial unresolved issue in GPCRs activation/signaling is the role of receptor structural conformations in G protein/effector protein selection. One of the possible approaches to get comprehensive depiction of GPCRs activation dynamics are molecular simulations and recently described nanobody-derived intrabodies. Monomeric single-domain antibody (nanobody) from the Camelid family was found to allosterically bind to and stabilizes distinct conformational states of the β2AR. By applying informational spectrum method (ISM), a virtual spectroscopy method for investigation of the protein-protein interactions, we have designed peptide mimetic of the nanobody related to the β2AR (nanobody derived peptide, NDP). Further, interaction between NDP and the ligand-bound β2AR active conformation have been studied by protein-peptide docking, molecular dynamics simulations and metadynamics calculations of free energy binding. Finally, the affinity of selected NDPs towards agonist-activated β2AR was also studied by microscale thermophoresis (MST) and by bioluminescence resonance energy transfer (BRET) based β-arrestin 2 recruitment assay. MST data predicted micromolar range interaction of selected NDPs with the β2AR, while the preliminary β-arrestin 2 recruitment results suggest prospective further modification and optimization of NDPs toward effective modulators of the β2AR.
PB  - Department of Biology and Ecology : Faculty of Sciences University of Novi Sad
C3  - Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22
T1  - Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)
VL  - 40
IS  - 1
SP  - 58
UR  - https://hdl.handle.net/21.15107/rcub_vinar_11013
ER  - 
@conference{
author = "Senćanski, Milan and Vrecl, Milka and Veljković, Nevena V. and Glišić, Sanja",
year = "2018",
abstract = "Stabilization of specific G-protein coupled receptor (GPCR) conformation is achieved by ligand binding to orthosteric or allosteric sites on a GPCRs. A crucial unresolved issue in GPCRs activation/signaling is the role of receptor structural conformations in G protein/effector protein selection. One of the possible approaches to get comprehensive depiction of GPCRs activation dynamics are molecular simulations and recently described nanobody-derived intrabodies. Monomeric single-domain antibody (nanobody) from the Camelid family was found to allosterically bind to and stabilizes distinct conformational states of the β2AR. By applying informational spectrum method (ISM), a virtual spectroscopy method for investigation of the protein-protein interactions, we have designed peptide mimetic of the nanobody related to the β2AR (nanobody derived peptide, NDP). Further, interaction between NDP and the ligand-bound β2AR active conformation have been studied by protein-peptide docking, molecular dynamics simulations and metadynamics calculations of free energy binding. Finally, the affinity of selected NDPs towards agonist-activated β2AR was also studied by microscale thermophoresis (MST) and by bioluminescence resonance energy transfer (BRET) based β-arrestin 2 recruitment assay. MST data predicted micromolar range interaction of selected NDPs with the β2AR, while the preliminary β-arrestin 2 recruitment results suggest prospective further modification and optimization of NDPs toward effective modulators of the β2AR.",
publisher = "Department of Biology and Ecology : Faculty of Sciences University of Novi Sad",
journal = "Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22",
title = "Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)",
volume = "40",
number = "1",
pages = "58",
url = "https://hdl.handle.net/21.15107/rcub_vinar_11013"
}
Senćanski, M., Vrecl, M., Veljković, N. V.,& Glišić, S.. (2018). Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR). in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22
Department of Biology and Ecology : Faculty of Sciences University of Novi Sad., 40(1), 58.
https://hdl.handle.net/21.15107/rcub_vinar_11013
Senćanski M, Vrecl M, Veljković NV, Glišić S. Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR). in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22. 2018;40(1):58.
https://hdl.handle.net/21.15107/rcub_vinar_11013 .
Senćanski, Milan, Vrecl, Milka, Veljković, Nevena V., Glišić, Sanja, "Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)" in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22, 40, no. 1 (2018):58,
https://hdl.handle.net/21.15107/rcub_vinar_11013 .

In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum

Stevanović, Strahinja; Perdih, Andrej; Senćanski, Milan V.; Glišić, Sanja; Duarte, Margarida; Tomas, Ana; Sena, Filipa; Sousa, Filipe; Pereira, Manuela M.; Šolmajer, Tom

(2018)

TY  - JOUR
AU  - Stevanović, Strahinja
AU  - Perdih, Andrej
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
AU  - Duarte, Margarida
AU  - Tomas, Ana
AU  - Sena, Filipa
AU  - Sousa, Filipe
AU  - Pereira, Manuela M.
AU  - Šolmajer, Tom
PY  - 2018
UR  - http://www.mdpi.com/1420-3049/23/4/772
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7774
AB  - There is an urgent need for the discovery of new antileishmanial drugs with a new mechanism of action. Type 2 NADH dehydrogenase from Leishmania infantum (LiNDH2) is an enzyme of the parasite's respiratory system, which catalyzes the electron transfer from NADH to ubiquinone without coupled proton pumping. In previous studies of the related NADH: ubiquinone oxidoreductase crystal structure from Saccharomyces cerevisiae, two ubiquinone-binding sites (UQI and UQII) were identified and shown to play an important role in the NDH-2-catalyzed oxidoreduction reaction. Based on the available structural data, we developed a three-dimensional structural model of LiNDH2 using homology detection methods and performed an in silico virtual screening campaign to search for potential inhibitors targeting the LiNDH2 ubiquinone-binding site 1-UQI. Selected compounds displaying favorable properties in the computational screening experiments were assayed for inhibitory activity in the structurally similar recombinant NDH-2 from S. aureus and leishmanicidal activity was determined in the wild-type axenic amastigotes and promastigotes of L. infantum. The identified compound, a substituted 6-methoxy-quinalidine, showed promising nanomolar leishmanicidal activity on wild-type axenic promastigotes and amastigotes of L. infantum and the potential for further development.
T2  - Molecules
T1  - In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum
VL  - 23
IS  - 4
SP  - 772
DO  - 10.3390/molecules23040772
ER  - 
@article{
author = "Stevanović, Strahinja and Perdih, Andrej and Senćanski, Milan V. and Glišić, Sanja and Duarte, Margarida and Tomas, Ana and Sena, Filipa and Sousa, Filipe and Pereira, Manuela M. and Šolmajer, Tom",
year = "2018",
abstract = "There is an urgent need for the discovery of new antileishmanial drugs with a new mechanism of action. Type 2 NADH dehydrogenase from Leishmania infantum (LiNDH2) is an enzyme of the parasite's respiratory system, which catalyzes the electron transfer from NADH to ubiquinone without coupled proton pumping. In previous studies of the related NADH: ubiquinone oxidoreductase crystal structure from Saccharomyces cerevisiae, two ubiquinone-binding sites (UQI and UQII) were identified and shown to play an important role in the NDH-2-catalyzed oxidoreduction reaction. Based on the available structural data, we developed a three-dimensional structural model of LiNDH2 using homology detection methods and performed an in silico virtual screening campaign to search for potential inhibitors targeting the LiNDH2 ubiquinone-binding site 1-UQI. Selected compounds displaying favorable properties in the computational screening experiments were assayed for inhibitory activity in the structurally similar recombinant NDH-2 from S. aureus and leishmanicidal activity was determined in the wild-type axenic amastigotes and promastigotes of L. infantum. The identified compound, a substituted 6-methoxy-quinalidine, showed promising nanomolar leishmanicidal activity on wild-type axenic promastigotes and amastigotes of L. infantum and the potential for further development.",
journal = "Molecules",
title = "In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum",
volume = "23",
number = "4",
pages = "772",
doi = "10.3390/molecules23040772"
}
Stevanović, S., Perdih, A., Senćanski, M. V., Glišić, S., Duarte, M., Tomas, A., Sena, F., Sousa, F., Pereira, M. M.,& Šolmajer, T.. (2018). In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum. in Molecules, 23(4), 772.
https://doi.org/10.3390/molecules23040772
Stevanović S, Perdih A, Senćanski MV, Glišić S, Duarte M, Tomas A, Sena F, Sousa F, Pereira MM, Šolmajer T. In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum. in Molecules. 2018;23(4):772.
doi:10.3390/molecules23040772 .
Stevanović, Strahinja, Perdih, Andrej, Senćanski, Milan V., Glišić, Sanja, Duarte, Margarida, Tomas, Ana, Sena, Filipa, Sousa, Filipe, Pereira, Manuela M., Šolmajer, Tom, "In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum" in Molecules, 23, no. 4 (2018):772,
https://doi.org/10.3390/molecules23040772 . .
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Annotation Of The Functional Impact Of Coding Genetic Variants

Perović, Vladimir R.; Gemović, Branislava S.; Veljković, Veljko; Glišić, Sanja; Veljković, Nevena V.

(2017)

TY  - CONF
AU  - Perović, Vladimir R.
AU  - Gemović, Branislava S.
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Veljković, Nevena V.
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10770
AB  - Summary. Coding genetic variants can have profound effects on protein function. Computational tools for the prediction of these effects are used to complement and guide experimental biological studies. Phylogenetic analyses that determine the evolutionary relationship among related sequences are commonly used to distinguish between functionally significant and insignificant gene variations. Here, we have reviewed applications of the non-alignment sequence analyses method for phylogenetic analyses, ISTREE. Furthermore, we assessed how an unsupervised ISTREE-d3 method based on the universal d3 measure responds to this task compared to supervised and semi-supervised ISTREE methods that were previously used in two studies. The findings presented here suggest that ISTREE-d3 can efficiently substitute for the corresponding supervised models, given that it is more suitable for automatic applications. In conclusion, the ISTREE-d3 method has a broad biological relevance and represents a promising approach in functional assessment of coding gene variations.
C3  - Biologica Serbica
T1  - Annotation Of The Functional Impact Of Coding Genetic Variants
VL  - 39
IS  - 1
SP  - 74
EP  - 82
DO  - 10.5281/zenodo.826908
ER  - 
@conference{
author = "Perović, Vladimir R. and Gemović, Branislava S. and Veljković, Veljko and Glišić, Sanja and Veljković, Nevena V.",
year = "2017",
abstract = "Summary. Coding genetic variants can have profound effects on protein function. Computational tools for the prediction of these effects are used to complement and guide experimental biological studies. Phylogenetic analyses that determine the evolutionary relationship among related sequences are commonly used to distinguish between functionally significant and insignificant gene variations. Here, we have reviewed applications of the non-alignment sequence analyses method for phylogenetic analyses, ISTREE. Furthermore, we assessed how an unsupervised ISTREE-d3 method based on the universal d3 measure responds to this task compared to supervised and semi-supervised ISTREE methods that were previously used in two studies. The findings presented here suggest that ISTREE-d3 can efficiently substitute for the corresponding supervised models, given that it is more suitable for automatic applications. In conclusion, the ISTREE-d3 method has a broad biological relevance and represents a promising approach in functional assessment of coding gene variations.",
journal = "Biologica Serbica",
title = "Annotation Of The Functional Impact Of Coding Genetic Variants",
volume = "39",
number = "1",
pages = "74-82",
doi = "10.5281/zenodo.826908"
}
Perović, V. R., Gemović, B. S., Veljković, V., Glišić, S.,& Veljković, N. V.. (2017). Annotation Of The Functional Impact Of Coding Genetic Variants. in Biologica Serbica, 39(1), 74-82.
https://doi.org/10.5281/zenodo.826908
Perović VR, Gemović BS, Veljković V, Glišić S, Veljković NV. Annotation Of The Functional Impact Of Coding Genetic Variants. in Biologica Serbica. 2017;39(1):74-82.
doi:10.5281/zenodo.826908 .
Perović, Vladimir R., Gemović, Branislava S., Veljković, Veljko, Glišić, Sanja, Veljković, Nevena V., "Annotation Of The Functional Impact Of Coding Genetic Variants" in Biologica Serbica, 39, no. 1 (2017):74-82,
https://doi.org/10.5281/zenodo.826908 . .

TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation

Perović, Vladimir R.; Šumonja, Neven; Gemović, Branislava S.; Toska, Eneda; Roberts, Stefan G. E.; Veljković, Nevena V.

(2017)

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Gemović, Branislava S.
AU  - Toska, Eneda
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1468
AB  - The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions.
T2  - Bioinformatics
T1  - TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation
VL  - 33
IS  - 2
SP  - 289
EP  - 291
DO  - 10.1093/bioinformatics/btw590
ER  - 
@article{
author = "Perović, Vladimir R. and Šumonja, Neven and Gemović, Branislava S. and Toska, Eneda and Roberts, Stefan G. E. and Veljković, Nevena V.",
year = "2017",
abstract = "The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions.",
journal = "Bioinformatics",
title = "TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation",
volume = "33",
number = "2",
pages = "289-291",
doi = "10.1093/bioinformatics/btw590"
}
Perović, V. R., Šumonja, N., Gemović, B. S., Toska, E., Roberts, S. G. E.,& Veljković, N. V.. (2017). TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation. in Bioinformatics, 33(2), 289-291.
https://doi.org/10.1093/bioinformatics/btw590
Perović VR, Šumonja N, Gemović BS, Toska E, Roberts SGE, Veljković NV. TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation. in Bioinformatics. 2017;33(2):289-291.
doi:10.1093/bioinformatics/btw590 .
Perović, Vladimir R., Šumonja, Neven, Gemović, Branislava S., Toska, Eneda, Roberts, Stefan G. E., Veljković, Nevena V., "TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation" in Bioinformatics, 33, no. 2 (2017):289-291,
https://doi.org/10.1093/bioinformatics/btw590 . .
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Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus

Bojić, Tijana; Perović, Vladimir R.; Senćanski, Milan V.; Glišić, Sanja

(2017)

TY  - JOUR
AU  - Bojić, Tijana
AU  - Perović, Vladimir R.
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1823
AB  - Chronic tinnitus is characterized by neuroplastic changes of the auditory cortex. A promising method for therapy of chronic tinnitus is vagus nerve stimulation (VNS) combined with auditory stimulation. The principle of VNS is reversal of pathological neuroplastic changes of the auditory cortex toward physiological neural activity and synchronicity. The VNS mechanism of action in chronic tinnitus patients is prevailingly through the muscarinic neuromodulation of the auditory cortex by the activation of nc. basalis Meynerti. The aim of this study is to propose potential pharmaceutics which may improve the neuromodulatory effects of VNS. The working hypothesis is that M1 receptors have a dominant role in the neural plasticity of the auditory cortex. We propose that allosteric agonists of the muscarinic receptor type 1 (M1) receptor could improve specificity and selectivity of the neuromodulatory effect of VNS on the auditory cortex of chronic tinnitus patients even in the circumstances of lower acetylcholine brain concentration. This intervention would also reinforce the re-learning process of tinnitus (sub) networks by acting on cholinergic memory and learning mechanisms. We performed in silico screening of drug space using the EIIP/AQVN filter and selected 50 drugs as candidates for allosteric modulators of muscarinic receptors. Further filtering of these compounds by means of 3D QSAR and docking revealed 3 approved drugs-bromazepam, estazolam and flumazenil as the most promising candidates for combined chronic tinnitus therapy. These drugs should be further evaluated by biological tests and clinical trials.
T2  - Frontiers in Neuroscience
T1  - Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus
VL  - 11
SP  - 636
DO  - 10.3389/fnins.2017.00636
ER  - 
@article{
author = "Bojić, Tijana and Perović, Vladimir R. and Senćanski, Milan V. and Glišić, Sanja",
year = "2017",
abstract = "Chronic tinnitus is characterized by neuroplastic changes of the auditory cortex. A promising method for therapy of chronic tinnitus is vagus nerve stimulation (VNS) combined with auditory stimulation. The principle of VNS is reversal of pathological neuroplastic changes of the auditory cortex toward physiological neural activity and synchronicity. The VNS mechanism of action in chronic tinnitus patients is prevailingly through the muscarinic neuromodulation of the auditory cortex by the activation of nc. basalis Meynerti. The aim of this study is to propose potential pharmaceutics which may improve the neuromodulatory effects of VNS. The working hypothesis is that M1 receptors have a dominant role in the neural plasticity of the auditory cortex. We propose that allosteric agonists of the muscarinic receptor type 1 (M1) receptor could improve specificity and selectivity of the neuromodulatory effect of VNS on the auditory cortex of chronic tinnitus patients even in the circumstances of lower acetylcholine brain concentration. This intervention would also reinforce the re-learning process of tinnitus (sub) networks by acting on cholinergic memory and learning mechanisms. We performed in silico screening of drug space using the EIIP/AQVN filter and selected 50 drugs as candidates for allosteric modulators of muscarinic receptors. Further filtering of these compounds by means of 3D QSAR and docking revealed 3 approved drugs-bromazepam, estazolam and flumazenil as the most promising candidates for combined chronic tinnitus therapy. These drugs should be further evaluated by biological tests and clinical trials.",
journal = "Frontiers in Neuroscience",
title = "Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus",
volume = "11",
pages = "636",
doi = "10.3389/fnins.2017.00636"
}
Bojić, T., Perović, V. R., Senćanski, M. V.,& Glišić, S.. (2017). Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus. in Frontiers in Neuroscience, 11, 636.
https://doi.org/10.3389/fnins.2017.00636
Bojić T, Perović VR, Senćanski MV, Glišić S. Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus. in Frontiers in Neuroscience. 2017;11:636.
doi:10.3389/fnins.2017.00636 .
Bojić, Tijana, Perović, Vladimir R., Senćanski, Milan V., Glišić, Sanja, "Identification of Candidate Allosteric Modulators of the M1 Muscarinic Acetylcholine Receptor Which May Improve Vagus Nerve Stimulation in ChronicTinnitus" in Frontiers in Neuroscience, 11 (2017):636,
https://doi.org/10.3389/fnins.2017.00636 . .
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