Veljković, Nevena V.

Link to this page

Authority KeyName Variants
orcid::0000-0001-6562-5800
  • Veljković, Nevena V. (68)
Projects
Application of the EIIP/ISM bioinformatics platform in discovery of novel therapeutic targets and potential therapeutic molecules Synthesis, Quantitative Structure and Activity Relationship, Physico-Chemical Characterisation and Analysis of Pharmacologically Active Substances
Agencia Nacional de Promocion Cientifica y Tecnologica (ANPCyT) of Argentina [PICT-2015/3367] Agencia Nacional de Promocion Cientifica y Tecnologica (ANPCyT) of Argentina [PICT2017/1924]
Basileus program Basileus S Program, Slovenian Research Agency program [P4-0053]
BBSRC (BB/K000446/1) Carlsberg Distinguished Fellowship [CF18-0314]
Consejo Nacional de Ciencia y Tecnologia (CONACyT) [215503] COST Action (BM1405)
COST Action BM1405 NGP-net, ELIXIR-IIB, Hungarian Academy of Sciences [LP2014-16], Hungarian Scientific Research Fund [OTKA K 108798], AIRC Research Fellowship, Spanish Ministerio de Educacion Cultura i Deporte PhD Fellowship, Mexican National Council for Science and Technology (CONACYT) [215503], Grant PortoNeuroDRIve'i3S - Norte Portugal Regional Operational Programme (NORTE), under the PORTUGAL Partnership Agreement, through the European Regional Development Fund (ERDF), Direction Generale des Armees, Aix-Marseille University PhD Fellowship, OTKA Grant [PD-OTKA 108772], French Ministry of National Education, Research and Technology PhD Fellowship, ICREAAcademia Award, Odysseus Grant from Research Foundation Flanders (FWO) [G.0029.12], AIRC IG Grant [17753], Italian Ministry of Health [GR-2011-02347754, GR-2011-02346845], Swedish Research Council Grant [VR-NT 2012-5046] Danmarks Grundforskningsfond [DNRF125]
Elixir-GR, Action 'Reinforcement of the Research and Innovation Infrastructure', Operational Programme 'Competitiveness, Entrepreneurship and Innovation' [NSRF] European Commission [TRIoH LSHG-CT-2003-503480]
European COST Action (GLISTEN) [CM1207], Chiesi Foundation European Regional Development Fund [POCI01-0145-FEDER-029221]
European Regional Development Fund [POCI-01-0145-FEDER-031173] European Union's Horizon 2020 research and innovation programme [778247]. Funding for open access charge: European Union's Horizon 2020 research and innovation programme [778247]
H2020-MSCA-RISE project REFRACT [GA No. 823886] Hungarian Academy of Sciences [LP2014-18]
Hungarian Academy of Sciences [PREMIUM-2017-48] Hungarian National Research, Development, and Innovation Office (NKFIH) [FK-128133]
ICREA CHAARM - Combined Highly Active Anti-retroviral Microbicides
TRANSPLANT - Trans-national Infrastructure for Plant Genomic Science MAESTRA - Learning from Massive, Incompletely annotated, and Structured Data
Hormonal regulation of expression and activity of the nitric oxide synthase and sodium-potassium pump in experimental models of insulin resistance, diabetes and cardiovascular disorders Molecular determinants for tumor marker design
Genetic basis of human vascular and inflammatory diseases Carotid disease in Serbia - pathologic dynamics, prevention, diagnostics and inovative therapeutic methods

Author's Bibliography

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

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

(2021)

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

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

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

(2020)

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

Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field

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

(2020)

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

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

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

(2019)

TY  - JOUR
AU  - Zhou, Naihui
AU  - Jiang, Yuxiang
AU  - Bergquist, Timothy R
AU  - Lee, Alexandra J
AU  - Kacsoh, Balint Z
AU  - Crocker, Alex W
AU  - Lewis, Kimberley A
AU  - Georghiou, George
AU  - Nguyen, Huy N
AU  - Hamid, Md Nafiz
AU  - Davis, Larry
AU  - Dogan, Tunca
AU  - Atalay, Volkan
AU  - Rifaioglu, Ahmet S
AU  - Dalkıran, Alperen
AU  - Cetin Atalay, Rengul
AU  - Zhang, Chengxin
AU  - Hurto, Rebecca L
AU  - Freddolino, Peter L
AU  - Zhang, Yang
AU  - Bhat, Prajwal
AU  - Supek, Fran
AU  - Fernández, José M
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Davidović, Radoslav S.
AU  - Šumonja, Neven
AU  - Veljković, Nevena V.
AU  - Asgari, Ehsaneddin
AU  - Mofrad, Mohammad R.K.
AU  - Profiti, Giuseppe
AU  - Savojardo, Castrense
AU  - Martelli, Pier Luigi
AU  - Casadio, Rita
AU  - Boecker, Florian
AU  - Schoof, Heiko
AU  - Kahanda, Indika
AU  - Thurlby, Natalie
AU  - McHardy, Alice C
AU  - Renaux, Alexandre
AU  - Saidi, Rabie
AU  - Gough, Julian
AU  - Freitas, Alex A
AU  - Antczak, Magdalena
AU  - Fabris, Fabio
AU  - Wass, Mark N
AU  - Hou, Jie
AU  - Cheng, Jianlin
AU  - Wang, Zheng
AU  - Romero, Alfonso E
AU  - Paccanaro, Alberto
AU  - Yang, Haixuan
AU  - Goldberg, Tatyana
AU  - Zhao, Chenguang
AU  - Holm, Liisa
AU  - Törönen, Petri
AU  - Medlar, Alan J
AU  - Zosa, Elaine
AU  - Borukhov, Itamar
AU  - Novikov, Ilya
AU  - Wilkins, Angela
AU  - Lichtarge, Olivier
AU  - Chi, Po-Han
AU  - Tseng, Wei-Cheng
AU  - Linial, Michal
AU  - Rose, Peter W
AU  - Dessimoz, Christophe
AU  - Vidulin, Vedrana
AU  - Dzeroski, Saso
AU  - Sillitoe, Ian
AU  - Das, Sayoni
AU  - Lees, Jonathan Gill
AU  - Jones, David T
AU  - Wan, Cen
AU  - Cozzetto, Domenico
AU  - Fa, Rui
AU  - Torres, Mateo
AU  - Warwick Vesztrocy, Alex
AU  - Rodriguez, Jose Manuel
AU  - Tress, Michael L
AU  - Frasca, Marco
AU  - Notaro, Marco
AU  - Grossi, Giuliano
AU  - Petrini, Alessandro
AU  - Re, Matteo
AU  - Valentini, Giorgio
AU  - Mesiti, Marco
AU  - Roche, Daniel B
AU  - Reeb, Jonas
AU  - Ritchie, David W
AU  - Aridhi, Sabeur
AU  - Alborzi, Seyed Ziaeddin
AU  - Devignes, Marie-Dominique
AU  - Koo, Da Chen Emily
AU  - Bonneau, Richard
AU  - Gligorijević, Vladimir
AU  - Barot, Meet
AU  - Fang, Hai
AU  - Toppo, Stefano
AU  - Lavezzo, Enrico
AU  - Falda, Marco
AU  - Berselli, Michele
AU  - Tosatto, Silvio C.E.
AU  - Carraro, Marco
AU  - Piovesan, Damiano
AU  - Ur Rehman, Hafeez
AU  - Mao, Qizhong
AU  - Zhang, Shanshan
AU  - Vucetic, Slobodan
AU  - Black, Gage S
AU  - Jo, Dane
AU  - Suh, Erica
AU  - Dayton, Jonathan B
AU  - Larsen, Dallas J
AU  - Omdahl, Ashton R
AU  - McGuffin, Liam J
AU  - Brackenridge, Danielle A
AU  - Babbitt, Patricia C
AU  - Yunes, Jeffrey M
AU  - Fontana, Paolo
AU  - Zhang, Feng
AU  - Zhu, Shanfeng
AU  - You, Ronghui
AU  - Zhang, Zihan
AU  - Dai, Suyang
AU  - Yao, Shuwei
AU  - Tian, Weidong
AU  - Cao, Renzhi
AU  - Chandler, Caleb
AU  - Amezola, Miguel
AU  - Johnson, Devon
AU  - Chang, Jia-Ming
AU  - Liao, Wen-Hung
AU  - Liu, Yi-Wei
AU  - Pascarelli, Stefano
AU  - Frank, Yotam
AU  - Hoehndorf, Robert
AU  - Kulmanov, Maxat
AU  - Boudellioua, Imane
AU  - Politano, Gianfranco
AU  - Di Carlo, Stefano
AU  - Benso, Alfredo
AU  - Hakala, Kai
AU  - Ginter, Filip
AU  - Mehryary, Farrokh
AU  - Kaewphan, Suwisa
AU  - Björne, Jari
AU  - Moen, Hans
AU  - Tolvanen, Martti E.E.
AU  - Salakoski, Tapio
AU  - Kihara, Daisuke
AU  - Jain, Aashish
AU  - Šmuc, Tomislav
AU  - Altenhoff, Adrian
AU  - Ben-Hur, Asa
AU  - Rost, Burkhard
AU  - Brenner, Steven E
AU  - Orengo, Christine A
AU  - Jeffery, Constance J
AU  - Bosco, Giovanni
AU  - Hogan, Deborah A
AU  - Martin, Maria J
AU  - O’Donovan, Claire
AU  - Mooney, Sean D
AU  - Greene, Casey S
AU  - Radivojac, Predrag
AU  - Friedberg, Iddo
PY  - 2019
UR  - http://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",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/8655",
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.
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. Genome Biology. 2019;20(1):244
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" Genome Biology, 20, no. 1 (2019):244,
https://doi.org/10.1186/s13059-019-1835-8 .
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39

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

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

(2019)

TY  - JOUR
AU  - Radošević, Draginja
AU  - Senćanski, Milan V.
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
AU  - Prljić, Jelena
AU  - Veljković, Veljko
AU  - Mantlo, Emily
AU  - Bukreyeva, Natalya
AU  - Paessler, Slobodan
AU  - Glišić, Sanja
PY  - 2019
UR  - https://www.frontiersin.org/article/10.3389/fcimb.2019.00067/full
UR  - http://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
IS  - MAR
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",
url = "https://www.frontiersin.org/article/10.3389/fcimb.2019.00067/full, http://vinar.vin.bg.ac.rs/handle/123456789/8163",
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",
number = "MAR",
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.
Frontiers in Cellular and Infection Microbiology, 9(MAR).
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. Frontiers in Cellular and Infection Microbiology. 2019;9(MAR)
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" Frontiers in Cellular and Infection Microbiology, 9, no. MAR (2019),
https://doi.org/10.3389/fcimb.2019.00067 .
1
5
4
4

DisProt: intrinsic protein disorder annotation in 2020

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

(2019)

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

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

(2019)

TY  - JOUR
AU  - Šumonja, Neven
AU  - Gemović, Branislava S.
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
PY  - 2019
UR  - http://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",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/8395",
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.
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. Amino Acids. 2019;51(8):1187-1200
Šumonja Neven, Gemović Branislava S., Veljković Nevena V., Perović Vladimir R., "Automated feature engineering improves prediction of protein–protein interactions" Amino Acids, 51, no. 8 (2019):1187-1200,
https://doi.org/10.1007/s00726-019-02756-9 .
1
8
2
6

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

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

(2019)

TY  - JOUR
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
AU  - Šnajder, Marko
AU  - Veljković, Nevena V.
AU  - Poklar Ulrih, Nataša
AU  - Mavri, Janez
AU  - Vrecl, Milka
PY  - 2019
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/8648
AB  - This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).
T2  - Scientific Reports
T1  - Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)
VL  - 9
IS  - 1
SP  - 16555
DO  - 10.1038/s41598-019-52934-8
ER  - 
@article{
author = "Senćanski, Milan V. and Glišić, Sanja and Šnajder, Marko and Veljković, Nevena V. and Poklar Ulrih, Nataša and Mavri, Janez and Vrecl, Milka",
year = "2019",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/8648",
abstract = "This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).",
journal = "Scientific Reports",
title = "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)",
volume = "9",
number = "1",
pages = "16555",
doi = "10.1038/s41598-019-52934-8"
}
Senćanski, M. V., Glišić, S., Šnajder, M., Veljković, N. V., Poklar Ulrih, N., Mavri, J.,& Vrecl, M. (2019). Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR).
Scientific Reports, 9(1), 16555.
https://doi.org/10.1038/s41598-019-52934-8
Senćanski MV, Glišić S, Šnajder M, Veljković NV, Poklar Ulrih N, Mavri J, Vrecl M. Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR). Scientific Reports. 2019;9(1):16555
Senćanski Milan V., Glišić Sanja, Šnajder Marko, Veljković Nevena V., Poklar Ulrih Nataša, Mavri Janez, Vrecl Milka, "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)" Scientific Reports, 9, no. 1 (2019):16555,
https://doi.org/10.1038/s41598-019-52934-8 .
4
7
1
3

Recent In Silico Resources for Drug Design and Discovery (Editorial)

Veljković, Nevena V.

(2019)

TY  - JOUR
AU  - Veljković, Nevena V.
PY  - 2019
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/8537
T2  - Current Medicinal Chemistry
T1  - Recent In Silico Resources for Drug Design and Discovery (Editorial)
VL  - 26
IS  - 21
SP  - 3836
EP  - 3837
DO  - 10.2174/092986732621190919104301
ER  - 
@article{
author = "Veljković, Nevena V.",
year = "2019",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/8537",
journal = "Current Medicinal Chemistry",
title = "Recent In Silico Resources for Drug Design and Discovery (Editorial)",
volume = "26",
number = "21",
pages = "3836-3837",
doi = "10.2174/092986732621190919104301"
}
Veljković, N. V. (2019). Recent In Silico Resources for Drug Design and Discovery (Editorial).
Current Medicinal Chemistry, 26(21), 3836-3837.
https://doi.org/10.2174/092986732621190919104301
Veljković NV. Recent In Silico Resources for Drug Design and Discovery (Editorial). Current Medicinal Chemistry. 2019;26(21):3836-3837
Veljković Nevena V., "Recent In Silico Resources for Drug Design and Discovery (Editorial)" Current Medicinal Chemistry, 26, no. 21 (2019):3836-3837,
https://doi.org/10.2174/092986732621190919104301 .
1
1
1

Functional characterization of β2-adrenergic and insulin receptor heteromers

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

(2019)

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

Genetic Markers for Coronary Artery Disease

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

(2018)

TY  - JOUR
AU  - Veljković, Nevena V.
AU  - Zarić, Božidarka
AU  - Đurić, Ilona
AU  - Obradović, Milan M.
AU  - Sudar-Milovanović, Emina
AU  - Radak, Đorđe J.
AU  - Isenović, Esma R.
PY  - 2018
UR  - http://www.mdpi.com/1010-660X/54/3/36
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/7878
AB  - Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
T2  - Medicina
T1  - Genetic Markers for Coronary Artery Disease
VL  - 54
IS  - 3
SP  - 36
DO  - 10.3390/medicina54030036
ER  - 
@article{
author = "Veljković, Nevena V. and Zarić, Božidarka and Đurić, Ilona and Obradović, Milan M. and Sudar-Milovanović, Emina and Radak, Đorđe J. and Isenović, Esma R.",
year = "2018",
url = "http://www.mdpi.com/1010-660X/54/3/36, http://vinar.vin.bg.ac.rs/handle/123456789/7878",
abstract = "Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.",
journal = "Medicina",
title = "Genetic Markers for Coronary Artery Disease",
volume = "54",
number = "3",
pages = "36",
doi = "10.3390/medicina54030036"
}
Veljković, N. V., Zarić, B., Đurić, I., Obradović, M. M., Sudar-Milovanović, E., Radak, Đ. J.,& Isenović, E. R. (2018). Genetic Markers for Coronary Artery Disease.
Medicina, 54(3), 36.
https://doi.org/10.3390/medicina54030036
Veljković NV, Zarić B, Đurić I, Obradović MM, Sudar-Milovanović E, Radak ĐJ, Isenović ER. Genetic Markers for Coronary Artery Disease. Medicina. 2018;54(3):36
Veljković Nevena V., Zarić Božidarka, Đurić Ilona, Obradović Milan M., Sudar-Milovanović Emina, Radak Đorđe J., Isenović Esma R., "Genetic Markers for Coronary Artery Disease" Medicina, 54, no. 3 (2018):36,
https://doi.org/10.3390/medicina54030036 .
1
5
6
6

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

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

(2018)

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Marsh, Lindsey A.
AU  - Radovanović, Sandro
AU  - Vukićević, Milan
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2018
UR  - http://www.nature.com/articles/s41598-018-28815-x
UR  - http://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",
url = "http://www.nature.com/articles/s41598-018-28815-x, http://vinar.vin.bg.ac.rs/handle/123456789/7811",
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.
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. Scientific Reports. 2018;8(1):10563
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" Scientific Reports, 8, no. 1 (2018):10563,
https://doi.org/10.1038/s41598-018-28815-x .
4
7
4
4

Ibuprofen as a template molecule for drug design against Ebola virus

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

(2018)

TY  - JOUR
AU  - Paessler, Slobodan
AU  - Huang, Cheng
AU  - Senćanski, Milan V.
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
AU  - Glišić, Sanja
AU  - Veljković, Veljko
PY  - 2018
UR  - http://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
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",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/7695",
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"
}
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.
Frontiers in Bioscience - Landmark, 23(5), 947-953.
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. Frontiers in Bioscience - Landmark. 2018;23(5):947-953
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" Frontiers in Bioscience - Landmark, 23, no. 5 (2018):947-953
13

DisProt 7.0: a major update of the database of disordered proteins

Piovesan, Damiano; Tabaro, Francesco; Micetic, Ivan; Necci, Marco; Quaglia, Federica; Oldfield, Christopher J.; Aspromonte, Maria Cristina; Davey, Norman E.; Davidović, Radoslav S.; Dosztanyi, Zsuzsanna; Elofsson, Arne; Gasparini, Alessandra; Hatos, Andras; Kajava, Andrey V.; Kalmar, Lajos; Leonardi, Emanuela; Lazar, Tamas; Macedo-Ribeiro, Sandra; Macossay-Castillo, Mauricio; Meszaros, Attila; Minervini, Giovanni; Murvai, Nikoletta; Pujols, Jordi; Roche, Daniel B.; Salladini, Edoardo; Schad, Eva; Schramm, Antoine; Szabo, Beata; Tantos, Agnes; Tonello, Fiorella; Tsirigos, Konstantinos D.; Veljković, Nevena V.; Ventura, Salvador; Vranken, Wim; Warholm, Per; Uversky, Vladimir N.; Dunker, A. Keith; Longhi, Sonia; Tompa, Peter; Tosatto, Silvio C. E.

(2017)

TY  - JOUR
AU  - Piovesan, Damiano
AU  - Tabaro, Francesco
AU  - Micetic, Ivan
AU  - Necci, Marco
AU  - Quaglia, Federica
AU  - Oldfield, Christopher J.
AU  - Aspromonte, Maria Cristina
AU  - Davey, Norman E.
AU  - Davidović, Radoslav S.
AU  - Dosztanyi, Zsuzsanna
AU  - Elofsson, Arne
AU  - Gasparini, Alessandra
AU  - Hatos, Andras
AU  - Kajava, Andrey V.
AU  - Kalmar, Lajos
AU  - Leonardi, Emanuela
AU  - Lazar, Tamas
AU  - Macedo-Ribeiro, Sandra
AU  - Macossay-Castillo, Mauricio
AU  - Meszaros, Attila
AU  - Minervini, Giovanni
AU  - Murvai, Nikoletta
AU  - Pujols, Jordi
AU  - Roche, Daniel B.
AU  - Salladini, Edoardo
AU  - Schad, Eva
AU  - Schramm, Antoine
AU  - Szabo, Beata
AU  - Tantos, Agnes
AU  - Tonello, Fiorella
AU  - Tsirigos, Konstantinos D.
AU  - Veljković, Nevena V.
AU  - Ventura, Salvador
AU  - Vranken, Wim
AU  - Warholm, Per
AU  - Uversky, Vladimir N.
AU  - Dunker, A. Keith
AU  - Longhi, Sonia
AU  - Tompa, Peter
AU  - Tosatto, Silvio C. E.
PY  - 2017
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/1464
AB  - The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance ( primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.
T2  - Nucleic Acids Research
T1  - DisProt 7.0: a major update of the database of disordered proteins
VL  - 45
IS  - D1
SP  - D219
EP  - D227
DO  - 10.1093/nar/gkw1056
ER  - 
@article{
author = "Piovesan, Damiano and Tabaro, Francesco and Micetic, Ivan and Necci, Marco and Quaglia, Federica and Oldfield, Christopher J. and Aspromonte, Maria Cristina and Davey, Norman E. and Davidović, Radoslav S. and Dosztanyi, Zsuzsanna and Elofsson, Arne and Gasparini, Alessandra and Hatos, Andras and Kajava, Andrey V. and Kalmar, Lajos and Leonardi, Emanuela and Lazar, Tamas and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Meszaros, Attila and Minervini, Giovanni and Murvai, Nikoletta and Pujols, Jordi and Roche, Daniel B. and Salladini, Edoardo and Schad, Eva and Schramm, Antoine and Szabo, Beata and Tantos, Agnes and Tonello, Fiorella and Tsirigos, Konstantinos D. and Veljković, Nevena V. and Ventura, Salvador and Vranken, Wim and Warholm, Per and Uversky, Vladimir N. and Dunker, A. Keith and Longhi, Sonia and Tompa, Peter and Tosatto, Silvio C. E.",
year = "2017",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1464",
abstract = "The Database of Protein Disorder (DisProt, URL: www.disprot.org) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance ( primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.",
journal = "Nucleic Acids Research",
title = "DisProt 7.0: a major update of the database of disordered proteins",
volume = "45",
number = "D1",
pages = "D219-D227",
doi = "10.1093/nar/gkw1056"
}
Piovesan, D., Tabaro, F., Micetic, I., Necci, M., Quaglia, F., Oldfield, C. J., Aspromonte, M. C., Davey, N. E., Davidović, R. S., Dosztanyi, Z., Elofsson, A., Gasparini, A., Hatos, A., Kajava, A. V., Kalmar, L., Leonardi, E., Lazar, T., Macedo-Ribeiro, S., Macossay-Castillo, M., Meszaros, A., Minervini, G., Murvai, N., Pujols, J., Roche, D. B., Salladini, E., Schad, E., Schramm, A., Szabo, B., Tantos, A., Tonello, F., Tsirigos, K. D., Veljković, N. V., Ventura, S., Vranken, W., Warholm, P., Uversky, V. N., Dunker, A. K., Longhi, S., Tompa, P.,& Tosatto, S. C. E. (2017). DisProt 7.0: a major update of the database of disordered proteins.
Nucleic Acids Research, 45(D1), D219-D227.
https://doi.org/10.1093/nar/gkw1056
Piovesan D, Tabaro F, Micetic I, Necci M, Quaglia F, Oldfield CJ, Aspromonte MC, Davey NE, Davidović RS, Dosztanyi Z, Elofsson A, Gasparini A, Hatos A, Kajava AV, Kalmar L, Leonardi E, Lazar T, Macedo-Ribeiro S, Macossay-Castillo M, Meszaros A, Minervini G, Murvai N, Pujols J, Roche DB, Salladini E, Schad E, Schramm A, Szabo B, Tantos A, Tonello F, Tsirigos KD, Veljković NV, Ventura S, Vranken W, Warholm P, Uversky VN, Dunker AK, Longhi S, Tompa P, Tosatto SCE. DisProt 7.0: a major update of the database of disordered proteins. Nucleic Acids Research. 2017;45(D1):D219-D227
Piovesan Damiano, Tabaro Francesco, Micetic Ivan, Necci Marco, Quaglia Federica, Oldfield Christopher J., Aspromonte Maria Cristina, Davey Norman E., Davidović Radoslav S., Dosztanyi Zsuzsanna, Elofsson Arne, Gasparini Alessandra, Hatos Andras, Kajava Andrey V., Kalmar Lajos, Leonardi Emanuela, Lazar Tamas, Macedo-Ribeiro Sandra, Macossay-Castillo Mauricio, Meszaros Attila, Minervini Giovanni, Murvai Nikoletta, Pujols Jordi, Roche Daniel B., Salladini Edoardo, Schad Eva, Schramm Antoine, Szabo Beata, Tantos Agnes, Tonello Fiorella, Tsirigos Konstantinos D., Veljković Nevena V., Ventura Salvador, Vranken Wim, Warholm Per, Uversky Vladimir N., Dunker A. Keith, Longhi Sonia, Tompa Peter, Tosatto Silvio C. E., "DisProt 7.0: a major update of the database of disordered proteins" Nucleic Acids Research, 45, no. D1 (2017):D219-D227,
https://doi.org/10.1093/nar/gkw1056 .
7
170
106
125

DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017)

Piovesan, Damiano; Tabaro, Francesco; Micetic, Ivan; Necci, Marco; Quaglia, Federica; Oldfield, Christopher J.; Aspromonte, Maria Cristina; Davey, Norman E.; Davidović, Radoslav S.; Dosztanyi, Zsuzsanna; Elofsson, Arne; Gasparini, Alessandra; Hatos, Andras; Kajava, Andrey V.; Kalmar, Lajos; Leonardi, Emanuela; Lazar, Tamas; Macedo-Ribeiro, Sandra; Macossay-Castillo, Mauricio; Meszaros, Attila; Minervini, Giovanni; Murvai, Nikoletta; Pujols, Jordi; Roche, Daniel B.; Salladini, Edoardo; Schad, Eva; Schramm, Antoine; Szabo, Beata; Tantos, Agnes; Tonello, Fiorella; Tsirigos, Konstantinos D.; Veljković, Nevena V.; Ventura, Salvador; Vranken, Wim; Warholm, Per; Uversky, Vladimir N.; Dunker, A. Keith; Longhi, Sonia; Tompa, Peter; Tosatto, Silvio C. E.

(2017)

TY  - BOOK
AU  - Piovesan, Damiano
AU  - Tabaro, Francesco
AU  - Micetic, Ivan
AU  - Necci, Marco
AU  - Quaglia, Federica
AU  - Oldfield, Christopher J.
AU  - Aspromonte, Maria Cristina
AU  - Davey, Norman E.
AU  - Davidović, Radoslav S.
AU  - Dosztanyi, Zsuzsanna
AU  - Elofsson, Arne
AU  - Gasparini, Alessandra
AU  - Hatos, Andras
AU  - Kajava, Andrey V.
AU  - Kalmar, Lajos
AU  - Leonardi, Emanuela
AU  - Lazar, Tamas
AU  - Macedo-Ribeiro, Sandra
AU  - Macossay-Castillo, Mauricio
AU  - Meszaros, Attila
AU  - Minervini, Giovanni
AU  - Murvai, Nikoletta
AU  - Pujols, Jordi
AU  - Roche, Daniel B.
AU  - Salladini, Edoardo
AU  - Schad, Eva
AU  - Schramm, Antoine
AU  - Szabo, Beata
AU  - Tantos, Agnes
AU  - Tonello, Fiorella
AU  - Tsirigos, Konstantinos D.
AU  - Veljković, Nevena V.
AU  - Ventura, Salvador
AU  - Vranken, Wim
AU  - Warholm, Per
AU  - Uversky, Vladimir N.
AU  - Dunker, A. Keith
AU  - Longhi, Sonia
AU  - Tompa, Peter
AU  - Tosatto, Silvio C. E.
PY  - 2017
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/1465
T2  - Nucleic Acids Research
T1  - DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017)
VL  - 45
IS  - D1
SP  - D1123
EP  - D1124
DO  - 10.1093/nar/gkw1279
ER  - 
@book{
author = "Piovesan, Damiano and Tabaro, Francesco and Micetic, Ivan and Necci, Marco and Quaglia, Federica and Oldfield, Christopher J. and Aspromonte, Maria Cristina and Davey, Norman E. and Davidović, Radoslav S. and Dosztanyi, Zsuzsanna and Elofsson, Arne and Gasparini, Alessandra and Hatos, Andras and Kajava, Andrey V. and Kalmar, Lajos and Leonardi, Emanuela and Lazar, Tamas and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Meszaros, Attila and Minervini, Giovanni and Murvai, Nikoletta and Pujols, Jordi and Roche, Daniel B. and Salladini, Edoardo and Schad, Eva and Schramm, Antoine and Szabo, Beata and Tantos, Agnes and Tonello, Fiorella and Tsirigos, Konstantinos D. and Veljković, Nevena V. and Ventura, Salvador and Vranken, Wim and Warholm, Per and Uversky, Vladimir N. and Dunker, A. Keith and Longhi, Sonia and Tompa, Peter and Tosatto, Silvio C. E.",
year = "2017",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1465",
journal = "Nucleic Acids Research",
title = "DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017)",
volume = "45",
number = "D1",
pages = "D1123-D1124",
doi = "10.1093/nar/gkw1279"
}
Piovesan, D., Tabaro, F., Micetic, I., Necci, M., Quaglia, F., Oldfield, C. J., Aspromonte, M. C., Davey, N. E., Davidović, R. S., Dosztanyi, Z., Elofsson, A., Gasparini, A., Hatos, A., Kajava, A. V., Kalmar, L., Leonardi, E., Lazar, T., Macedo-Ribeiro, S., Macossay-Castillo, M., Meszaros, A., Minervini, G., Murvai, N., Pujols, J., Roche, D. B., Salladini, E., Schad, E., Schramm, A., Szabo, B., Tantos, A., Tonello, F., Tsirigos, K. D., Veljković, N. V., Ventura, S., Vranken, W., Warholm, P., Uversky, V. N., Dunker, A. K., Longhi, S., Tompa, P.,& Tosatto, S. C. E. (2017). DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017).
Nucleic Acids Research, 45(D1), D1123-D1124.
https://doi.org/10.1093/nar/gkw1279
Piovesan D, Tabaro F, Micetic I, Necci M, Quaglia F, Oldfield CJ, Aspromonte MC, Davey NE, Davidović RS, Dosztanyi Z, Elofsson A, Gasparini A, Hatos A, Kajava AV, Kalmar L, Leonardi E, Lazar T, Macedo-Ribeiro S, Macossay-Castillo M, Meszaros A, Minervini G, Murvai N, Pujols J, Roche DB, Salladini E, Schad E, Schramm A, Szabo B, Tantos A, Tonello F, Tsirigos KD, Veljković NV, Ventura S, Vranken W, Warholm P, Uversky VN, Dunker AK, Longhi S, Tompa P, Tosatto SCE. DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017). Nucleic Acids Research. 2017;45(D1):D1123-D1124
Piovesan Damiano, Tabaro Francesco, Micetic Ivan, Necci Marco, Quaglia Federica, Oldfield Christopher J., Aspromonte Maria Cristina, Davey Norman E., Davidović Radoslav S., Dosztanyi Zsuzsanna, Elofsson Arne, Gasparini Alessandra, Hatos Andras, Kajava Andrey V., Kalmar Lajos, Leonardi Emanuela, Lazar Tamas, Macedo-Ribeiro Sandra, Macossay-Castillo Mauricio, Meszaros Attila, Minervini Giovanni, Murvai Nikoletta, Pujols Jordi, Roche Daniel B., Salladini Edoardo, Schad Eva, Schramm Antoine, Szabo Beata, Tantos Agnes, Tonello Fiorella, Tsirigos Konstantinos D., Veljković Nevena V., Ventura Salvador, Vranken Wim, Warholm Per, Uversky Vladimir N., Dunker A. Keith, Longhi Sonia, Tompa Peter, Tosatto Silvio C. E., "DisProt 7.0: a major update of the database of disordered proteins (vol 45, pg D219, 2017)" Nucleic Acids Research, 45, no. D1 (2017):D1123-D1124,
https://doi.org/10.1093/nar/gkw1279 .
3
39
39
14

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

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

(2017)

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Gemović, Branislava S.
AU  - Toska, Eneda
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2017
UR  - http://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",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1468",
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.
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. Bioinformatics. 2017;33(2):289-291
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" Bioinformatics, 33, no. 2 (2017):289-291,
https://doi.org/10.1093/bioinformatics/btw590 .
1
7
5
6

Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China

Veljković, Veljko; Veljković, Nevena V.; Paessler, Slobodan; Goeijenbier, Marco; Perović, Vladimir R.; Glišić, Sanja; Muller, Claude P.

(2016)

TY  - JOUR
AU  - Veljković, Veljko
AU  - Veljković, Nevena V.
AU  - Paessler, Slobodan
AU  - Goeijenbier, Marco
AU  - Perović, Vladimir R.
AU  - Glišić, Sanja
AU  - Muller, Claude P.
PY  - 2016
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/1300
AB  - Influenza A virus (IAV) subtypes against which little or no pre-existing immunity exists in humans represent a serious threat to global public health. Monitoring of IAV in animal hosts is essential for early and rapid detection of potential pandemic IAV strains to prevent their spread. Recently, the increased pandemic potential of the avian-like swine H1N1 IAV A/swine/Guangdong/104/2013 has been suggested. The virus is infectious in humans and the general population seems to lack neutralizing antibodies against this virus. Here we present an in silico analysis that shows a strong human propensity of this swine virus further confirming its pandemic potential. We suggest mutations which would further enhance its human propensity. We also propose conserved antigenic determinants which could serve as a component of a prepandemic vaccine. The bioinformatics tool, which can be used to further monitor the evolution of swine influenza viruses towards a pandemic virus, are described here and are made publically available (http://www.vin.bg.ac.rs/180/tools/iav_ mon.php;http://www.biomedprotection.com/iav_mon.php).
T2  - PLOS One
T1  - Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China
VL  - 11
IS  - 11
DO  - 10.1371/journal.pone.0165451
ER  - 
@article{
author = "Veljković, Veljko and Veljković, Nevena V. and Paessler, Slobodan and Goeijenbier, Marco and Perović, Vladimir R. and Glišić, Sanja and Muller, Claude P.",
year = "2016",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1300",
abstract = "Influenza A virus (IAV) subtypes against which little or no pre-existing immunity exists in humans represent a serious threat to global public health. Monitoring of IAV in animal hosts is essential for early and rapid detection of potential pandemic IAV strains to prevent their spread. Recently, the increased pandemic potential of the avian-like swine H1N1 IAV A/swine/Guangdong/104/2013 has been suggested. The virus is infectious in humans and the general population seems to lack neutralizing antibodies against this virus. Here we present an in silico analysis that shows a strong human propensity of this swine virus further confirming its pandemic potential. We suggest mutations which would further enhance its human propensity. We also propose conserved antigenic determinants which could serve as a component of a prepandemic vaccine. The bioinformatics tool, which can be used to further monitor the evolution of swine influenza viruses towards a pandemic virus, are described here and are made publically available (http://www.vin.bg.ac.rs/180/tools/iav_ mon.php;http://www.biomedprotection.com/iav_mon.php).",
journal = "PLOS One",
title = "Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China",
volume = "11",
number = "11",
doi = "10.1371/journal.pone.0165451"
}
Veljković, V., Veljković, N. V., Paessler, S., Goeijenbier, M., Perović, V. R., Glišić, S.,& Muller, C. P. (2016). Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China.
PLOS One, 11(11).
https://doi.org/10.1371/journal.pone.0165451
Veljković V, Veljković NV, Paessler S, Goeijenbier M, Perović VR, Glišić S, Muller CP. Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China. PLOS One. 2016;11(11)
Veljković Veljko, Veljković Nevena V., Paessler Slobodan, Goeijenbier Marco, Perović Vladimir R., Glišić Sanja, Muller Claude P., "Predicted Enhanced Human Propensity of Current Avian-Like H1N1 Swine Influenza Virus from China" PLOS One, 11, no. 11 (2016),
https://doi.org/10.1371/journal.pone.0165451 .
2
2
1

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

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

(2016)

TY  - JOUR
AU  - Jiang, Yuxiang
AU  - Gemović, Branislava S.
AU  - Glišić, Sanja
AU  - Perović, Vladimir R.
AU  - Veljković, Veljko
AU  - Veljković, Nevena V.
PY  - 2016
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/1244
AB  - Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
T2  - Genome Biology
T1  - An expanded evaluation of protein function prediction methods shows an improvement in accuracy
VL  - 17
DO  - 10.1186/s13059-016-1037-6
ER  - 
@article{
author = "Jiang, Yuxiang and Gemović, Branislava S. and Glišić, Sanja and Perović, Vladimir R. and Veljković, Veljko and Veljković, Nevena V.",
year = "2016",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1244",
abstract = "Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.",
journal = "Genome Biology",
title = "An expanded evaluation of protein function prediction methods shows an improvement in accuracy",
volume = "17",
doi = "10.1186/s13059-016-1037-6"
}
Jiang, Y., Gemović, B. S., Glišić, S., Perović, V. R., Veljković, V.,& Veljković, N. V. (2016). An expanded evaluation of protein function prediction methods shows an improvement in accuracy.
Genome Biology, 17.
https://doi.org/10.1186/s13059-016-1037-6
Jiang Y, Gemović BS, Glišić S, Perović VR, Veljković V, Veljković NV. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biology. 2016;17
Jiang Yuxiang, Gemović Branislava S., Glišić Sanja, Perović Vladimir R., Veljković Veljko, Veljković Nevena V., "An expanded evaluation of protein function prediction methods shows an improvement in accuracy" Genome Biology, 17 (2016),
https://doi.org/10.1186/s13059-016-1037-6 .
32
238
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160

Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells

Srdić-Rajić, Tatjana; Nikolic, Katarina; Cavic, Milena; Đokić, Ivana; Gemović, Branislava S.; Perović, Vladimir R.; Veljković, Nevena V.

(2016)

TY  - JOUR
AU  - Srdić-Rajić, Tatjana
AU  - Nikolic, Katarina
AU  - Cavic, Milena
AU  - Đokić, Ivana
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
PY  - 2016
UR  - http://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.
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 Nikolic, Katarina and Cavic, Milena and Đokić, Ivana and Gemović, Branislava S. and Perović, Vladimir R. and Veljković, Nevena V.",
year = "2016",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/884",
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.",
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., Nikolic, K., Cavic, M., 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.
European Journal of Pharmaceutical Sciences, 81, 172-180.
https://doi.org/10.1016/j.ejps.2015.10.017
Srdić-Rajić T, Nikolic K, Cavic M, Đokić I, Gemović BS, Perović VR, Veljković NV. Rilmenidine suppresses proliferation and promotes apoptosis via the mitochondrial pathway in human leukemic K562 cells. European Journal of Pharmaceutical Sciences. 2016;81:172-180
Srdić-Rajić Tatjana, Nikolic Katarina, Cavic Milena, 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" European Journal of Pharmaceutical Sciences, 81 (2016):172-180,
https://doi.org/10.1016/j.ejps.2015.10.017 .
7
9
7
10

A combined ligand- and structure-based approach for the identification of rilmenidine-derived compounds which synergize the antitumor effects of doxorubicin

Vucicevic, 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; Nikolic, Katarina; Radi, Marco; Veljković, Nevena V.

(2016)

TY  - JOUR
AU  - Vucicevic, 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  - Nikolic, Katarina
AU  - Radi, Marco
AU  - Veljković, Nevena V.
PY  - 2016
UR  - http://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 = "Vucicevic, 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 Nikolic, Katarina and Radi, Marco and Veljković, Nevena V.",
year = "2016",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1110",
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"
}
Vucicevic, 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., Nikolic, K., 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.
Bioorganic and Medicinal Chemistry, 24(14), 3174-3183.
https://doi.org/10.1016/j.bmc.2016.05.043
Vucicevic J, Srdić-Rajić T, Pieroni M, Laurila JMM, Perović VR, Tassini S, Azzali E, Costantino G, Glišić S, Agbaba D, Scheinin M, Nikolic K, 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. Bioorganic and Medicinal Chemistry. 2016;24(14):3174-3183
Vucicevic 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, Nikolic Katarina, 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" Bioorganic and Medicinal Chemistry, 24, no. 14 (2016):3174-3183,
https://doi.org/10.1016/j.bmc.2016.05.043 .
2
9
10
8

Pomegranate (Punica granatum): a natural source for the development of therapeutic compositions of food supplements with anticancer activities based on electron acceptor molecular characteristics

Veljković, Veljko; Glišić, Sanja; Perović, Vladimir R.; Veljković, Nevena V.; Nicolson, Garth L.

(2016)

TY  - JOUR
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Perović, Vladimir R.
AU  - Veljković, Nevena V.
AU  - Nicolson, Garth L.
PY  - 2016
UR  - http://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
ER  - 
@article{
author = "Veljković, Veljko and Glišić, Sanja and Perović, Vladimir R. and Veljković, Nevena V. and Nicolson, Garth L.",
year = "2016",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/1372",
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"
}
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.
Functional Foods in Health and Disease, 6(12), 769-787.
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. Functional Foods in Health and Disease. 2016;6(12):769-787
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" Functional Foods in Health and Disease, 6, no. 12 (2016):769-787
1

CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results

Živković, Maja; Đurić, Tamara; Stojković, Ljiljana S.; Jovanović, Ivan G.; Končar, Igor; Davidovic, Lazar; Veljković, Nevena V.; Alavantić, Dragan; Stanković, Aleksandra

(2015)

TY  - JOUR
AU  - Živković, Maja
AU  - Đurić, Tamara
AU  - Stojković, Ljiljana S.
AU  - Jovanović, Ivan G.
AU  - Končar, Igor
AU  - Davidovic, Lazar
AU  - Veljković, Nevena V.
AU  - Alavantić, Dragan
AU  - Stanković, Aleksandra
PY  - 2015
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/481
AB  - Aim: Chemokine CXC ligand 16 (CXCL16) has chemoattractive, adhesive and scavenging properties and may play a role in the formation of atherosclerotic lesions. However, studies of CXCL16 polymorphisms in patients with atherosclerosis are scarce. The missense polymorphisms I123T and A181V are potentially important factors in the regulation of presentation and shedding of the CXCL16 chemokine domain. The aim of this study was to analyze the association between I123T and A181V polymorphism haplotypes and the accumulation of carotid plaque as well as the effect of the haplotype on the CXCL16 mRNA expression in carotid plaques in patients with advanced atherosclerosis. Additionally, we performed a bioinformatic prediction analysis of the impact of CXCL16 protein sequence variation on CXCL16-CXCR6 interactions and analyzed the soluble CXCL16 plasma levels according to the CXCL16 haplotype. Methods: This study evaluated a total of 733 participants, including 283 controls and 450 patients with carotid atherosclerosis (CA) undergoing endarterectomy. Analyses of the polymorphisms and the gene expression were performed using real-time PCR. The soluble CXCL16 levels were measured with ELISA. Results: The missense allele haplotype, T123V181, was found to be significantly and independently associated with the occurrence of CA plaque (OR=1.27; 1.02-1.57, p=0.03). This haplotype was predicted to significantly change the CXCL16-CXCR6 interaction, compared to I123A181. Neither the CXCL16 mRNA expression in the human plaques nor the soluble CXCL16 plasma levels differed according to the haplotype. Conclusions: These results indicate that the CXCL16 T123V181 haplotype is a moderate genetic risk factor for the development of carotid plaque. Further functional and replication studies are needed to clarify the mechanisms by which this combination of alleles promotes advanced CA and validate its impact on disease progression.
T2  - Journal of Atherosclerosis and Thrombosis
T1  - CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results
VL  - 22
IS  - 1
SP  - 10
EP  - 20
DO  - 10.5551/jat.24299
ER  - 
@article{
author = "Živković, Maja and Đurić, Tamara and Stojković, Ljiljana S. and Jovanović, Ivan G. and Končar, Igor and Davidovic, Lazar and Veljković, Nevena V. and Alavantić, Dragan and Stanković, Aleksandra",
year = "2015",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/481",
abstract = "Aim: Chemokine CXC ligand 16 (CXCL16) has chemoattractive, adhesive and scavenging properties and may play a role in the formation of atherosclerotic lesions. However, studies of CXCL16 polymorphisms in patients with atherosclerosis are scarce. The missense polymorphisms I123T and A181V are potentially important factors in the regulation of presentation and shedding of the CXCL16 chemokine domain. The aim of this study was to analyze the association between I123T and A181V polymorphism haplotypes and the accumulation of carotid plaque as well as the effect of the haplotype on the CXCL16 mRNA expression in carotid plaques in patients with advanced atherosclerosis. Additionally, we performed a bioinformatic prediction analysis of the impact of CXCL16 protein sequence variation on CXCL16-CXCR6 interactions and analyzed the soluble CXCL16 plasma levels according to the CXCL16 haplotype. Methods: This study evaluated a total of 733 participants, including 283 controls and 450 patients with carotid atherosclerosis (CA) undergoing endarterectomy. Analyses of the polymorphisms and the gene expression were performed using real-time PCR. The soluble CXCL16 levels were measured with ELISA. Results: The missense allele haplotype, T123V181, was found to be significantly and independently associated with the occurrence of CA plaque (OR=1.27; 1.02-1.57, p=0.03). This haplotype was predicted to significantly change the CXCL16-CXCR6 interaction, compared to I123A181. Neither the CXCL16 mRNA expression in the human plaques nor the soluble CXCL16 plasma levels differed according to the haplotype. Conclusions: These results indicate that the CXCL16 T123V181 haplotype is a moderate genetic risk factor for the development of carotid plaque. Further functional and replication studies are needed to clarify the mechanisms by which this combination of alleles promotes advanced CA and validate its impact on disease progression.",
journal = "Journal of Atherosclerosis and Thrombosis",
title = "CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results",
volume = "22",
number = "1",
pages = "10-20",
doi = "10.5551/jat.24299"
}
Živković, M., Đurić, T., Stojković, L. S., Jovanović, I. G., Končar, I., Davidovic, L., Veljković, N. V., Alavantić, D.,& Stanković, A. (2015). CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results.
Journal of Atherosclerosis and Thrombosis, 22(1), 10-20.
https://doi.org/10.5551/jat.24299
Živković M, Đurić T, Stojković LS, Jovanović IG, Končar I, Davidovic L, Veljković NV, Alavantić D, Stanković A. CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results. Journal of Atherosclerosis and Thrombosis. 2015;22(1):10-20
Živković Maja, Đurić Tamara, Stojković Ljiljana S., Jovanović Ivan G., Končar Igor, Davidovic Lazar, Veljković Nevena V., Alavantić Dragan, Stanković Aleksandra, "CXCL16 Haplotypes in Patients with Human Carotid Atherosclerosis: Preliminary Results" Journal of Atherosclerosis and Thrombosis, 22, no. 1 (2015):10-20,
https://doi.org/10.5551/jat.24299 .
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In silico analysis suggests interaction between Ebola virus and the extracellular matrix

Veljković, Veljko; Glišić, Sanja; Muller, Claude P.; Scotch, Matthew; Branch, Donald R.; Perović, Vladimir R.; Senćanski, Milan V.; Veljković, Nevena V.; Colombatti, Alfonso

(2015)

TY  - JOUR
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Muller, Claude P.
AU  - Scotch, Matthew
AU  - Branch, Donald R.
AU  - Perović, Vladimir R.
AU  - Senćanski, Milan V.
AU  - Veljković, Nevena V.
AU  - Colombatti, Alfonso
PY  - 2015
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/423
AB  - The worst Ebola virus (EV) outbreak in history has hit Liberia, Sierra Leone and Guinea hardest and the trend lines in this crisis are grave, and now represents a global public health threat concern. Limited therapeutic and/or prophylactic options are available for people suffering from Ebola virus disease (EVD) and further complicate the situation. Previous studies suggested that the EV glycoprotein (GP) is the main determinant causing structural damage of endothelial cells that triggers the hemorrhagic diathesis, but molecular mechanisms underlying this phenomenon remains elusive. Using the informational spectrum method (ISM), a virtual spectroscopy method for analysis of the protein-protein interactions, the interaction of GP with endothelial extracellular matrix (ECM) was investigated. Presented results of this in silico study suggest that Elastin Microfibril Interface Located Proteins (EMILINs) are involved in interaction between GP and ECM. This finding could contribute to a better understanding of EV/endothelium interaction and its role in pathogenesis, prevention and therapy of EVD.
T2  - Frontiers in Microbiology
T1  - In silico analysis suggests interaction between Ebola virus and the extracellular matrix
VL  - 6
DO  - 10.3389/fmicb.2015.00135
ER  - 
@article{
author = "Veljković, Veljko and Glišić, Sanja and Muller, Claude P. and Scotch, Matthew and Branch, Donald R. and Perović, Vladimir R. and Senćanski, Milan V. and Veljković, Nevena V. and Colombatti, Alfonso",
year = "2015",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/423",
abstract = "The worst Ebola virus (EV) outbreak in history has hit Liberia, Sierra Leone and Guinea hardest and the trend lines in this crisis are grave, and now represents a global public health threat concern. Limited therapeutic and/or prophylactic options are available for people suffering from Ebola virus disease (EVD) and further complicate the situation. Previous studies suggested that the EV glycoprotein (GP) is the main determinant causing structural damage of endothelial cells that triggers the hemorrhagic diathesis, but molecular mechanisms underlying this phenomenon remains elusive. Using the informational spectrum method (ISM), a virtual spectroscopy method for analysis of the protein-protein interactions, the interaction of GP with endothelial extracellular matrix (ECM) was investigated. Presented results of this in silico study suggest that Elastin Microfibril Interface Located Proteins (EMILINs) are involved in interaction between GP and ECM. This finding could contribute to a better understanding of EV/endothelium interaction and its role in pathogenesis, prevention and therapy of EVD.",
journal = "Frontiers in Microbiology",
title = "In silico analysis suggests interaction between Ebola virus and the extracellular matrix",
volume = "6",
doi = "10.3389/fmicb.2015.00135"
}
Veljković, V., Glišić, S., Muller, C. P., Scotch, M., Branch, D. R., Perović, V. R., Senćanski, M. V., Veljković, N. V.,& Colombatti, A. (2015). In silico analysis suggests interaction between Ebola virus and the extracellular matrix.
Frontiers in Microbiology, 6.
https://doi.org/10.3389/fmicb.2015.00135
Veljković V, Glišić S, Muller CP, Scotch M, Branch DR, Perović VR, Senćanski MV, Veljković NV, Colombatti A. In silico analysis suggests interaction between Ebola virus and the extracellular matrix. Frontiers in Microbiology. 2015;6
Veljković Veljko, Glišić Sanja, Muller Claude P., Scotch Matthew, Branch Donald R., Perović Vladimir R., Senćanski Milan V., Veljković Nevena V., Colombatti Alfonso, "In silico analysis suggests interaction between Ebola virus and the extracellular matrix" Frontiers in Microbiology, 6 (2015),
https://doi.org/10.3389/fmicb.2015.00135 .
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11

Natural Products as Promising Therapeutics for Treatment of Influenza Disease

Senćanski, Milan V.; Radosevic, Draginja; Perović, Vladimir R.; Gemović, Branislava S.; Stanojevic, Maja; Veljković, Nevena V.; Glišić, Sanja

(2015)

TY  - JOUR
AU  - Senćanski, Milan V.
AU  - Radosevic, Draginja
AU  - Perović, Vladimir R.
AU  - Gemović, Branislava S.
AU  - Stanojevic, Maja
AU  - Veljković, Nevena V.
AU  - Glišić, Sanja
PY  - 2015
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/806
AB  - The influenza virus represents a permanent global health threat because it circulates not only within but also between numerous host populations, thereby frequently causing unexpected outbreaks in animals and humans with a generally unpredictable course of disease and epidemiology. Conventional influenza therapy is directed against the viral neuraminidase protein, which promotes virus release from infected cells, and the viral ion channel M2, which facilitates viral uncoating. However, these drugs, albeit effective, have a major drawback: their targets are of a highly variable sequence. As a consequence, the virus can readily acquire resistance by mutating the drug targets. Indeed, most seasonal A/H1N1 viruses and the 2009 H1N1 virus are resistant to M2 inhibitors, and a significant proportion of the seasonal A/H1N1 viruses are resistant to the neuraminidase inhibitor oseltamivir. Development of new effective drugs for treatment of disease during the regular influenza seasons and the possible influenza pandemic represents an important goal. The results presented here point out natural products as a promising source of low toxic and widely accessible drug candidates for treatment of the influenza disease. Natural products combined with new therapeutic targets and drug repurposing techniques, which accelerate development of new drugs, serve as an important platform for development of new influenza therapeutics.
T2  - Current Pharmaceutical Design
T1  - Natural Products as Promising Therapeutics for Treatment of Influenza Disease
VL  - 21
IS  - 38
SP  - 5573
EP  - 5588
DO  - 10.2174/1381612821666151002113426
ER  - 
@article{
author = "Senćanski, Milan V. and Radosevic, Draginja and Perović, Vladimir R. and Gemović, Branislava S. and Stanojevic, Maja and Veljković, Nevena V. and Glišić, Sanja",
year = "2015",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/806",
abstract = "The influenza virus represents a permanent global health threat because it circulates not only within but also between numerous host populations, thereby frequently causing unexpected outbreaks in animals and humans with a generally unpredictable course of disease and epidemiology. Conventional influenza therapy is directed against the viral neuraminidase protein, which promotes virus release from infected cells, and the viral ion channel M2, which facilitates viral uncoating. However, these drugs, albeit effective, have a major drawback: their targets are of a highly variable sequence. As a consequence, the virus can readily acquire resistance by mutating the drug targets. Indeed, most seasonal A/H1N1 viruses and the 2009 H1N1 virus are resistant to M2 inhibitors, and a significant proportion of the seasonal A/H1N1 viruses are resistant to the neuraminidase inhibitor oseltamivir. Development of new effective drugs for treatment of disease during the regular influenza seasons and the possible influenza pandemic represents an important goal. The results presented here point out natural products as a promising source of low toxic and widely accessible drug candidates for treatment of the influenza disease. Natural products combined with new therapeutic targets and drug repurposing techniques, which accelerate development of new drugs, serve as an important platform for development of new influenza therapeutics.",
journal = "Current Pharmaceutical Design",
title = "Natural Products as Promising Therapeutics for Treatment of Influenza Disease",
volume = "21",
number = "38",
pages = "5573-5588",
doi = "10.2174/1381612821666151002113426"
}
Senćanski, M. V., Radosevic, D., Perović, V. R., Gemović, B. S., Stanojevic, M., Veljković, N. V.,& Glišić, S. (2015). Natural Products as Promising Therapeutics for Treatment of Influenza Disease.
Current Pharmaceutical Design, 21(38), 5573-5588.
https://doi.org/10.2174/1381612821666151002113426
Senćanski MV, Radosevic D, Perović VR, Gemović BS, Stanojevic M, Veljković NV, Glišić S. Natural Products as Promising Therapeutics for Treatment of Influenza Disease. Current Pharmaceutical Design. 2015;21(38):5573-5588
Senćanski Milan V., Radosevic Draginja, Perović Vladimir R., Gemović Branislava S., Stanojevic Maja, Veljković Nevena V., Glišić Sanja, "Natural Products as Promising Therapeutics for Treatment of Influenza Disease" Current Pharmaceutical Design, 21, no. 38 (2015):5573-5588,
https://doi.org/10.2174/1381612821666151002113426 .
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Improving attrition rates in Ebola virus drug discovery

Glišić, Sanja; Paessler, Slobodan; Veljković, Nevena V.; Perović, Vladimir R.; Prljić, Jelena; Veljković, Veljko

(2015)

TY  - JOUR
AU  - Glišić, Sanja
AU  - Paessler, Slobodan
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
AU  - Prljić, Jelena
AU  - Veljković, Veljko
PY  - 2015
UR  - http://vinar.vin.bg.ac.rs/handle/123456789/709
AB  - Introduction: The Ebola 2014/2015 outbreak has had devastating effects on the people living in West Africa. The spread of the disease in endemic countries and the potential introduction of sporadic cases in other continents points out the global health threat of Ebola virus disease (EVD). Despite the urgent need for treating EVD, there are no approved treatments. Given the lack of treatments available, alternative therapeutic strategies have had to be used. Areas covered: This article summarizes the unregistered therapeutics that were used to treat patients during the Ebola 2014/2015 outbreak, in addition to approaches used for the selection of candidate drugs. The article also proposes potential theoretical criterion for use in virtual screening of molecular libraries for candidate Ebola drugs. Expert opinion: In the absence of approved therapeutics for EVD, experimental drugs have had to be used. The repurposing of approved drugs for the treatment of EVD, as an alternative therapeutic strategy, has also been suggested. Screening in vitro- and in sllico-approved drugs revealed several promising candidates but further testing is required to test their efficacy. All these therapeutic approaches are, however, only short-term solutions and there is still an urgent need for the development of specific drugs for the current and future outbreaks.
T2  - Expert Opinion on Drug Discovery
T1  - Improving attrition rates in Ebola virus drug discovery
VL  - 10
IS  - 9
SP  - 1025
EP  - 1032
DO  - 10.1517/17460441.2015.1062872
ER  - 
@article{
author = "Glišić, Sanja and Paessler, Slobodan and Veljković, Nevena V. and Perović, Vladimir R. and Prljić, Jelena and Veljković, Veljko",
year = "2015",
url = "http://vinar.vin.bg.ac.rs/handle/123456789/709",
abstract = "Introduction: The Ebola 2014/2015 outbreak has had devastating effects on the people living in West Africa. The spread of the disease in endemic countries and the potential introduction of sporadic cases in other continents points out the global health threat of Ebola virus disease (EVD). Despite the urgent need for treating EVD, there are no approved treatments. Given the lack of treatments available, alternative therapeutic strategies have had to be used. Areas covered: This article summarizes the unregistered therapeutics that were used to treat patients during the Ebola 2014/2015 outbreak, in addition to approaches used for the selection of candidate drugs. The article also proposes potential theoretical criterion for use in virtual screening of molecular libraries for candidate Ebola drugs. Expert opinion: In the absence of approved therapeutics for EVD, experimental drugs have had to be used. The repurposing of approved drugs for the treatment of EVD, as an alternative therapeutic strategy, has also been suggested. Screening in vitro- and in sllico-approved drugs revealed several promising candidates but further testing is required to test their efficacy. All these therapeutic approaches are, however, only short-term solutions and there is still an urgent need for the development of specific drugs for the current and future outbreaks.",
journal = "Expert Opinion on Drug Discovery",
title = "Improving attrition rates in Ebola virus drug discovery",
volume = "10",
number = "9",
pages = "1025-1032",
doi = "10.1517/17460441.2015.1062872"
}
Glišić, S., Paessler, S., Veljković, N. V., Perović, V. R., Prljić, J.,& Veljković, V. (2015). Improving attrition rates in Ebola virus drug discovery.
Expert Opinion on Drug Discovery, 10(9), 1025-1032.
https://doi.org/10.1517/17460441.2015.1062872
Glišić S, Paessler S, Veljković NV, Perović VR, Prljić J, Veljković V. Improving attrition rates in Ebola virus drug discovery. Expert Opinion on Drug Discovery. 2015;10(9):1025-1032
Glišić Sanja, Paessler Slobodan, Veljković Nevena V., Perović Vladimir R., Prljić Jelena, Veljković Veljko, "Improving attrition rates in Ebola virus drug discovery" Expert Opinion on Drug Discovery, 10, no. 9 (2015):1025-1032,
https://doi.org/10.1517/17460441.2015.1062872 .
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