TY  - JOUR
AU  - Dopsaj, Milivoj
AU  - Tan, Wilhelmina
AU  - Perović, Vladimir
AU  - Stajić, Zoran
AU  - Milosavljević, Nemanja
AU  - Paessler, Slobodan
AU  - Makishima, Tomoko
PY  - 2024
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/12994
AB  - Virtual reality (VR) is a computer-created 3D environment with a focus on realistic scenes and pictures created for entertainment, medical and/or educational and training purposes. One of the major side effects of VR immersion reported in the scientific literature, media and social media is Visually Induced Motion Sickness (VIMS), with clinical symptoms such as disorientation, nausea, and oculomotor discomfort. VIMS is mostly caused by the discrepancy between the visual and vestibular systems and can lead to dizziness, nausea, and disorientation. In this study, we present one potential novel solution to combat motion sickness in VR, showcasing a significant reduction of nausea in VR users employing the META Quest 2 headsets in conjunction with a whole-body controller. Using a neurodigital approach, we facilitate a more immersive and comfortable VR experience. Our findings indicate a marked reduction in VR-induced nausea, paving the way to promote VR technology for broader applications across various fields.
T2  - Neuroscience Letters
T1  - Novel neurodigital interface reduces motion sickness in virtual reality
VL  - 825
SP  - 137692
DO  - 10.1016/j.neulet.2024.137692
ER  - 

@article{
author = "Dopsaj, Milivoj and Tan, Wilhelmina and Perović, Vladimir and Stajić, Zoran and Milosavljević, Nemanja and Paessler, Slobodan and Makishima, Tomoko",
year = "2024",
abstract = "Virtual reality (VR) is a computer-created 3D environment with a focus on realistic scenes and pictures created for entertainment, medical and/or educational and training purposes. One of the major side effects of VR immersion reported in the scientific literature, media and social media is Visually Induced Motion Sickness (VIMS), with clinical symptoms such as disorientation, nausea, and oculomotor discomfort. VIMS is mostly caused by the discrepancy between the visual and vestibular systems and can lead to dizziness, nausea, and disorientation. In this study, we present one potential novel solution to combat motion sickness in VR, showcasing a significant reduction of nausea in VR users employing the META Quest 2 headsets in conjunction with a whole-body controller. Using a neurodigital approach, we facilitate a more immersive and comfortable VR experience. Our findings indicate a marked reduction in VR-induced nausea, paving the way to promote VR technology for broader applications across various fields.",
journal = "Neuroscience Letters",
title = "Novel neurodigital interface reduces motion sickness in virtual reality",
volume = "825",
pages = "137692",
doi = "10.1016/j.neulet.2024.137692"
}

Dopsaj, M., Tan, W., Perović, V., Stajić, Z., Milosavljević, N., Paessler, S.,& Makishima, T.. (2024). Novel neurodigital interface reduces motion sickness in virtual reality. in Neuroscience Letters, 825, 137692.
https://doi.org/10.1016/j.neulet.2024.137692

Dopsaj M, Tan W, Perović V, Stajić Z, Milosavljević N, Paessler S, Makishima T. Novel neurodigital interface reduces motion sickness in virtual reality. in Neuroscience Letters. 2024;825:137692.
doi:10.1016/j.neulet.2024.137692 .

Dopsaj, Milivoj, Tan, Wilhelmina, Perović, Vladimir, Stajić, Zoran, Milosavljević, Nemanja, Paessler, Slobodan, Makishima, Tomoko, "Novel neurodigital interface reduces motion sickness in virtual reality" in Neuroscience Letters, 825 (2024):137692,
https://doi.org/10.1016/j.neulet.2024.137692 . .

TY  - JOUR
AU  - Protić, Sara
AU  - Kaličanin, Nevena
AU  - Senćanski, Milan
AU  - Prodanović, Olivera
AU  - Milićević, Jelena S.
AU  - Perović, Vladimir
AU  - Paessler, Slobodan
AU  - Prodanović, Radivoje
AU  - Glišić, Sanja
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10644
AB  - Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrentpandemic. Since developing a new treatment takes a significant amount of time, drug repurposingcan be an effective option for achieving a rapid response. This study used a combined in silico virtualscreening protocol for candidate SARS-CoV-2 PLpro inhibitors. The Drugbank database was searchedfirst, using the Informational Spectrum Method for Small Molecules, followed by molecular docking.Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PLpro.After the expression and purification of PLpro, gramicidin D was screened for protease inhibitionin vitro and was found to be active against PLpro. The current study’s findings are significantbecause it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorablesafety profile.
T2  - International Journal of Molecular Sciences
T1  - In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D
VL  - 24
IS  - 3
SP  - 1955
DO  - 10.3390/ijms24031955
ER  - 

@article{
author = "Protić, Sara and Kaličanin, Nevena and Senćanski, Milan and Prodanović, Olivera and Milićević, Jelena S. and Perović, Vladimir and Paessler, Slobodan and Prodanović, Radivoje and Glišić, Sanja",
year = "2023",
abstract = "Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrentpandemic. Since developing a new treatment takes a significant amount of time, drug repurposingcan be an effective option for achieving a rapid response. This study used a combined in silico virtualscreening protocol for candidate SARS-CoV-2 PLpro inhibitors. The Drugbank database was searchedfirst, using the Informational Spectrum Method for Small Molecules, followed by molecular docking.Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PLpro.After the expression and purification of PLpro, gramicidin D was screened for protease inhibitionin vitro and was found to be active against PLpro. The current study’s findings are significantbecause it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorablesafety profile.",
journal = "International Journal of Molecular Sciences",
title = "In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D",
volume = "24",
number = "3",
pages = "1955",
doi = "10.3390/ijms24031955"
}

Protić, S., Kaličanin, N., Senćanski, M., Prodanović, O., Milićević, J. S., Perović, V., Paessler, S., Prodanović, R.,& Glišić, S.. (2023). In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D. in International Journal of Molecular Sciences, 24(3), 1955.
https://doi.org/10.3390/ijms24031955

Protić S, Kaličanin N, Senćanski M, Prodanović O, Milićević JS, Perović V, Paessler S, Prodanović R, Glišić S. In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D. in International Journal of Molecular Sciences. 2023;24(3):1955.
doi:10.3390/ijms24031955 .

Protić, Sara, Kaličanin, Nevena, Senćanski, Milan, Prodanović, Olivera, Milićević, Jelena S., Perović, Vladimir, Paessler, Slobodan, Prodanović, Radivoje, Glišić, Sanja, "In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D" in International Journal of Molecular Sciences, 24, no. 3 (2023):1955,
https://doi.org/10.3390/ijms24031955 . .

TY  - JOUR
AU  - Bojić, Tijana
AU  - Senćanski, Milan V.
AU  - Perović, Vladimir R.
AU  - Milićević, Jelena S.
AU  - Glišić, Sanja
PY  - 2022
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10252
AB  - Alzheimer’s disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC—natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.
T2  - Molecules
T1  - In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease
VL  - 27
IS  - 9
SP  - 2626
DO  - 10.3390/molecules27092626
ER  - 

@article{
author = "Bojić, Tijana and Senćanski, Milan V. and Perović, Vladimir R. and Milićević, Jelena S. and Glišić, Sanja",
year = "2022",
abstract = "Alzheimer’s disease (AD), a devastating neurodegenerative disease, is the focus of pharmacological research. One of the targets that attract the most attention for the potential therapy of AD is the serotonin 5HT6 receptor, which is the receptor situated exclusively in CNS on glutamatergic and GABAergic neurons. The neurochemical impact of this receptor supports the hypothesis about its role in cognitive, learning, and memory systems, which are of critical importance for AD. Natural products are a promising source of novel bioactive compounds with potential therapeutic potential as a 5HT6 receptor antagonist in the treatment of AD dementia. The ZINC—natural product database was in silico screened in order to find the candidate antagonists of 5-HT6 receptor against AD. A virtual screening protocol that includes both short-and long-range interactions between interacting molecules was employed. First, the EIIP/AQVN filter was applied for in silico screening of the ZINC database followed by 3D QSAR and molecular docking. Ten best candidate compounds were selected from the ZINC Natural Product database as potential 5HT6 Receptor antagonists and were proposed for further evaluation. The best candidate was evaluated by molecular dynamics simulations and free energy calculations.",
journal = "Molecules",
title = "In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease",
volume = "27",
number = "9",
pages = "2626",
doi = "10.3390/molecules27092626"
}

Bojić, T., Senćanski, M. V., Perović, V. R., Milićević, J. S.,& Glišić, S.. (2022). In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease. in Molecules, 27(9), 2626.
https://doi.org/10.3390/molecules27092626

Bojić T, Senćanski MV, Perović VR, Milićević JS, Glišić S. In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease. in Molecules. 2022;27(9):2626.
doi:10.3390/molecules27092626 .

Bojić, Tijana, Senćanski, Milan V., Perović, Vladimir R., Milićević, Jelena S., Glišić, Sanja, "In Silico Screening of Natural Compounds for Candidates 5HT6 Receptor Antagonists against Alzheimer’s Disease" in Molecules, 27, no. 9 (2022):2626,
https://doi.org/10.3390/molecules27092626 . .

TY  - JOUR
AU  - Senćanski, Milan
AU  - Perović, Vladimir
AU  - Milićević, Jelena S.
AU  - Todorović, Tamara
AU  - Prodanović, Radivoje
AU  - Veljković, Veljko
AU  - Paessler, Slobodan
AU  - Glišić, Sanja
PY  - 2022
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10425
AB  - In the currentpandemic,findingan effectivedrugto preventortreatthe infectionis the highestpriority.A rapidand safeapproachto counteractCOVID-19is in silicodrugrepurposing.The SARS-CoV-2PLpropromotesviral replicationand modu-latesthe hostimmunesystem,resultingin inhibitionof thehostantiviralinnateimmuneresponse,and thereforeis anattractivedrugtarget.In this study,we useda combinedinsilicovirtualscreeningfor candidatesfor SARS-CoV-2PLproproteaseinhibitors.We usedthe Informationalspectrummethodappliedfor SmallMoleculesfor searchingthe Drugbankdatabasefollowedby moleculardocking.Afterin silicoscreen-ing of drugspace,we identified44 drugsas potentialSARS-CoV-2PLproinhibitorsthat we proposefor furtherexperimentaltesting.
T2  - ChemistryOpen
T1  - Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach
VL  - 11
IS  - 2
SP  - e202100248
DO  - 10.1002/open.202100248
ER  - 

@article{
author = "Senćanski, Milan and Perović, Vladimir and Milićević, Jelena S. and Todorović, Tamara and Prodanović, Radivoje and Veljković, Veljko and Paessler, Slobodan and Glišić, Sanja",
year = "2022",
abstract = "In the currentpandemic,findingan effectivedrugto preventortreatthe infectionis the highestpriority.A rapidand safeapproachto counteractCOVID-19is in silicodrugrepurposing.The SARS-CoV-2PLpropromotesviral replicationand modu-latesthe hostimmunesystem,resultingin inhibitionof thehostantiviralinnateimmuneresponse,and thereforeis anattractivedrugtarget.In this study,we useda combinedinsilicovirtualscreeningfor candidatesfor SARS-CoV-2PLproproteaseinhibitors.We usedthe Informationalspectrummethodappliedfor SmallMoleculesfor searchingthe Drugbankdatabasefollowedby moleculardocking.Afterin silicoscreen-ing of drugspace,we identified44 drugsas potentialSARS-CoV-2PLproinhibitorsthat we proposefor furtherexperimentaltesting.",
journal = "ChemistryOpen",
title = "Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach",
volume = "11",
number = "2",
pages = "e202100248",
doi = "10.1002/open.202100248"
}

Senćanski, M., Perović, V., Milićević, J. S., Todorović, T., Prodanović, R., Veljković, V., Paessler, S.,& Glišić, S.. (2022). Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach. in ChemistryOpen, 11(2), e202100248.
https://doi.org/10.1002/open.202100248

Senćanski M, Perović V, Milićević JS, Todorović T, Prodanović R, Veljković V, Paessler S, Glišić S. Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach. in ChemistryOpen. 2022;11(2):e202100248.
doi:10.1002/open.202100248 .

Senćanski, Milan, Perović, Vladimir, Milićević, Jelena S., Todorović, Tamara, Prodanović, Radivoje, Veljković, Veljko, Paessler, Slobodan, Glišić, Sanja, "Identification of SARS-CoV-2 Papain-like Protease (PLpro) Inhibitors Using Combined Computational Approach" in ChemistryOpen, 11, no. 2 (2022):e202100248,
https://doi.org/10.1002/open.202100248 . .

TY  - JOUR
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Perović, Vladimir R.
AU  - Veljković, Milena
AU  - Paessler, Slobodan
PY  - 2022
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10295
AB  - A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become the leading threat to global health. An effective antiviral could not only help those still vulnerable to the virus but could be a critical treatment if a virus emerges toward evading coronavirus disease 2019 (COVID-19) vaccines. Despite the significant efforts to test already-approved drugs for their potential to kill the virus, researchers found very few actually worked. Methods: The present report uses the electronic molecular descriptors, the quasi-valence number (AQVN), and the electron-ion interaction potential (EIIP), for the analysis of natural compounds with proven therapeutic activity against the COVID-19. Results: Based on the analysis of the electronic properties of natural compounds which are effective against SARS-CoV-2 virus the simple theoretical criterion for the selection of candidate compounds for the treatment of COVID-19 is proposed. Conclusions: The proposed theoretical criterion can be used for the identification and optimization of new lead compounds for the treatment of the COVID-19 disease and for the selection of the food and food supplements which could have a beneficial effect on COVID-19 patients.
T2  - Frontiers in Bioscience - Landmark
T1  - Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity
VL  - 27
IS  - 5
SP  - 152
DO  - 10.31083/j.fbl2705152
ER  - 

@article{
author = "Veljković, Veljko and Glišić, Sanja and Perović, Vladimir R. and Veljković, Milena and Paessler, Slobodan",
year = "2022",
abstract = "A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become the leading threat to global health. An effective antiviral could not only help those still vulnerable to the virus but could be a critical treatment if a virus emerges toward evading coronavirus disease 2019 (COVID-19) vaccines. Despite the significant efforts to test already-approved drugs for their potential to kill the virus, researchers found very few actually worked. Methods: The present report uses the electronic molecular descriptors, the quasi-valence number (AQVN), and the electron-ion interaction potential (EIIP), for the analysis of natural compounds with proven therapeutic activity against the COVID-19. Results: Based on the analysis of the electronic properties of natural compounds which are effective against SARS-CoV-2 virus the simple theoretical criterion for the selection of candidate compounds for the treatment of COVID-19 is proposed. Conclusions: The proposed theoretical criterion can be used for the identification and optimization of new lead compounds for the treatment of the COVID-19 disease and for the selection of the food and food supplements which could have a beneficial effect on COVID-19 patients.",
journal = "Frontiers in Bioscience - Landmark",
title = "Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity",
volume = "27",
number = "5",
pages = "152",
doi = "10.31083/j.fbl2705152"
}

Veljković, V., Glišić, S., Perović, V. R., Veljković, M.,& Paessler, S.. (2022). Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity. in Frontiers in Bioscience - Landmark, 27(5), 152.
https://doi.org/10.31083/j.fbl2705152

Veljković V, Glišić S, Perović VR, Veljković M, Paessler S. Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity. in Frontiers in Bioscience - Landmark. 2022;27(5):152.
doi:10.31083/j.fbl2705152 .

Veljković, Veljko, Glišić, Sanja, Perović, Vladimir R., Veljković, Milena, Paessler, Slobodan, "Simple Theoretical Criterion for Selection of Natural Compounds with Anti-COVID-19 Activity" in Frontiers in Bioscience - Landmark, 27, no. 5 (2022):152,
https://doi.org/10.31083/j.fbl2705152 . .

TY  - JOUR
AU  - Drljača, Tamara
AU  - Zukić, Branka
AU  - Kovačević, Vladimir
AU  - Gemović, Branislava S.
AU  - Karan-Đurašević, Teodora
AU  - Perović, Vladimir R.
AU  - Lazarević, Mladen
AU  - Pavlović, Sonja
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10769
AB  - The complete understanding of the genomic contribution to complex traits, diseases, and response to treatments, as well as genomic medicine application to the well-being of all humans will be achieved through the global variome that encompasses fine-scale genetic diversity. Despite significant efforts in recent years, uneven representation still characterizes genomic resources and among the underrepresented European populations are the Western Balkans including the Serbian population. Our research addresses this gap and presents the first ever targeted sequencing dataset of variants in clinically relevant genes. By measuring population differentiation and applying the Principal Component and Admixture analysis we demonstrated that the Serbian population differs little from other European populations, yet we identified several novel and more frequent variants that appear as its unique genetic determinants. We explored thoroughly the functional impact of frequent variants and its correlation with the health burden of the population of Serbia based on a sample of 144 individuals. Our variants catalogue improves the understanding of genetics of modern Serbia, contributes to research on ancestry, and aids in improvements of well-being and health equity. In addition, this resource may also be applicable in neighboring regions and valuable in worldwide functional analyses of genetic variants in individuals of European descent.
T2  - Scientific Reports
T1  - The first insight into the genetic structure of the population of modern Serbia
VL  - 11
IS  - 1
SP  - 13995
DO  - 10.1038/s41598-021-93129-4
ER  - 

@article{
author = "Drljača, Tamara and Zukić, Branka and Kovačević, Vladimir and Gemović, Branislava S. and Karan-Đurašević, Teodora and Perović, Vladimir R. and Lazarević, Mladen and Pavlović, Sonja and Veljković, Nevena V.",
year = "2021",
abstract = "The complete understanding of the genomic contribution to complex traits, diseases, and response to treatments, as well as genomic medicine application to the well-being of all humans will be achieved through the global variome that encompasses fine-scale genetic diversity. Despite significant efforts in recent years, uneven representation still characterizes genomic resources and among the underrepresented European populations are the Western Balkans including the Serbian population. Our research addresses this gap and presents the first ever targeted sequencing dataset of variants in clinically relevant genes. By measuring population differentiation and applying the Principal Component and Admixture analysis we demonstrated that the Serbian population differs little from other European populations, yet we identified several novel and more frequent variants that appear as its unique genetic determinants. We explored thoroughly the functional impact of frequent variants and its correlation with the health burden of the population of Serbia based on a sample of 144 individuals. Our variants catalogue improves the understanding of genetics of modern Serbia, contributes to research on ancestry, and aids in improvements of well-being and health equity. In addition, this resource may also be applicable in neighboring regions and valuable in worldwide functional analyses of genetic variants in individuals of European descent.",
journal = "Scientific Reports",
title = "The first insight into the genetic structure of the population of modern Serbia",
volume = "11",
number = "1",
pages = "13995",
doi = "10.1038/s41598-021-93129-4"
}

Drljača, T., Zukić, B., Kovačević, V., Gemović, B. S., Karan-Đurašević, T., Perović, V. R., Lazarević, M., Pavlović, S.,& Veljković, N. V.. (2021). The first insight into the genetic structure of the population of modern Serbia. in Scientific Reports, 11(1), 13995.
https://doi.org/10.1038/s41598-021-93129-4

Drljača T, Zukić B, Kovačević V, Gemović BS, Karan-Đurašević T, Perović VR, Lazarević M, Pavlović S, Veljković NV. The first insight into the genetic structure of the population of modern Serbia. in Scientific Reports. 2021;11(1):13995.
doi:10.1038/s41598-021-93129-4 .

Drljača, Tamara, Zukić, Branka, Kovačević, Vladimir, Gemović, Branislava S., Karan-Đurašević, Teodora, Perović, Vladimir R., Lazarević, Mladen, Pavlović, Sonja, Veljković, Nevena V., "The first insight into the genetic structure of the population of modern Serbia" in Scientific Reports, 11, no. 1 (2021):13995,
https://doi.org/10.1038/s41598-021-93129-4 . .

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 . .

TY  - CONF
AU  - Perović, Vladimir
AU  - Gemović, Branislava S.
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11014
AB  - Progress in a wide range of fields ranging from population genetics to precision medicine may be attributed to availability of big biological data. Alignment-free sequence comparison is the methodology of choice in data-intensive applications given that it is significantly faster and requires less resources compared to traditional sequence comparison based on pairwise or multiple sequence alignment. The symbiosis of alignment-free methods with machine learning is a paradigm of new age in bioinformatics, as it ensures the much needed boost to quicken the complex predictions on large datasets, particularly of molecules with low sequence identity. In this talk, I will present two stories in which I will describe approaches to predict functional consequences of gene variants and imperfect tandem repeats in protein sequences.
PB  - Department of Biology and Ecology : Faculty of Sciences University of Novi Sad
C3  - Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25
T1  - New age for alignment-free methods for sequence analyses
SP  - 49
UR  - https://hdl.handle.net/21.15107/rcub_vinar_11014
ER  - 

@conference{
author = "Perović, Vladimir and Gemović, Branislava S. and Veljković, Nevena V.",
year = "2021",
abstract = "Progress in a wide range of fields ranging from population genetics to precision medicine may be attributed to availability of big biological data. Alignment-free sequence comparison is the methodology of choice in data-intensive applications given that it is significantly faster and requires less resources compared to traditional sequence comparison based on pairwise or multiple sequence alignment. The symbiosis of alignment-free methods with machine learning is a paradigm of new age in bioinformatics, as it ensures the much needed boost to quicken the complex predictions on large datasets, particularly of molecules with low sequence identity. In this talk, I will present two stories in which I will describe approaches to predict functional consequences of gene variants and imperfect tandem repeats in protein sequences.",
publisher = "Department of Biology and Ecology : Faculty of Sciences University of Novi Sad",
journal = "Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25",
title = "New age for alignment-free methods for sequence analyses",
pages = "49",
url = "https://hdl.handle.net/21.15107/rcub_vinar_11014"
}

Perović, V., Gemović, B. S.,& Veljković, N. V.. (2021). New age for alignment-free methods for sequence analyses. in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25
Department of Biology and Ecology : Faculty of Sciences University of Novi Sad., 49.
https://hdl.handle.net/21.15107/rcub_vinar_11014

Perović V, Gemović BS, Veljković NV. New age for alignment-free methods for sequence analyses. in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25. 2021;:49.
https://hdl.handle.net/21.15107/rcub_vinar_11014 .

Perović, Vladimir, Gemović, Branislava S., Veljković, Nevena V., "New age for alignment-free methods for sequence analyses" in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25 (2021):49,
https://hdl.handle.net/21.15107/rcub_vinar_11014 .

TY  - CONF
AU  - Senćanski, Milan
AU  - Milićević, Jelena S.
AU  - Perović, Vladimir
AU  - Glišić, Sanja
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11016
AB  - The SARS-CoV-2 outbreak that is spreading rapidly around the world requires urgently effective treatments. Therefore, in silico drug repurposing represents a powerful strategy to enable the acceleration of the identification of drug candidates with already known safety profiles. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. This study used the virtual screening protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. The Informational spectrum method developed for small molecules was first applied for searching the Drugbank database of antiparasitic agents and further followed by molecular docking. After in silico screening of drug space, we propose several drugs as potential SARS-CoV-2 main protease inhibitors for further experimental testing.
PB  - Department of Biology and Ecology : Faculty of Sciences University of Novi Sad
C3  - Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25
T1  - Repurposing of antiparasitic drugs for Candidate SARS-CoV-2 Main Protease Inhibitors by combined in silico Method
VL  - 43
IS  - 1
SP  - 111
UR  - https://hdl.handle.net/21.15107/rcub_vinar_11016
ER  - 

@conference{
author = "Senćanski, Milan and Milićević, Jelena S. and Perović, Vladimir and Glišić, Sanja",
year = "2021",
abstract = "The SARS-CoV-2 outbreak that is spreading rapidly around the world requires urgently effective treatments. Therefore, in silico drug repurposing represents a powerful strategy to enable the acceleration of the identification of drug candidates with already known safety profiles. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. This study used the virtual screening protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. The Informational spectrum method developed for small molecules was first applied for searching the Drugbank database of antiparasitic agents and further followed by molecular docking. After in silico screening of drug space, we propose several drugs as potential SARS-CoV-2 main protease inhibitors for further experimental testing.",
publisher = "Department of Biology and Ecology : Faculty of Sciences University of Novi Sad",
journal = "Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25",
title = "Repurposing of antiparasitic drugs for Candidate SARS-CoV-2 Main Protease Inhibitors by combined in silico Method",
volume = "43",
number = "1",
pages = "111",
url = "https://hdl.handle.net/21.15107/rcub_vinar_11016"
}

Senćanski, M., Milićević, J. S., Perović, V.,& Glišić, S.. (2021). Repurposing of antiparasitic drugs for Candidate SARS-CoV-2 Main Protease Inhibitors by combined in silico Method. in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25
Department of Biology and Ecology : Faculty of Sciences University of Novi Sad., 43(1), 111.
https://hdl.handle.net/21.15107/rcub_vinar_11016

Senćanski M, Milićević JS, Perović V, Glišić S. Repurposing of antiparasitic drugs for Candidate SARS-CoV-2 Main Protease Inhibitors by combined in silico Method. in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25. 2021;43(1):111.
https://hdl.handle.net/21.15107/rcub_vinar_11016 .

Senćanski, Milan, Milićević, Jelena S., Perović, Vladimir, Glišić, Sanja, "Repurposing of antiparasitic drugs for Candidate SARS-CoV-2 Main Protease Inhibitors by combined in silico Method" in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2021 : program and the book of abstracts; June 21-25, 43, no. 1 (2021):111,
https://hdl.handle.net/21.15107/rcub_vinar_11016 .

TY  - JOUR
AU  - Senćanski, Milan V.
AU  - Perović, Vladimir R.
AU  - Pajović, Snežana B.
AU  - Adžić, Miroslav
AU  - Paessler, Slobodan
AU  - Glišić, Sanja
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9611
AB  - The SARS-CoV-2 outbreak caused an unprecedented global public health threat, having a high transmission rate with currently no drugs or vaccines approved. An alternative powerful additional approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. In this study, we used the virtual screening protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. First, the Informational spectrum method applied for small molecules was used for searching the Drugbank database and further followed by molecular docking. After in silico screening of drug space, we identified 57 drugs as potential SARS-CoV-2 main protease inhibitors that we propose for further experimental testing. © 2020 by the authors.
T2  - Molecules
T1  - Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method
VL  - 25
IS  - 17
DO  - 10.3390/molecules25173830
ER  - 

@article{
author = "Senćanski, Milan V. and Perović, Vladimir R. and Pajović, Snežana B. and Adžić, Miroslav and Paessler, Slobodan and Glišić, Sanja",
year = "2020",
abstract = "The SARS-CoV-2 outbreak caused an unprecedented global public health threat, having a high transmission rate with currently no drugs or vaccines approved. An alternative powerful additional approach to counteract COVID-19 is in silico drug repurposing. The SARS-CoV-2 main protease is essential for viral replication and an attractive drug target. In this study, we used the virtual screening protocol with both long-range and short-range interactions to select candidate SARS-CoV-2 main protease inhibitors. First, the Informational spectrum method applied for small molecules was used for searching the Drugbank database and further followed by molecular docking. After in silico screening of drug space, we identified 57 drugs as potential SARS-CoV-2 main protease inhibitors that we propose for further experimental testing. © 2020 by the authors.",
journal = "Molecules",
title = "Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method",
volume = "25",
number = "17",
doi = "10.3390/molecules25173830"
}

Senćanski, M. V., Perović, V. R., Pajović, S. B., Adžić, M., Paessler, S.,& Glišić, S.. (2020). Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method. in Molecules, 25(17).
https://doi.org/10.3390/molecules25173830

Senćanski MV, Perović VR, Pajović SB, Adžić M, Paessler S, Glišić S. Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method. in Molecules. 2020;25(17).
doi:10.3390/molecules25173830 .

Senćanski, Milan V., Perović, Vladimir R., Pajović, Snežana B., Adžić, Miroslav, Paessler, Slobodan, Glišić, Sanja, "Drug Repurposing for Candidate SARS-CoV-2 Main Protease Inhibitors by a Novel in Silico Method" in Molecules, 25, no. 17 (2020),
https://doi.org/10.3390/molecules25173830 . .

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 . .

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 . .

TY  - JOUR
AU  - Glišić, Sanja
AU  - Perović, Vladimir R.
AU  - Senćanski, Milan V.
AU  - Paessler, Slobodan
AU  - Veljković, Veljko
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9723
AB  - The Bacillus Calmette–Guerin vaccine is still widely used in the developing world. The vaccination prevents infant death not only from tuberculosis but also from unrelated infectious agents, especially respiratory tract infections and neonatal sepsis. It is proposed that these off-target protective effects of the BCG vaccine are mediated by the general long-term boosting of innate immune mechanisms, also termed “trained innate immunity”. Recent studies indicate that both COVID-19 incidence and total deaths are strongly associated with the presence or absence of national mandatory BCG vaccination programs and encourage the initiation of several clinical studies with the expectation that revaccination with BCG could reduce the incidence and severity of COVID-19. Here, presented results from the bioinformatics analysis of the Mycobacterium bovis (strain BCG/Pasteur 1173P2) proteome suggests four immunodominant antigens that could induce an immune response against SARS-CoV-2.
T2  - Journal of Proteome Research
T2  - Journal of Proteome ResearchJ. Proteome Res.
T1  - Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2
VL  - 19
IS  - 11
SP  - 4649
EP  - 4654
DO  - 10.1021/acs.jproteome.0c00410
ER  - 

@article{
author = "Glišić, Sanja and Perović, Vladimir R. and Senćanski, Milan V. and Paessler, Slobodan and Veljković, Veljko",
year = "2020",
abstract = "The Bacillus Calmette–Guerin vaccine is still widely used in the developing world. The vaccination prevents infant death not only from tuberculosis but also from unrelated infectious agents, especially respiratory tract infections and neonatal sepsis. It is proposed that these off-target protective effects of the BCG vaccine are mediated by the general long-term boosting of innate immune mechanisms, also termed “trained innate immunity”. Recent studies indicate that both COVID-19 incidence and total deaths are strongly associated with the presence or absence of national mandatory BCG vaccination programs and encourage the initiation of several clinical studies with the expectation that revaccination with BCG could reduce the incidence and severity of COVID-19. Here, presented results from the bioinformatics analysis of the Mycobacterium bovis (strain BCG/Pasteur 1173P2) proteome suggests four immunodominant antigens that could induce an immune response against SARS-CoV-2.",
journal = "Journal of Proteome Research, Journal of Proteome ResearchJ. Proteome Res.",
title = "Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2",
volume = "19",
number = "11",
pages = "4649-4654",
doi = "10.1021/acs.jproteome.0c00410"
}

Glišić, S., Perović, V. R., Senćanski, M. V., Paessler, S.,& Veljković, V.. (2020). Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2. in Journal of Proteome Research, 19(11), 4649-4654.
https://doi.org/10.1021/acs.jproteome.0c00410

Glišić S, Perović VR, Senćanski MV, Paessler S, Veljković V. Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2. in Journal of Proteome Research. 2020;19(11):4649-4654.
doi:10.1021/acs.jproteome.0c00410 .

Glišić, Sanja, Perović, Vladimir R., Senćanski, Milan V., Paessler, Slobodan, Veljković, Veljko, "Biological Rationale for the Repurposing of BCG Vaccine against SARS-CoV-2" in Journal of Proteome Research, 19, no. 11 (2020):4649-4654,
https://doi.org/10.1021/acs.jproteome.0c00410 . .

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 . .

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 . .

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 . .

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 . .

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 .

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 . .

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 . .

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 . .

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 . .

TY  - JOUR
AU  - Srdić-Rajić, Tatjana
AU  - Nikolić, Katarina M.
AU  - Čavić, Milena R.
AU  - Đokić, Ivana
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/884
AB  - Imidazoline I1 receptor signaling is associated with pathways that regulate cell viability leading to varied cell-type specific phenotypes. We demonstrated that the antihypertensive drug rilmenidine, a selective imidazoline I1 receptor agonist, modulates proliferation and stimulates the proapoptotic protein Bax thus inducing the perturbation of the mitochondrial pathway and apoptosis in human leukemic K562 cells. Rilmenidine acts through a mechanism which involves deactivation of Ras/MAP kinases ERK, p38 and JNK. Moreover, rilmenidine renders K562 cells, which are particularly resistant to chemotherapeutic agents, susceptible to the DNA damaging drug doxorubicin. The rilmenidine co-treatment with doxorubicin reverses G2/M arrest and triggers apoptotic response to DNA damage. Our data offer new insights into the pathways associated with imidazoline I1 receptor activation in K562 cells suggesting rilmenidine as a valuable tool to deepen our understanding of imidazoline I1 receptor signaling in hematologic malignancies and to search for medicinally active agents. (C) 2015 Elsevier B.V. All rights reserved.
PB  - Elsevier
T2  - European Journal of Pharmaceutical Sciences
T1  - Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells
VL  - 81
SP  - 172
EP  - 180
DO  - 10.1016/j.ejps.2015.10.017
ER  - 

@article{
author = "Srdić-Rajić, Tatjana and Nikolić, Katarina M. and Čavić, Milena R. and Đokić, Ivana and Gemović, Branislava S. and Perović, Vladimir R. and Veljković, Nevena V.",
year = "2016",
abstract = "Imidazoline I1 receptor signaling is associated with pathways that regulate cell viability leading to varied cell-type specific phenotypes. We demonstrated that the antihypertensive drug rilmenidine, a selective imidazoline I1 receptor agonist, modulates proliferation and stimulates the proapoptotic protein Bax thus inducing the perturbation of the mitochondrial pathway and apoptosis in human leukemic K562 cells. Rilmenidine acts through a mechanism which involves deactivation of Ras/MAP kinases ERK, p38 and JNK. Moreover, rilmenidine renders K562 cells, which are particularly resistant to chemotherapeutic agents, susceptible to the DNA damaging drug doxorubicin. The rilmenidine co-treatment with doxorubicin reverses G2/M arrest and triggers apoptotic response to DNA damage. Our data offer new insights into the pathways associated with imidazoline I1 receptor activation in K562 cells suggesting rilmenidine as a valuable tool to deepen our understanding of imidazoline I1 receptor signaling in hematologic malignancies and to search for medicinally active agents. (C) 2015 Elsevier B.V. All rights reserved.",
publisher = "Elsevier",
journal = "European Journal of Pharmaceutical Sciences",
title = "Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells",
volume = "81",
pages = "172-180",
doi = "10.1016/j.ejps.2015.10.017"
}

Srdić-Rajić, T., Nikolić, K. M., Čavić, M. R., Đokić, I., Gemović, B. S., Perović, V. R.,& Veljković, N. V.. (2016). Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells. in European Journal of Pharmaceutical Sciences
Elsevier., 81, 172-180.
https://doi.org/10.1016/j.ejps.2015.10.017

Srdić-Rajić T, Nikolić KM, Čavić MR, Đokić I, Gemović BS, Perović VR, Veljković NV. Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells. in European Journal of Pharmaceutical Sciences. 2016;81:172-180.
doi:10.1016/j.ejps.2015.10.017 .

Srdić-Rajić, Tatjana, Nikolić, Katarina M., Čavić, Milena R., Đokić, Ivana, Gemović, Branislava S., Perović, Vladimir R., Veljković, Nevena V., "Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells" in European Journal of Pharmaceutical Sciences, 81 (2016):172-180,
https://doi.org/10.1016/j.ejps.2015.10.017 . .

TY  - JOUR
AU  - Vučićević, Jelica
AU  - Srdić-Rajić, Tatjana
AU  - Pieroni, Marco
AU  - Laurila, Jonne M. M.
AU  - Perović, Vladimir R.
AU  - Tassini, Sabrina
AU  - Azzali, Elisa
AU  - Costantino, Gabriele
AU  - Glišić, Sanja
AU  - Agbaba, Danica
AU  - Scheinin, Mika
AU  - Nikolić, Katarina M.
AU  - Radi, Marco
AU  - Veljković, Nevena V.
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1110
AB  - The clonidine-like central antihypertensive agent rilmenidine, which has high affinity for I-1-type imidazoline receptors (I-1-IR) was recently found to have cytotoxic effects on cultured cancer cell lines. However, due to its pharmacological effects resulting also from alpha(2)-adrenoceptor activation, rilmenidine cannot be considered a suitable anticancer drug candidate. Here, we report the identification of novel rilmenidine- derived compounds with anticancer potential and devoid of alpha(2)-adrenoceptor effects by means of ligand-and structure-based drug design approaches. Starting from a large virtual library, eleven compounds were selected, synthesized and submitted to biological evaluation. The most active compound 5 exhibited a cytotoxic profile similar to that of rilmenidine, but without appreciable affinity to alpha(2)-adrenoceptors. In addition, compound 5 significantly enhanced the apoptotic response to doxorubicin, and may thus represent an important tool for the development of better adjuvant chemotherapeutic strategies for doxorubicin-insensitive cancers. (C) 2016 Elsevier Ltd. All rights reserved.
T2  - Bioorganic and Medicinal Chemistry
T1  - A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin
VL  - 24
IS  - 14
SP  - 3174
EP  - 3183
DO  - 10.1016/j.bmc.2016.05.043
ER  - 

@article{
author = "Vučićević, Jelica and Srdić-Rajić, Tatjana and Pieroni, Marco and Laurila, Jonne M. M. and Perović, Vladimir R. and Tassini, Sabrina and Azzali, Elisa and Costantino, Gabriele and Glišić, Sanja and Agbaba, Danica and Scheinin, Mika and Nikolić, Katarina M. and Radi, Marco and Veljković, Nevena V.",
year = "2016",
abstract = "The clonidine-like central antihypertensive agent rilmenidine, which has high affinity for I-1-type imidazoline receptors (I-1-IR) was recently found to have cytotoxic effects on cultured cancer cell lines. However, due to its pharmacological effects resulting also from alpha(2)-adrenoceptor activation, rilmenidine cannot be considered a suitable anticancer drug candidate. Here, we report the identification of novel rilmenidine- derived compounds with anticancer potential and devoid of alpha(2)-adrenoceptor effects by means of ligand-and structure-based drug design approaches. Starting from a large virtual library, eleven compounds were selected, synthesized and submitted to biological evaluation. The most active compound 5 exhibited a cytotoxic profile similar to that of rilmenidine, but without appreciable affinity to alpha(2)-adrenoceptors. In addition, compound 5 significantly enhanced the apoptotic response to doxorubicin, and may thus represent an important tool for the development of better adjuvant chemotherapeutic strategies for doxorubicin-insensitive cancers. (C) 2016 Elsevier Ltd. All rights reserved.",
journal = "Bioorganic and Medicinal Chemistry",
title = "A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin",
volume = "24",
number = "14",
pages = "3174-3183",
doi = "10.1016/j.bmc.2016.05.043"
}

Vučićević, J., Srdić-Rajić, T., Pieroni, M., Laurila, J. M. M., Perović, V. R., Tassini, S., Azzali, E., Costantino, G., Glišić, S., Agbaba, D., Scheinin, M., Nikolić, K. M., Radi, M.,& Veljković, N. V.. (2016). A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin. in Bioorganic and Medicinal Chemistry, 24(14), 3174-3183.
https://doi.org/10.1016/j.bmc.2016.05.043

Vučićević J, Srdić-Rajić T, Pieroni M, Laurila JMM, Perović VR, Tassini S, Azzali E, Costantino G, Glišić S, Agbaba D, Scheinin M, Nikolić KM, Radi M, Veljković NV. A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin. in Bioorganic and Medicinal Chemistry. 2016;24(14):3174-3183.
doi:10.1016/j.bmc.2016.05.043 .

Vučićević, Jelica, Srdić-Rajić, Tatjana, Pieroni, Marco, Laurila, Jonne M. M., Perović, Vladimir R., Tassini, Sabrina, Azzali, Elisa, Costantino, Gabriele, Glišić, Sanja, Agbaba, Danica, Scheinin, Mika, Nikolić, Katarina M., Radi, Marco, Veljković, Nevena V., "A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin" in Bioorganic and Medicinal Chemistry, 24, no. 14 (2016):3174-3183,
https://doi.org/10.1016/j.bmc.2016.05.043 . .

TY  - JOUR
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
AU  - Nicolson, Garth L.
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1372
AB  - Background: Numerous in vitro and in vivo studies, in addition to clinical data, demonstrate that pomegranate juice can prevent or slow-down the progression of some types of cancers. Despite the well-documented effect of pomegranate ingredients on neoplastic changes, the molecular mechanism(s) underlying this phenomenon remains elusive. Methods: For the study of pomegranate ingredients the electron-ion interaction potential (EIIP) and the average quasi valence number (AQVN) were used. These molecular descriptors can be used to describe the long-range intermolecular interactions in biological systems and can identify substances with strong electron-acceptor properties. In this study, candidate human proteins interacting with pomegranate flavonoids have been analyzed by the informational spectrum method (ISM). This represents a virtual spectroscopy method for studying protein molecular interactions. Results: Our analysis indicates that the anti-cancer properties of pomegranate juice can be ascribed to the strong electron-acceptor properties of its chemical ingredients. This analysis also suggests that pomegranate flavonoids inhibit the NF-kappaB (NF-kappa B) pathway, which plays a critical role in the pathogenesis of cancer. Conclusion: The results offer a possible explanation for an important molecular mechanism underlying the anticancer activity of pomegranate ingredients, which could also serve as a basis for the development of new therapeutic compositions of food supplements with pomegranate-like anticancer properties.
T2  - Functional Foods in Health and Disease
T1  - Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics
VL  - 6
IS  - 12
SP  - 769
EP  - 787
DO  - 10.31989/ffhd.v6i12.289
ER  - 

@article{
author = "Veljković, Veljko and Glišić, Sanja and Perović, Vladimir R. and Veljković, Nevena V. and Nicolson, Garth L.",
year = "2016",
abstract = "Background: Numerous in vitro and in vivo studies, in addition to clinical data, demonstrate that pomegranate juice can prevent or slow-down the progression of some types of cancers. Despite the well-documented effect of pomegranate ingredients on neoplastic changes, the molecular mechanism(s) underlying this phenomenon remains elusive. Methods: For the study of pomegranate ingredients the electron-ion interaction potential (EIIP) and the average quasi valence number (AQVN) were used. These molecular descriptors can be used to describe the long-range intermolecular interactions in biological systems and can identify substances with strong electron-acceptor properties. In this study, candidate human proteins interacting with pomegranate flavonoids have been analyzed by the informational spectrum method (ISM). This represents a virtual spectroscopy method for studying protein molecular interactions. Results: Our analysis indicates that the anti-cancer properties of pomegranate juice can be ascribed to the strong electron-acceptor properties of its chemical ingredients. This analysis also suggests that pomegranate flavonoids inhibit the NF-kappaB (NF-kappa B) pathway, which plays a critical role in the pathogenesis of cancer. Conclusion: The results offer a possible explanation for an important molecular mechanism underlying the anticancer activity of pomegranate ingredients, which could also serve as a basis for the development of new therapeutic compositions of food supplements with pomegranate-like anticancer properties.",
journal = "Functional Foods in Health and Disease",
title = "Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics",
volume = "6",
number = "12",
pages = "769-787",
doi = "10.31989/ffhd.v6i12.289"
}

Veljković, V., Glišić, S., Perović, V. R., Veljković, N. V.,& Nicolson, G. L.. (2016). Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics. in Functional Foods in Health and Disease, 6(12), 769-787.
https://doi.org/10.31989/ffhd.v6i12.289

Veljković V, Glišić S, Perović VR, Veljković NV, Nicolson GL. Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics. in Functional Foods in Health and Disease. 2016;6(12):769-787.
doi:10.31989/ffhd.v6i12.289 .

Veljković, Veljko, Glišić, Sanja, Perović, Vladimir R., Veljković, Nevena V., Nicolson, Garth L., "Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics" in Functional Foods in Health and Disease, 6, no. 12 (2016):769-787,
https://doi.org/10.31989/ffhd.v6i12.289 . .