TY  - CONF
AU  - Drljača, Tamara
AU  - Stevanović, Kristina
AU  - Radošević, Draginja
AU  - Milićević, Jelena S.
AU  - Veljković, Nevena
AU  - Glišić, Sanja
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/12243
AB  - Peroxisome proliferator-activated receptor alpha (PPARα) is crucial in regulating lipid metabolism. Clinically, PPARα is significant as a possible therapeutic target for a variety of human disorders, including cardiovascular, neurological, and metabolic syndromes. The wide range of natural compounds provides great opportunities for new approaches in targeting PPARα. Carotenoids, a large class of natural compounds, have been recognized as PPARα agonists. Tomatoes (Solanum lycopersicum) are one of the most widely grown crops in the world and contain compounds that improve lipid metabolism. Since there is no data on tomato carotenoids as PPARα agonists in this study, we focused on searching carotenoids from tomatoes as possible PPARα agonists. The Solanum lycopersicum carotenoids from Carotenoids Database were in silico screened using a combined protocol with the Electron-Ion Interaction Potential/Average Quasi Valence Number (EIIP/AQVN) filter and molecular docking to find the most promising candidate compounds. The best resulting compounds may have the promise to be further developed as candidates for PPARα agonists.
PB  - Kragujevac : Institute for Information Technologies, University of Kragujevac
C3  - ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics : Book of Proceedings
T1  - In silico screening of Solanum lycopersicum carotenoids from Carotenoids Database for candidates PPARα agonists
SP  - 605
EP  - 608
DO  - 10.46793/ICCBI23.605D
ER  - 

@conference{
author = "Drljača, Tamara and Stevanović, Kristina and Radošević, Draginja and Milićević, Jelena S. and Veljković, Nevena and Glišić, Sanja",
year = "2023",
abstract = "Peroxisome proliferator-activated receptor alpha (PPARα) is crucial in regulating lipid metabolism. Clinically, PPARα is significant as a possible therapeutic target for a variety of human disorders, including cardiovascular, neurological, and metabolic syndromes. The wide range of natural compounds provides great opportunities for new approaches in targeting PPARα. Carotenoids, a large class of natural compounds, have been recognized as PPARα agonists. Tomatoes (Solanum lycopersicum) are one of the most widely grown crops in the world and contain compounds that improve lipid metabolism. Since there is no data on tomato carotenoids as PPARα agonists in this study, we focused on searching carotenoids from tomatoes as possible PPARα agonists. The Solanum lycopersicum carotenoids from Carotenoids Database were in silico screened using a combined protocol with the Electron-Ion Interaction Potential/Average Quasi Valence Number (EIIP/AQVN) filter and molecular docking to find the most promising candidate compounds. The best resulting compounds may have the promise to be further developed as candidates for PPARα agonists.",
publisher = "Kragujevac : Institute for Information Technologies, University of Kragujevac",
journal = "ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics : Book of Proceedings",
title = "In silico screening of Solanum lycopersicum carotenoids from Carotenoids Database for candidates PPARα agonists",
pages = "605-608",
doi = "10.46793/ICCBI23.605D"
}

Drljača, T., Stevanović, K., Radošević, D., Milićević, J. S., Veljković, N.,& Glišić, S.. (2023). In silico screening of Solanum lycopersicum carotenoids from Carotenoids Database for candidates PPARα agonists. in ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics : Book of Proceedings
Kragujevac : Institute for Information Technologies, University of Kragujevac., 605-608.
https://doi.org/10.46793/ICCBI23.605D

Drljača T, Stevanović K, Radošević D, Milićević JS, Veljković N, Glišić S. In silico screening of Solanum lycopersicum carotenoids from Carotenoids Database for candidates PPARα agonists. in ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics : Book of Proceedings. 2023;:605-608.
doi:10.46793/ICCBI23.605D .

Drljača, Tamara, Stevanović, Kristina, Radošević, Draginja, Milićević, Jelena S., Veljković, Nevena, Glišić, Sanja, "In silico screening of Solanum lycopersicum carotenoids from Carotenoids Database for candidates PPARα agonists" in ICCBIKG 2023 : 2nd International Conference on Chemo and Bioinformatics : Book of Proceedings (2023):605-608,
https://doi.org/10.46793/ICCBI23.605D . .

TY  - JOUR
AU  - Gauffin, Oskar
AU  - Brand, Judith S.
AU  - Vidlin, Sara Hedfors
AU  - Sartori, Daniele
AU  - Asikainen, Suvi
AU  - Catala, Martí
AU  - Chalabi, Etir
AU  - Dedman, Daniel
AU  - Danilović, Ana
AU  - Duarte-Salles, Talita
AU  - García Morales, Maria Teresa
AU  - Hiltunen, Saara
AU  - Jödicke, Annika M.
AU  - Lazarević, Milan
AU  - Mayer, Miguel A.
AU  - Miladinović, Jelena
AU  - Mitchell, Joseph
AU  - Pistillo, Andrea
AU  - Ramírez-Anguita, Juan Manuel
AU  - Reyes, Carlen
AU  - Rudolph, Annette
AU  - Sandberg, Lovisa
AU  - Savage, Ruth
AU  - Schuemie, Martijn
AU  - Spasić, Dimitrije
AU  - Trinh, Nhung T. H.
AU  - Veljković, Nevena V.
AU  - Vujovic, Ankica
AU  - de Wilde, Marcel
AU  - Zekarias, Alem
AU  - Rijnbeek, Peter
AU  - Ryan, Patrick
AU  - Prieto-Alhambra, Daniel
AU  - Noren, G. Niklas
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11727
AB  - Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.
T2  - Drug Safety
T1  - Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study
DO  - 10.1007/s40264-023-01353-w
ER  - 

@article{
author = "Gauffin, Oskar and Brand, Judith S. and Vidlin, Sara Hedfors and Sartori, Daniele and Asikainen, Suvi and Catala, Martí and Chalabi, Etir and Dedman, Daniel and Danilović, Ana and Duarte-Salles, Talita and García Morales, Maria Teresa and Hiltunen, Saara and Jödicke, Annika M. and Lazarević, Milan and Mayer, Miguel A. and Miladinović, Jelena and Mitchell, Joseph and Pistillo, Andrea and Ramírez-Anguita, Juan Manuel and Reyes, Carlen and Rudolph, Annette and Sandberg, Lovisa and Savage, Ruth and Schuemie, Martijn and Spasić, Dimitrije and Trinh, Nhung T. H. and Veljković, Nevena V. and Vujovic, Ankica and de Wilde, Marcel and Zekarias, Alem and Rijnbeek, Peter and Ryan, Patrick and Prieto-Alhambra, Daniel and Noren, G. Niklas",
year = "2023",
abstract = "Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.",
journal = "Drug Safety",
title = "Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study",
doi = "10.1007/s40264-023-01353-w"
}

Gauffin, O., Brand, J. S., Vidlin, S. H., Sartori, D., Asikainen, S., Catala, M., Chalabi, E., Dedman, D., Danilović, A., Duarte-Salles, T., García Morales, M. T., Hiltunen, S., Jödicke, A. M., Lazarević, M., Mayer, M. A., Miladinović, J., Mitchell, J., Pistillo, A., Ramírez-Anguita, J. M., Reyes, C., Rudolph, A., Sandberg, L., Savage, R., Schuemie, M., Spasić, D., Trinh, N. T. H., Veljković, N. V., Vujovic, A., de Wilde, M., Zekarias, A., Rijnbeek, P., Ryan, P., Prieto-Alhambra, D.,& Noren, G. N.. (2023). Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study. in Drug Safety.
https://doi.org/10.1007/s40264-023-01353-w

Gauffin O, Brand JS, Vidlin SH, Sartori D, Asikainen S, Catala M, Chalabi E, Dedman D, Danilović A, Duarte-Salles T, García Morales MT, Hiltunen S, Jödicke AM, Lazarević M, Mayer MA, Miladinović J, Mitchell J, Pistillo A, Ramírez-Anguita JM, Reyes C, Rudolph A, Sandberg L, Savage R, Schuemie M, Spasić D, Trinh NTH, Veljković NV, Vujovic A, de Wilde M, Zekarias A, Rijnbeek P, Ryan P, Prieto-Alhambra D, Noren GN. Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study. in Drug Safety. 2023;.
doi:10.1007/s40264-023-01353-w .

Gauffin, Oskar, Brand, Judith S., Vidlin, Sara Hedfors, Sartori, Daniele, Asikainen, Suvi, Catala, Martí, Chalabi, Etir, Dedman, Daniel, Danilović, Ana, Duarte-Salles, Talita, García Morales, Maria Teresa, Hiltunen, Saara, Jödicke, Annika M., Lazarević, Milan, Mayer, Miguel A., Miladinović, Jelena, Mitchell, Joseph, Pistillo, Andrea, Ramírez-Anguita, Juan Manuel, Reyes, Carlen, Rudolph, Annette, Sandberg, Lovisa, Savage, Ruth, Schuemie, Martijn, Spasić, Dimitrije, Trinh, Nhung T. H., Veljković, Nevena V., Vujovic, Ankica, de Wilde, Marcel, Zekarias, Alem, Rijnbeek, Peter, Ryan, Patrick, Prieto-Alhambra, Daniel, Noren, G. Niklas, "Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study" in Drug Safety (2023),
https://doi.org/10.1007/s40264-023-01353-w . .

TY  - JOUR
AU  - Quaglia, Federica
AU  - Mészáros, Balint
AU  - Salladini, Edoardo
AU  - Hatos, Andras
AU  - Pancsa, Rita
AU  - Davidović, Radoslav S.
AU  - Veljković, Nevena V.
PY  - 2022
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10187
AB  - The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
T2  - Nucleic acids research
T1  - DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation
VL  - 50
IS  - D1
SP  - D480
EP  - D487
DO  - 10.1093/nar/gkab1082
ER  - 

@article{
author = "Quaglia, Federica and Mészáros, Balint and Salladini, Edoardo and Hatos, Andras and Pancsa, Rita and Davidović, Radoslav S. and Veljković, Nevena V.",
year = "2022",
abstract = "The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.",
journal = "Nucleic acids research",
title = "DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation",
volume = "50",
number = "D1",
pages = "D480-D487",
doi = "10.1093/nar/gkab1082"
}

Quaglia, F., Mészáros, B., Salladini, E., Hatos, A., Pancsa, R., Davidović, R. S.,& Veljković, N. V.. (2022). DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation. in Nucleic acids research, 50(D1), D480-D487.
https://doi.org/10.1093/nar/gkab1082

Quaglia F, Mészáros B, Salladini E, Hatos A, Pancsa R, Davidović RS, Veljković NV. DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation. in Nucleic acids research. 2022;50(D1):D480-D487.
doi:10.1093/nar/gkab1082 .

Quaglia, Federica, Mészáros, Balint, Salladini, Edoardo, Hatos, Andras, Pancsa, Rita, Davidović, Radoslav S., Veljković, Nevena V., "DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation" in Nucleic acids research, 50, no. D1 (2022):D480-D487,
https://doi.org/10.1093/nar/gkab1082 . .

TY  - JOUR
AU  - Milin-Lazović, Jelena
AU  - Madžarević, Petar
AU  - Rajović, Nina
AU  - Đorđević, Vladimir
AU  - Milić, Nikola
AU  - Pavlović, Sonja
AU  - Veljković, Nevena V.
AU  - Milić, Nataša M.
AU  - Radenković, Dejan
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9861
AB  - Introduction: The analysis of cell-free DNA (cfDNA) for genetic abnormalities is a promising new approach for the diagnosis and prognosis of pancreatic cancer patients. Insights into the molecular characteristics of pancreatic cancer may provide valuable information, leading to its earlier detection and the development of targeted therapies. Material and Methods: We conducted a systematic review and a meta-analysis of studies that reported cfDNA in pancreatic ductal adenocarcinoma (PDAC). The studies were considered eligible if they included patients with PDAC, if they had blood tests for cfDNA/ctDNA, and if they analyzed the prognostic value of cfDNA/ctDNA for patients’ survival. The studies published before 22 October 2020 were identified through the PubMED, EMBASE, Web of Science and Cochrane Library databases. The assessed outcomes were the overall (OS) and progression-free survival (PFS), expressed as the log hazard ratio (HR) and standard error (SE). The summary of the HR effect size was estimated by pooling the individual trial results using the Review Manager, version 5.3, Cochrane Collaboration. The heterogeneity was assessed using the Cochran Q test and I2 statistic. Results: In total, 48 studies were included in the qualitative review, while 44 were assessed in the quantitative synthesis, with the total number of patients included being 3524. Overall negative impacts of cfDNA and KRAS mutations on OS and PFS in PDAC (HR = 2.42, 95% CI: 1.95–2.99 and HR = 2.46, 95% CI: 2.01–3.00, respectively) were found. The subgroup analysis of the locally advanced and metastatic disease presented similar results (HR = 2.51, 95% CI: 1.90–3.31). In the studies assessing the pre-treatment presence of KRAS, there was a moderate to high degree of heterogeneity (I2 = 87% and I2 = 48%, for OS and PFS, respectively), which was remarkably decreased in the analysis of the studies measuring post-treatment KRAS (I2 = 24% and I2 = 0%, for OS and PFS, respectively). The patients who were KRAS positive before but KRAS negative after treatment had a better prognosis than the persistently KRAS-positive patients (HR = 5.30, 95% CI: 1.02–27.63). Conclusion: The assessment of KRAS mutation by liquid biopsy can be considered as an additional tool for the estimation of the disease course and outcome in PDAC patients.
T2  - Cancers
T1  - Meta-analysis of circulating cell-free dna’s role in the prognosis of pancreatic cancer
VL  - 13
IS  - 14
SP  - 3378
DO  - 10.3390/cancers13143378
ER  - 

@article{
author = "Milin-Lazović, Jelena and Madžarević, Petar and Rajović, Nina and Đorđević, Vladimir and Milić, Nikola and Pavlović, Sonja and Veljković, Nevena V. and Milić, Nataša M. and Radenković, Dejan",
year = "2021",
abstract = "Introduction: The analysis of cell-free DNA (cfDNA) for genetic abnormalities is a promising new approach for the diagnosis and prognosis of pancreatic cancer patients. Insights into the molecular characteristics of pancreatic cancer may provide valuable information, leading to its earlier detection and the development of targeted therapies. Material and Methods: We conducted a systematic review and a meta-analysis of studies that reported cfDNA in pancreatic ductal adenocarcinoma (PDAC). The studies were considered eligible if they included patients with PDAC, if they had blood tests for cfDNA/ctDNA, and if they analyzed the prognostic value of cfDNA/ctDNA for patients’ survival. The studies published before 22 October 2020 were identified through the PubMED, EMBASE, Web of Science and Cochrane Library databases. The assessed outcomes were the overall (OS) and progression-free survival (PFS), expressed as the log hazard ratio (HR) and standard error (SE). The summary of the HR effect size was estimated by pooling the individual trial results using the Review Manager, version 5.3, Cochrane Collaboration. The heterogeneity was assessed using the Cochran Q test and I2 statistic. Results: In total, 48 studies were included in the qualitative review, while 44 were assessed in the quantitative synthesis, with the total number of patients included being 3524. Overall negative impacts of cfDNA and KRAS mutations on OS and PFS in PDAC (HR = 2.42, 95% CI: 1.95–2.99 and HR = 2.46, 95% CI: 2.01–3.00, respectively) were found. The subgroup analysis of the locally advanced and metastatic disease presented similar results (HR = 2.51, 95% CI: 1.90–3.31). In the studies assessing the pre-treatment presence of KRAS, there was a moderate to high degree of heterogeneity (I2 = 87% and I2 = 48%, for OS and PFS, respectively), which was remarkably decreased in the analysis of the studies measuring post-treatment KRAS (I2 = 24% and I2 = 0%, for OS and PFS, respectively). The patients who were KRAS positive before but KRAS negative after treatment had a better prognosis than the persistently KRAS-positive patients (HR = 5.30, 95% CI: 1.02–27.63). Conclusion: The assessment of KRAS mutation by liquid biopsy can be considered as an additional tool for the estimation of the disease course and outcome in PDAC patients.",
journal = "Cancers",
title = "Meta-analysis of circulating cell-free dna’s role in the prognosis of pancreatic cancer",
volume = "13",
number = "14",
pages = "3378",
doi = "10.3390/cancers13143378"
}

Milin-Lazović, J., Madžarević, P., Rajović, N., Đorđević, V., Milić, N., Pavlović, S., Veljković, N. V., Milić, N. M.,& Radenković, D.. (2021). Meta-analysis of circulating cell-free dna’s role in the prognosis of pancreatic cancer. in Cancers, 13(14), 3378.
https://doi.org/10.3390/cancers13143378

Milin-Lazović J, Madžarević P, Rajović N, Đorđević V, Milić N, Pavlović S, Veljković NV, Milić NM, Radenković D. Meta-analysis of circulating cell-free dna’s role in the prognosis of pancreatic cancer. in Cancers. 2021;13(14):3378.
doi:10.3390/cancers13143378 .

Milin-Lazović, Jelena, Madžarević, Petar, Rajović, Nina, Đorđević, Vladimir, Milić, Nikola, Pavlović, Sonja, Veljković, Nevena V., Milić, Nataša M., Radenković, Dejan, "Meta-analysis of circulating cell-free dna’s role in the prognosis of pancreatic cancer" in Cancers, 13, no. 14 (2021):3378,
https://doi.org/10.3390/cancers13143378 . .

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

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

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

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

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

TY  - JOUR
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Davidović, Radoslav S.
AU  - Drljača, Tamara
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8894
AB  - For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm–Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php.
T2  - PLOS One
T1  - Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies
VL  - 16
IS  - 1
SP  - e0244948
DO  - 10.1371/journal.pone.0244948
ER  - 

@article{
author = "Gemović, Branislava S. and Perović, Vladimir R. and Davidović, Radoslav S. and Drljača, Tamara and Veljković, Nevena V.",
year = "2021",
abstract = "For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm–Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php.",
journal = "PLOS One",
title = "Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies",
volume = "16",
number = "1",
pages = "e0244948",
doi = "10.1371/journal.pone.0244948"
}

Gemović, B. S., Perović, V. R., Davidović, R. S., Drljača, T.,& Veljković, N. V.. (2021). Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies. in PLOS One, 16(1), e0244948.
https://doi.org/10.1371/journal.pone.0244948

Gemović BS, Perović VR, Davidović RS, Drljača T, Veljković NV. Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies. in PLOS One. 2021;16(1):e0244948.
doi:10.1371/journal.pone.0244948 .

Gemović, Branislava S., Perović, Vladimir R., Davidović, Radoslav S., Drljača, Tamara, Veljković, Nevena V., "Alignment-free method for functional annotation of amino acid substitutions: Application on epigenetic factors involved in hematologic malignancies" in PLOS One, 16, no. 1 (2021):e0244948,
https://doi.org/10.1371/journal.pone.0244948 . .

TY  - JOUR
AU  - Necci, Marco
AU  - Piovesan, Damiano
AU  - Tosatto, Silvio C. E.
AU  - Davidović, Radoslav S.
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9698
AB  - Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F max = 0.483 on the full dataset and F max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.
T2  - Nature Methods
T1  - Critical assessment of protein intrinsic disorder prediction
VL  - 18
IS  - 5
SP  - 472
EP  - 481
DO  - 10.1038/s41592-021-01117-3
ER  - 

@article{
author = "Necci, Marco and Piovesan, Damiano and Tosatto, Silvio C. E. and Davidović, Radoslav S. and Veljković, Nevena V.",
year = "2021",
abstract = "Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F max = 0.483 on the full dataset and F max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.",
journal = "Nature Methods",
title = "Critical assessment of protein intrinsic disorder prediction",
volume = "18",
number = "5",
pages = "472-481",
doi = "10.1038/s41592-021-01117-3"
}

Necci, M., Piovesan, D., Tosatto, S. C. E., Davidović, R. S.,& Veljković, N. V.. (2021). Critical assessment of protein intrinsic disorder prediction. in Nature Methods, 18(5), 472-481.
https://doi.org/10.1038/s41592-021-01117-3

Necci M, Piovesan D, Tosatto SCE, Davidović RS, Veljković NV. Critical assessment of protein intrinsic disorder prediction. in Nature Methods. 2021;18(5):472-481.
doi:10.1038/s41592-021-01117-3 .

Necci, Marco, Piovesan, Damiano, Tosatto, Silvio C. E., Davidović, Radoslav S., Veljković, Nevena V., "Critical assessment of protein intrinsic disorder prediction" in Nature Methods, 18, no. 5 (2021):472-481,
https://doi.org/10.1038/s41592-021-01117-3 . .

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

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

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

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

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

TY  - JOUR
AU  - Đikić, Teodora
AU  - Vučićević, Jelica
AU  - Laurila, Jonne
AU  - Radi, Marco
AU  - Veljković, Nevena V.
AU  - Xhaard, Henri
AU  - Nikolić, Katarina M.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8887
AB  - Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors – rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α2- adrenoceptors.
T2  - Molecular Informatics
T1  - Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field
VL  - 39
IS  - 7
SP  - 1900165
DO  - 10.1002/minf.201900165
ER  - 

@article{
author = "Đikić, Teodora and Vučićević, Jelica and Laurila, Jonne and Radi, Marco and Veljković, Nevena V. and Xhaard, Henri and Nikolić, Katarina M.",
year = "2020",
abstract = "Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors – rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α2- adrenoceptors.",
journal = "Molecular Informatics",
title = "Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field",
volume = "39",
number = "7",
pages = "1900165",
doi = "10.1002/minf.201900165"
}

Đikić, T., Vučićević, J., Laurila, J., Radi, M., Veljković, N. V., Xhaard, H.,& Nikolić, K. M.. (2020). Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field. in Molecular Informatics, 39(7), 1900165.
https://doi.org/10.1002/minf.201900165

Đikić T, Vučićević J, Laurila J, Radi M, Veljković NV, Xhaard H, Nikolić KM. Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field. in Molecular Informatics. 2020;39(7):1900165.
doi:10.1002/minf.201900165 .

Đikić, Teodora, Vučićević, Jelica, Laurila, Jonne, Radi, Marco, Veljković, Nevena V., Xhaard, Henri, Nikolić, Katarina M., "Deciphering Imidazoline Off‐targets by Fishing in the Class A of GPCR field" in Molecular Informatics, 39, no. 7 (2020):1900165,
https://doi.org/10.1002/minf.201900165 . .

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Leclercq, Jeremy Y
AU  - Šumonja, Neven
AU  - Richard, Francois D
AU  - Veljković, Nevena V.
AU  - Kajava, Andrey V.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8997
AB  - Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs. Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%.
T2  - Bioinformatics
T1  - Tally-2.0: upgraded validator of tandem repeat detection in protein sequences
VL  - 36
IS  - 10
SP  - 3260
EP  - 3262
DO  - 10.1093/bioinformatics/btaa121
ER  - 

@article{
author = "Perović, Vladimir R. and Leclercq, Jeremy Y and Šumonja, Neven and Richard, Francois D and Veljković, Nevena V. and Kajava, Andrey V.",
year = "2020",
abstract = "Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs. Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%.",
journal = "Bioinformatics",
title = "Tally-2.0: upgraded validator of tandem repeat detection in protein sequences",
volume = "36",
number = "10",
pages = "3260-3262",
doi = "10.1093/bioinformatics/btaa121"
}

Perović, V. R., Leclercq, J. Y., Šumonja, N., Richard, F. D., Veljković, N. V.,& Kajava, A. V.. (2020). Tally-2.0: upgraded validator of tandem repeat detection in protein sequences. in Bioinformatics, 36(10), 3260-3262.
https://doi.org/10.1093/bioinformatics/btaa121

Perović VR, Leclercq JY, Šumonja N, Richard FD, Veljković NV, Kajava AV. Tally-2.0: upgraded validator of tandem repeat detection in protein sequences. in Bioinformatics. 2020;36(10):3260-3262.
doi:10.1093/bioinformatics/btaa121 .

Perović, Vladimir R., Leclercq, Jeremy Y, Šumonja, Neven, Richard, Francois D, Veljković, Nevena V., Kajava, Andrey V., "Tally-2.0: upgraded validator of tandem repeat detection in protein sequences" in Bioinformatics, 36, no. 10 (2020):3260-3262,
https://doi.org/10.1093/bioinformatics/btaa121 . .

TY  - JOUR
AU  - Davidović, Radoslav S.
AU  - Perović, Vladimir R.
AU  - Gemović, Branislava S.
AU  - Veljković, Nevena V.
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9666
AB  - Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design.DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php.Supplementary data are available at Bioinformatics online.
T2  - Bioinformatics
T1  - DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis
VL  - 36
IS  - 6
SP  - 1981
EP  - 1982
DO  - 10.1093/bioinformatics/btz836
ER  - 

@article{
author = "Davidović, Radoslav S. and Perović, Vladimir R. and Gemović, Branislava S. and Veljković, Nevena V.",
year = "2020",
abstract = "Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design.DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php.Supplementary data are available at Bioinformatics online.",
journal = "Bioinformatics",
title = "DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis",
volume = "36",
number = "6",
pages = "1981-1982",
doi = "10.1093/bioinformatics/btz836"
}

Davidović, R. S., Perović, V. R., Gemović, B. S.,& Veljković, N. V.. (2020). DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis. in Bioinformatics, 36(6), 1981-1982.
https://doi.org/10.1093/bioinformatics/btz836

Davidović RS, Perović VR, Gemović BS, Veljković NV. DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis. in Bioinformatics. 2020;36(6):1981-1982.
doi:10.1093/bioinformatics/btz836 .

Davidović, Radoslav S., Perović, Vladimir R., Gemović, Branislava S., Veljković, Nevena V., "DiNGO: standalone application for Gene Ontology and Human Phenotype Ontology term enrichment analysis" in Bioinformatics, 36, no. 6 (2020):1981-1982,
https://doi.org/10.1093/bioinformatics/btz836 . .

TY  - JOUR
AU  - Hatos, András
AU  - Hajdu-Soltész, Borbála
AU  - Monzon, Alexander M
AU  - Palopoli, Nicolas
AU  - Álvarez, Lucía
AU  - Aykac-Fas, Burcu
AU  - Bassot, Claudio
AU  - Benítez, Guillermo I
AU  - Bevilacqua, Martina
AU  - Chasapi, Anastasia
AU  - Chemes, Lucia
AU  - Davey, Norman E
AU  - Davidović, Radoslav S.
AU  - Dunker, A Keith
AU  - Elofsson, Arne
AU  - Gobeill, Julien
AU  - Foutel, Nicolás S González
AU  - Sudha, Govindarajan
AU  - Guharoy, Mainak
AU  - Horvath, Tamas
AU  - Iglesias, Valentin
AU  - Kajava, Andrey V.
AU  - Kovacs, Orsolya P
AU  - Lamb, John
AU  - Lambrughi, Matteo
AU  - Lazar, Tamas
AU  - Leclercq, Jeremy Y
AU  - Leonardi, Emanuela
AU  - Macedo-Ribeiro, Sandra
AU  - Macossay-Castillo, Mauricio
AU  - Maiani, Emiliano
AU  - Manso, José A
AU  - Marino-Buslje, Cristina
AU  - Martínez-Pérez, Elizabeth
AU  - Mészáros, Bálint
AU  - Mičetić, Ivan
AU  - Minervini, Giovanni
AU  - Murvai, Nikoletta
AU  - Necci, Marco
AU  - Ouzounis, Christos A
AU  - Pajkos, Mátyás
AU  - Paladin, Lisanna
AU  - Pancsa, Rita
AU  - Papaleo, Elena
AU  - Parisi, Gustavo
AU  - Pasche, Emilie
AU  - Barbosa Pereira, Pedro J
AU  - Promponas, Vasilis J
AU  - Pujols, Jordi
AU  - Quaglia, Federica
AU  - Ruch, Patrick
AU  - Salvatore, Marco
AU  - Schad, Eva
AU  - Szabo, Beata
AU  - Szaniszló, Tamás
AU  - Tamana, Stella
AU  - Tantos, Agnes
AU  - Veljković, Nevena V.
AU  - Ventura, Salvador
AU  - Vranken, Wim
AU  - Dosztányi, Zsuzsanna
AU  - Tompa, Peter
AU  - Tosatto, Silvio C E
AU  - Piovesan, Damiano
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8799
AB  - The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.
T2  - Nucleic Acids Research
T1  - DisProt: intrinsic protein disorder annotation in 2020
VL  - 48
IS  - D1
SP  - D269
EP  - D276
DO  - 10.1093/nar/gkz975
ER  - 

@article{
author = "Hatos, András and Hajdu-Soltész, Borbála and Monzon, Alexander M and Palopoli, Nicolas and Álvarez, Lucía and Aykac-Fas, Burcu and Bassot, Claudio and Benítez, Guillermo I and Bevilacqua, Martina and Chasapi, Anastasia and Chemes, Lucia and Davey, Norman E and Davidović, Radoslav S. and Dunker, A Keith and Elofsson, Arne and Gobeill, Julien and Foutel, Nicolás S González and Sudha, Govindarajan and Guharoy, Mainak and Horvath, Tamas and Iglesias, Valentin and Kajava, Andrey V. and Kovacs, Orsolya P and Lamb, John and Lambrughi, Matteo and Lazar, Tamas and Leclercq, Jeremy Y and Leonardi, Emanuela and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Maiani, Emiliano and Manso, José A and Marino-Buslje, Cristina and Martínez-Pérez, Elizabeth and Mészáros, Bálint and Mičetić, Ivan and Minervini, Giovanni and Murvai, Nikoletta and Necci, Marco and Ouzounis, Christos A and Pajkos, Mátyás and Paladin, Lisanna and Pancsa, Rita and Papaleo, Elena and Parisi, Gustavo and Pasche, Emilie and Barbosa Pereira, Pedro J and Promponas, Vasilis J and Pujols, Jordi and Quaglia, Federica and Ruch, Patrick and Salvatore, Marco and Schad, Eva and Szabo, Beata and Szaniszló, Tamás and Tamana, Stella and Tantos, Agnes and Veljković, Nevena V. and Ventura, Salvador and Vranken, Wim and Dosztányi, Zsuzsanna and Tompa, Peter and Tosatto, Silvio C E and Piovesan, Damiano",
year = "2019",
abstract = "The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.",
journal = "Nucleic Acids Research",
title = "DisProt: intrinsic protein disorder annotation in 2020",
volume = "48",
number = "D1",
pages = "D269-D276",
doi = "10.1093/nar/gkz975"
}

Hatos, A., Hajdu-Soltész, B., Monzon, A. M., Palopoli, N., Álvarez, L., Aykac-Fas, B., Bassot, C., Benítez, G. I., Bevilacqua, M., Chasapi, A., Chemes, L., Davey, N. E., Davidović, R. S., Dunker, A. K., Elofsson, A., Gobeill, J., Foutel, N. S. G., Sudha, G., Guharoy, M., Horvath, T., Iglesias, V., Kajava, A. V., Kovacs, O. P., Lamb, J., Lambrughi, M., Lazar, T., Leclercq, J. Y., Leonardi, E., Macedo-Ribeiro, S., Macossay-Castillo, M., Maiani, E., Manso, J. A., Marino-Buslje, C., Martínez-Pérez, E., Mészáros, B., Mičetić, I., Minervini, G., Murvai, N., Necci, M., Ouzounis, C. A., Pajkos, M., Paladin, L., Pancsa, R., Papaleo, E., Parisi, G., Pasche, E., Barbosa Pereira, P. J., Promponas, V. J., Pujols, J., Quaglia, F., Ruch, P., Salvatore, M., Schad, E., Szabo, B., Szaniszló, T., Tamana, S., Tantos, A., Veljković, N. V., Ventura, S., Vranken, W., Dosztányi, Z., Tompa, P., Tosatto, S. C. E.,& Piovesan, D.. (2019). DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research, 48(D1), D269-D276.
https://doi.org/10.1093/nar/gkz975

Hatos A, Hajdu-Soltész B, Monzon AM, Palopoli N, Álvarez L, Aykac-Fas B, Bassot C, Benítez GI, Bevilacqua M, Chasapi A, Chemes L, Davey NE, Davidović RS, Dunker AK, Elofsson A, Gobeill J, Foutel NSG, Sudha G, Guharoy M, Horvath T, Iglesias V, Kajava AV, Kovacs OP, Lamb J, Lambrughi M, Lazar T, Leclercq JY, Leonardi E, Macedo-Ribeiro S, Macossay-Castillo M, Maiani E, Manso JA, Marino-Buslje C, Martínez-Pérez E, Mészáros B, Mičetić I, Minervini G, Murvai N, Necci M, Ouzounis CA, Pajkos M, Paladin L, Pancsa R, Papaleo E, Parisi G, Pasche E, Barbosa Pereira PJ, Promponas VJ, Pujols J, Quaglia F, Ruch P, Salvatore M, Schad E, Szabo B, Szaniszló T, Tamana S, Tantos A, Veljković NV, Ventura S, Vranken W, Dosztányi Z, Tompa P, Tosatto SCE, Piovesan D. DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research. 2019;48(D1):D269-D276.
doi:10.1093/nar/gkz975 .

Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M, Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I, Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E, Davidović, Radoslav S., Dunker, A Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P, Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y, Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A, Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J, Promponas, Vasilis J, Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljković, Nevena V., Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C E, Piovesan, Damiano, "DisProt: intrinsic protein disorder annotation in 2020" in Nucleic Acids Research, 48, no. D1 (2019):D269-D276,
https://doi.org/10.1093/nar/gkz975 . .

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

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

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

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

Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.
T2  - Current Medicinal Chemistry
T1  - Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes
VL  - 26
IS  - 21
SP  - 3890
EP  - 3910
DO  - 10.2174/0929867325666180214113704
ER  - 

@article{
author = "Gemović, Branislava S. and Šumonja, Neven and Davidović, Radoslav and Perović, Vladimir and Veljković, Nevena V.",
year = "2019",
abstract = "Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology.

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

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

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

Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein–protein complexes for experimental studies.",
journal = "Current Medicinal Chemistry",
title = "Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes",
volume = "26",
number = "21",
pages = "3890-3910",
doi = "10.2174/0929867325666180214113704"
}

Gemović, B. S., Šumonja, N., Davidović, R., Perović, V.,& Veljković, N. V.. (2019). Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes. in Current Medicinal Chemistry, 26(21), 3890-3910.
https://doi.org/10.2174/0929867325666180214113704

Gemović BS, Šumonja N, Davidović R, Perović V, Veljković NV. Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes. in Current Medicinal Chemistry. 2019;26(21):3890-3910.
doi:10.2174/0929867325666180214113704 .

Gemović, Branislava S., Šumonja, Neven, Davidović, Radoslav, Perović, Vladimir, Veljković, Nevena V., "Mapping of Protein-Protein Interactions: Web-Based Resources for Revealing Interactomes" in Current Medicinal Chemistry, 26, no. 21 (2019):3890-3910,
https://doi.org/10.2174/0929867325666180214113704 . .

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

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

Radošević, D., Senćanski, M. V., Perović, V. R., Veljković, N. V., Prljić, J., Veljković, V., Mantlo, E., Bukreyeva, N., Paessler, S.,& Glišić, S.. (2019). Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors. in Frontiers in Cellular and Infection Microbiology, 9, 67.
https://doi.org/10.3389/fcimb.2019.00067

Radošević D, Senćanski MV, Perović VR, Veljković NV, Prljić J, Veljković V, Mantlo E, Bukreyeva N, Paessler S, Glišić S. Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors. in Frontiers in Cellular and Infection Microbiology. 2019;9:67.
doi:10.3389/fcimb.2019.00067 .

Radošević, Draginja, Senćanski, Milan V., Perović, Vladimir R., Veljković, Nevena V., Prljić, Jelena, Veljković, Veljko, Mantlo, Emily, Bukreyeva, Natalya, Paessler, Slobodan, Glišić, Sanja, "Virtual Screen for Repurposing of Drugs for Candidate Influenza a M2 Ion-Channel Inhibitors" in Frontiers in Cellular and Infection Microbiology, 9 (2019):67,
https://doi.org/10.3389/fcimb.2019.00067 . .

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

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

Šumonja, N., Gemović, B. S., Veljković, N. V.,& Perović, V. R.. (2019). Automated feature engineering improves prediction of protein–protein interactions. in Amino Acids, 51(8), 1187-1200.
https://doi.org/10.1007/s00726-019-02756-9

Šumonja N, Gemović BS, Veljković NV, Perović VR. Automated feature engineering improves prediction of protein–protein interactions. in Amino Acids. 2019;51(8):1187-1200.
doi:10.1007/s00726-019-02756-9 .

Šumonja, Neven, Gemović, Branislava S., Veljković, Nevena V., Perović, Vladimir R., "Automated feature engineering improves prediction of protein–protein interactions" in Amino Acids, 51, no. 8 (2019):1187-1200,
https://doi.org/10.1007/s00726-019-02756-9 . .

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

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

Susec, M., Senćanski, M. V., Glišić, S., Veljković, N. V., Pedersen, C., Drinovec, L., Stojan, J., Nøhr, J.,& Vrecl, M.. (2019). Functional characterization of β2-adrenergic and insulin receptor heteromers. in Neuropharmacology, 152, 78-89.
https://doi.org/10.1016/j.neuropharm.2019.01.025

Susec M, Senćanski MV, Glišić S, Veljković NV, Pedersen C, Drinovec L, Stojan J, Nøhr J, Vrecl M. Functional characterization of β2-adrenergic and insulin receptor heteromers. in Neuropharmacology. 2019;152:78-89.
doi:10.1016/j.neuropharm.2019.01.025 .

Susec, Maja, Senćanski, Milan V., Glišić, Sanja, Veljković, Nevena V., Pedersen, Christina, Drinovec, Luka, Stojan, Jurij, Nøhr, Jane, Vrecl, Milka, "Functional characterization of β2-adrenergic and insulin receptor heteromers" in Neuropharmacology, 152 (2019):78-89,
https://doi.org/10.1016/j.neuropharm.2019.01.025 . .

TY  - JOUR
AU  - Veljković, Nevena V.
PY  - 2019
UR  - https://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",
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). in 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). in Current Medicinal Chemistry. 2019;26(21):3836-3837.
doi:10.2174/092986732621190919104301 .

Veljković, Nevena V., "Recent In Silico Resources for Drug Design and Discovery (Editorial)" in Current Medicinal Chemistry, 26, no. 21 (2019):3836-3837,
https://doi.org/10.2174/092986732621190919104301 . .

TY  - JOUR
AU  - Senćanski, Milan V.
AU  - Glišić, Sanja
AU  - Šnajder, Marko
AU  - Veljković, Nevena V.
AU  - Poklar Ulrih, Nataša
AU  - Mavri, Janez
AU  - Vrecl, Milka
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8648
AB  - This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).
T2  - Scientific Reports
T1  - Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)
VL  - 9
IS  - 1
SP  - 16555
DO  - 10.1038/s41598-019-52934-8
ER  - 

@article{
author = "Senćanski, Milan V. and Glišić, Sanja and Šnajder, Marko and Veljković, Nevena V. and Poklar Ulrih, Nataša and Mavri, Janez and Vrecl, Milka",
year = "2019",
abstract = "This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s).",
journal = "Scientific Reports",
title = "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)",
volume = "9",
number = "1",
pages = "16555",
doi = "10.1038/s41598-019-52934-8"
}

Senćanski, M. V., Glišić, S., Šnajder, M., Veljković, N. V., Poklar Ulrih, N., Mavri, J.,& Vrecl, M.. (2019). Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR). in Scientific Reports, 9(1), 16555.
https://doi.org/10.1038/s41598-019-52934-8

Senćanski MV, Glišić S, Šnajder M, Veljković NV, Poklar Ulrih N, Mavri J, Vrecl M. Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR). in Scientific Reports. 2019;9(1):16555.
doi:10.1038/s41598-019-52934-8 .

Senćanski, Milan V., Glišić, Sanja, Šnajder, Marko, Veljković, Nevena V., Poklar Ulrih, Nataša, Mavri, Janez, Vrecl, Milka, "Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)" in Scientific Reports, 9, no. 1 (2019):16555,
https://doi.org/10.1038/s41598-019-52934-8 . .

TY  - JOUR
AU  - Zhou, Naihui
AU  - Jiang, Yuxiang
AU  - Bergquist, Timothy R
AU  - Lee, Alexandra J
AU  - Kacsoh, Balint Z
AU  - Crocker, Alex W
AU  - Lewis, Kimberley A
AU  - Georghiou, George
AU  - Nguyen, Huy N
AU  - Hamid, Md Nafiz
AU  - Davis, Larry
AU  - Dogan, Tunca
AU  - Atalay, Volkan
AU  - Rifaioglu, Ahmet S
AU  - Dalkıran, Alperen
AU  - Cetin Atalay, Rengul
AU  - Zhang, Chengxin
AU  - Hurto, Rebecca L
AU  - Freddolino, Peter L
AU  - Zhang, Yang
AU  - Bhat, Prajwal
AU  - Supek, Fran
AU  - Fernández, José M
AU  - Gemović, Branislava S.
AU  - Perović, Vladimir R.
AU  - Davidović, Radoslav S.
AU  - Šumonja, Neven
AU  - Veljković, Nevena V.
AU  - Asgari, Ehsaneddin
AU  - Mofrad, Mohammad R.K.
AU  - Profiti, Giuseppe
AU  - Savojardo, Castrense
AU  - Martelli, Pier Luigi
AU  - Casadio, Rita
AU  - Boecker, Florian
AU  - Schoof, Heiko
AU  - Kahanda, Indika
AU  - Thurlby, Natalie
AU  - McHardy, Alice C
AU  - Renaux, Alexandre
AU  - Saidi, Rabie
AU  - Gough, Julian
AU  - Freitas, Alex A
AU  - Antczak, Magdalena
AU  - Fabris, Fabio
AU  - Wass, Mark N
AU  - Hou, Jie
AU  - Cheng, Jianlin
AU  - Wang, Zheng
AU  - Romero, Alfonso E
AU  - Paccanaro, Alberto
AU  - Yang, Haixuan
AU  - Goldberg, Tatyana
AU  - Zhao, Chenguang
AU  - Holm, Liisa
AU  - Törönen, Petri
AU  - Medlar, Alan J
AU  - Zosa, Elaine
AU  - Borukhov, Itamar
AU  - Novikov, Ilya
AU  - Wilkins, Angela
AU  - Lichtarge, Olivier
AU  - Chi, Po-Han
AU  - Tseng, Wei-Cheng
AU  - Linial, Michal
AU  - Rose, Peter W
AU  - Dessimoz, Christophe
AU  - Vidulin, Vedrana
AU  - Dzeroski, Saso
AU  - Sillitoe, Ian
AU  - Das, Sayoni
AU  - Lees, Jonathan Gill
AU  - Jones, David T
AU  - Wan, Cen
AU  - Cozzetto, Domenico
AU  - Fa, Rui
AU  - Torres, Mateo
AU  - Warwick Vesztrocy, Alex
AU  - Rodriguez, Jose Manuel
AU  - Tress, Michael L
AU  - Frasca, Marco
AU  - Notaro, Marco
AU  - Grossi, Giuliano
AU  - Petrini, Alessandro
AU  - Re, Matteo
AU  - Valentini, Giorgio
AU  - Mesiti, Marco
AU  - Roche, Daniel B
AU  - Reeb, Jonas
AU  - Ritchie, David W
AU  - Aridhi, Sabeur
AU  - Alborzi, Seyed Ziaeddin
AU  - Devignes, Marie-Dominique
AU  - Koo, Da Chen Emily
AU  - Bonneau, Richard
AU  - Gligorijević, Vladimir
AU  - Barot, Meet
AU  - Fang, Hai
AU  - Toppo, Stefano
AU  - Lavezzo, Enrico
AU  - Falda, Marco
AU  - Berselli, Michele
AU  - Tosatto, Silvio C.E.
AU  - Carraro, Marco
AU  - Piovesan, Damiano
AU  - Ur Rehman, Hafeez
AU  - Mao, Qizhong
AU  - Zhang, Shanshan
AU  - Vucetic, Slobodan
AU  - Black, Gage S
AU  - Jo, Dane
AU  - Suh, Erica
AU  - Dayton, Jonathan B
AU  - Larsen, Dallas J
AU  - Omdahl, Ashton R
AU  - McGuffin, Liam J
AU  - Brackenridge, Danielle A
AU  - Babbitt, Patricia C
AU  - Yunes, Jeffrey M
AU  - Fontana, Paolo
AU  - Zhang, Feng
AU  - Zhu, Shanfeng
AU  - You, Ronghui
AU  - Zhang, Zihan
AU  - Dai, Suyang
AU  - Yao, Shuwei
AU  - Tian, Weidong
AU  - Cao, Renzhi
AU  - Chandler, Caleb
AU  - Amezola, Miguel
AU  - Johnson, Devon
AU  - Chang, Jia-Ming
AU  - Liao, Wen-Hung
AU  - Liu, Yi-Wei
AU  - Pascarelli, Stefano
AU  - Frank, Yotam
AU  - Hoehndorf, Robert
AU  - Kulmanov, Maxat
AU  - Boudellioua, Imane
AU  - Politano, Gianfranco
AU  - Di Carlo, Stefano
AU  - Benso, Alfredo
AU  - Hakala, Kai
AU  - Ginter, Filip
AU  - Mehryary, Farrokh
AU  - Kaewphan, Suwisa
AU  - Björne, Jari
AU  - Moen, Hans
AU  - Tolvanen, Martti E.E.
AU  - Salakoski, Tapio
AU  - Kihara, Daisuke
AU  - Jain, Aashish
AU  - Šmuc, Tomislav
AU  - Altenhoff, Adrian
AU  - Ben-Hur, Asa
AU  - Rost, Burkhard
AU  - Brenner, Steven E
AU  - Orengo, Christine A
AU  - Jeffery, Constance J
AU  - Bosco, Giovanni
AU  - Hogan, Deborah A
AU  - Martin, Maria J
AU  - O’Donovan, Claire
AU  - Mooney, Sean D
AU  - Greene, Casey S
AU  - Radivojac, Predrag
AU  - Friedberg, Iddo
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8655
AB  - Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).
T2  - Genome Biology
T1  - The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
VL  - 20
IS  - 1
SP  - 244
DO  - 10.1186/s13059-019-1835-8
ER  - 

@article{
author = "Zhou, Naihui and Jiang, Yuxiang and Bergquist, Timothy R and Lee, Alexandra J and Kacsoh, Balint Z and Crocker, Alex W and Lewis, Kimberley A and Georghiou, George and Nguyen, Huy N and Hamid, Md Nafiz and Davis, Larry and Dogan, Tunca and Atalay, Volkan and Rifaioglu, Ahmet S and Dalkıran, Alperen and Cetin Atalay, Rengul and Zhang, Chengxin and Hurto, Rebecca L and Freddolino, Peter L and Zhang, Yang and Bhat, Prajwal and Supek, Fran and Fernández, José M and Gemović, Branislava S. and Perović, Vladimir R. and Davidović, Radoslav S. and Šumonja, Neven and Veljković, Nevena V. and Asgari, Ehsaneddin and Mofrad, Mohammad R.K. and Profiti, Giuseppe and Savojardo, Castrense and Martelli, Pier Luigi and Casadio, Rita and Boecker, Florian and Schoof, Heiko and Kahanda, Indika and Thurlby, Natalie and McHardy, Alice C and Renaux, Alexandre and Saidi, Rabie and Gough, Julian and Freitas, Alex A and Antczak, Magdalena and Fabris, Fabio and Wass, Mark N and Hou, Jie and Cheng, Jianlin and Wang, Zheng and Romero, Alfonso E and Paccanaro, Alberto and Yang, Haixuan and Goldberg, Tatyana and Zhao, Chenguang and Holm, Liisa and Törönen, Petri and Medlar, Alan J and Zosa, Elaine and Borukhov, Itamar and Novikov, Ilya and Wilkins, Angela and Lichtarge, Olivier and Chi, Po-Han and Tseng, Wei-Cheng and Linial, Michal and Rose, Peter W and Dessimoz, Christophe and Vidulin, Vedrana and Dzeroski, Saso and Sillitoe, Ian and Das, Sayoni and Lees, Jonathan Gill and Jones, David T and Wan, Cen and Cozzetto, Domenico and Fa, Rui and Torres, Mateo and Warwick Vesztrocy, Alex and Rodriguez, Jose Manuel and Tress, Michael L and Frasca, Marco and Notaro, Marco and Grossi, Giuliano and Petrini, Alessandro and Re, Matteo and Valentini, Giorgio and Mesiti, Marco and Roche, Daniel B and Reeb, Jonas and Ritchie, David W and Aridhi, Sabeur and Alborzi, Seyed Ziaeddin and Devignes, Marie-Dominique and Koo, Da Chen Emily and Bonneau, Richard and Gligorijević, Vladimir and Barot, Meet and Fang, Hai and Toppo, Stefano and Lavezzo, Enrico and Falda, Marco and Berselli, Michele and Tosatto, Silvio C.E. and Carraro, Marco and Piovesan, Damiano and Ur Rehman, Hafeez and Mao, Qizhong and Zhang, Shanshan and Vucetic, Slobodan and Black, Gage S and Jo, Dane and Suh, Erica and Dayton, Jonathan B and Larsen, Dallas J and Omdahl, Ashton R and McGuffin, Liam J and Brackenridge, Danielle A and Babbitt, Patricia C and Yunes, Jeffrey M and Fontana, Paolo and Zhang, Feng and Zhu, Shanfeng and You, Ronghui and Zhang, Zihan and Dai, Suyang and Yao, Shuwei and Tian, Weidong and Cao, Renzhi and Chandler, Caleb and Amezola, Miguel and Johnson, Devon and Chang, Jia-Ming and Liao, Wen-Hung and Liu, Yi-Wei and Pascarelli, Stefano and Frank, Yotam and Hoehndorf, Robert and Kulmanov, Maxat and Boudellioua, Imane and Politano, Gianfranco and Di Carlo, Stefano and Benso, Alfredo and Hakala, Kai and Ginter, Filip and Mehryary, Farrokh and Kaewphan, Suwisa and Björne, Jari and Moen, Hans and Tolvanen, Martti E.E. and Salakoski, Tapio and Kihara, Daisuke and Jain, Aashish and Šmuc, Tomislav and Altenhoff, Adrian and Ben-Hur, Asa and Rost, Burkhard and Brenner, Steven E and Orengo, Christine A and Jeffery, Constance J and Bosco, Giovanni and Hogan, Deborah A and Martin, Maria J and O’Donovan, Claire and Mooney, Sean D and Greene, Casey S and Radivojac, Predrag and Friedberg, Iddo",
year = "2019",
abstract = "Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-Term memory. Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens. © 2019 The Author(s).",
journal = "Genome Biology",
title = "The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens",
volume = "20",
number = "1",
pages = "244",
doi = "10.1186/s13059-019-1835-8"
}

Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M. N., Davis, L., Dogan, T., Atalay, V., Rifaioglu, A. S., Dalkıran, A., Cetin Atalay, R., Zhang, C., Hurto, R. L., Freddolino, P. L., Zhang, Y., Bhat, P., Supek, F., Fernández, J. M., Gemović, B. S., Perović, V. R., Davidović, R. S., Šumonja, N., Veljković, N. V., Asgari, E., Mofrad, M. R.K., Profiti, G., Savojardo, C., Martelli, P. L., Casadio, R., Boecker, F., Schoof, H., Kahanda, I., Thurlby, N., McHardy, A. C., Renaux, A., Saidi, R., Gough, J., Freitas, A. A., Antczak, M., Fabris, F., Wass, M. N., Hou, J., Cheng, J., Wang, Z., Romero, A. E., Paccanaro, A., Yang, H., Goldberg, T., Zhao, C., Holm, L., Törönen, P., Medlar, A. J., Zosa, E., Borukhov, I., Novikov, I., Wilkins, A., Lichtarge, O., Chi, P., Tseng, W., Linial, M., Rose, P. W., Dessimoz, C., Vidulin, V., Dzeroski, S., Sillitoe, I., Das, S., Lees, J. G., Jones, D. T., Wan, C., Cozzetto, D., Fa, R., Torres, M., Warwick Vesztrocy, A., Rodriguez, J. M., Tress, M. L., Frasca, M., Notaro, M., Grossi, G., Petrini, A., Re, M., Valentini, G., Mesiti, M., Roche, D. B., Reeb, J., Ritchie, D. W., Aridhi, S., Alborzi, S. Z., Devignes, M., Koo, D. C. E., Bonneau, R., Gligorijević, V., Barot, M., Fang, H., Toppo, S., Lavezzo, E., Falda, M., Berselli, M., Tosatto, S. C.E., Carraro, M., Piovesan, D., Ur Rehman, H., Mao, Q., Zhang, S., Vucetic, S., Black, G. S., Jo, D., Suh, E., Dayton, J. B., Larsen, D. J., Omdahl, A. R., McGuffin, L. J., Brackenridge, D. A., Babbitt, P. C., Yunes, J. M., Fontana, P., Zhang, F., Zhu, S., You, R., Zhang, Z., Dai, S., Yao, S., Tian, W., Cao, R., Chandler, C., Amezola, M., Johnson, D., Chang, J., Liao, W., Liu, Y., Pascarelli, S., Frank, Y., Hoehndorf, R., Kulmanov, M., Boudellioua, I., Politano, G., Di Carlo, S., Benso, A., Hakala, K., Ginter, F., Mehryary, F., Kaewphan, S., Björne, J., Moen, H., Tolvanen, M. E.E., Salakoski, T., Kihara, D., Jain, A., Šmuc, T., Altenhoff, A., Ben-Hur, A., Rost, B., Brenner, S. E., Orengo, C. A., Jeffery, C. J., Bosco, G., Hogan, D. A., Martin, M. J., O’Donovan, C., Mooney, S. D., Greene, C. S., Radivojac, P.,& Friedberg, I.. (2019). The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. in Genome Biology, 20(1), 244.
https://doi.org/10.1186/s13059-019-1835-8

Zhou N, Jiang Y, Bergquist TR, Lee AJ, Kacsoh BZ, Crocker AW, Lewis KA, Georghiou G, Nguyen HN, Hamid MN, Davis L, Dogan T, Atalay V, Rifaioglu AS, Dalkıran A, Cetin Atalay R, Zhang C, Hurto RL, Freddolino PL, Zhang Y, Bhat P, Supek F, Fernández JM, Gemović BS, Perović VR, Davidović RS, Šumonja N, Veljković NV, Asgari E, Mofrad MR, Profiti G, Savojardo C, Martelli PL, Casadio R, Boecker F, Schoof H, Kahanda I, Thurlby N, McHardy AC, Renaux A, Saidi R, Gough J, Freitas AA, Antczak M, Fabris F, Wass MN, Hou J, Cheng J, Wang Z, Romero AE, Paccanaro A, Yang H, Goldberg T, Zhao C, Holm L, Törönen P, Medlar AJ, Zosa E, Borukhov I, Novikov I, Wilkins A, Lichtarge O, Chi P, Tseng W, Linial M, Rose PW, Dessimoz C, Vidulin V, Dzeroski S, Sillitoe I, Das S, Lees JG, Jones DT, Wan C, Cozzetto D, Fa R, Torres M, Warwick Vesztrocy A, Rodriguez JM, Tress ML, Frasca M, Notaro M, Grossi G, Petrini A, Re M, Valentini G, Mesiti M, Roche DB, Reeb J, Ritchie DW, Aridhi S, Alborzi SZ, Devignes M, Koo DCE, Bonneau R, Gligorijević V, Barot M, Fang H, Toppo S, Lavezzo E, Falda M, Berselli M, Tosatto SC, Carraro M, Piovesan D, Ur Rehman H, Mao Q, Zhang S, Vucetic S, Black GS, Jo D, Suh E, Dayton JB, Larsen DJ, Omdahl AR, McGuffin LJ, Brackenridge DA, Babbitt PC, Yunes JM, Fontana P, Zhang F, Zhu S, You R, Zhang Z, Dai S, Yao S, Tian W, Cao R, Chandler C, Amezola M, Johnson D, Chang J, Liao W, Liu Y, Pascarelli S, Frank Y, Hoehndorf R, Kulmanov M, Boudellioua I, Politano G, Di Carlo S, Benso A, Hakala K, Ginter F, Mehryary F, Kaewphan S, Björne J, Moen H, Tolvanen ME, Salakoski T, Kihara D, Jain A, Šmuc T, Altenhoff A, Ben-Hur A, Rost B, Brenner SE, Orengo CA, Jeffery CJ, Bosco G, Hogan DA, Martin MJ, O’Donovan C, Mooney SD, Greene CS, Radivojac P, Friedberg I. The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. in Genome Biology. 2019;20(1):244.
doi:10.1186/s13059-019-1835-8 .

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

TY  - JOUR
AU  - Veljković, Nevena V.
AU  - Zarić, Božidarka
AU  - Đurić, Ilona
AU  - Obradović, Milan M.
AU  - Sudar-Milovanović, Emina
AU  - Radak, Đorđe J.
AU  - Isenović, Esma R.
PY  - 2018
UR  - http://www.mdpi.com/1010-660X/54/3/36
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7878
AB  - Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
T2  - Medicina
T1  - Genetic Markers for Coronary Artery Disease
VL  - 54
IS  - 3
SP  - 36
DO  - 10.3390/medicina54030036
ER  - 

@article{
author = "Veljković, Nevena V. and Zarić, Božidarka and Đurić, Ilona and Obradović, Milan M. and Sudar-Milovanović, Emina and Radak, Đorđe J. and Isenović, Esma R.",
year = "2018",
abstract = "Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.",
journal = "Medicina",
title = "Genetic Markers for Coronary Artery Disease",
volume = "54",
number = "3",
pages = "36",
doi = "10.3390/medicina54030036"
}

Veljković, N. V., Zarić, B., Đurić, I., Obradović, M. M., Sudar-Milovanović, E., Radak, Đ. J.,& Isenović, E. R.. (2018). Genetic Markers for Coronary Artery Disease. in Medicina, 54(3), 36.
https://doi.org/10.3390/medicina54030036

Veljković NV, Zarić B, Đurić I, Obradović MM, Sudar-Milovanović E, Radak ĐJ, Isenović ER. Genetic Markers for Coronary Artery Disease. in Medicina. 2018;54(3):36.
doi:10.3390/medicina54030036 .

Veljković, Nevena V., Zarić, Božidarka, Đurić, Ilona, Obradović, Milan M., Sudar-Milovanović, Emina, Radak, Đorđe J., Isenović, Esma R., "Genetic Markers for Coronary Artery Disease" in Medicina, 54, no. 3 (2018):36,
https://doi.org/10.3390/medicina54030036 . .

TY  - JOUR
AU  - Paessler, Slobodan
AU  - Huang, Cheng
AU  - Senćanski, Milan V.
AU  - Veljković, Nevena V.
AU  - Perović, Vladimir R.
AU  - Glišić, Sanja
AU  - Veljković, Veljko
PY  - 2018
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7695
AB  - The Ebola virus outbreak in West Africa 2015 and Congo 2017, point out an urgent need for development of drugs against this important pathogen. Previously, by repurposing virtual screening of 6438 drugs from DrugBank, ibuprofen was selected as a possible inhibitor of the Ebola virus infection. The results of an additional docking analysis as well as experimental results showing measurable anti-Ebola effect of ibuprofen in cell culture suggest ibuprofen as a promising molecular template for the development of drugs for treatment of the infection by Ebola virus.
T2  - Frontiers in Bioscience - Landmark
T1  - Ibuprofen as a template molecule for drug design against Ebola virus
VL  - 23
IS  - 5
SP  - 947
EP  - 953
UR  - https://hdl.handle.net/21.15107/rcub_vinar_7695
ER  - 

@article{
author = "Paessler, Slobodan and Huang, Cheng and Senćanski, Milan V. and Veljković, Nevena V. and Perović, Vladimir R. and Glišić, Sanja and Veljković, Veljko",
year = "2018",
abstract = "The Ebola virus outbreak in West Africa 2015 and Congo 2017, point out an urgent need for development of drugs against this important pathogen. Previously, by repurposing virtual screening of 6438 drugs from DrugBank, ibuprofen was selected as a possible inhibitor of the Ebola virus infection. The results of an additional docking analysis as well as experimental results showing measurable anti-Ebola effect of ibuprofen in cell culture suggest ibuprofen as a promising molecular template for the development of drugs for treatment of the infection by Ebola virus.",
journal = "Frontiers in Bioscience - Landmark",
title = "Ibuprofen as a template molecule for drug design against Ebola virus",
volume = "23",
number = "5",
pages = "947-953",
url = "https://hdl.handle.net/21.15107/rcub_vinar_7695"
}

Paessler, S., Huang, C., Senćanski, M. V., Veljković, N. V., Perović, V. R., Glišić, S.,& Veljković, V.. (2018). Ibuprofen as a template molecule for drug design against Ebola virus. in Frontiers in Bioscience - Landmark, 23(5), 947-953.
https://hdl.handle.net/21.15107/rcub_vinar_7695

Paessler S, Huang C, Senćanski MV, Veljković NV, Perović VR, Glišić S, Veljković V. Ibuprofen as a template molecule for drug design against Ebola virus. in Frontiers in Bioscience - Landmark. 2018;23(5):947-953.
https://hdl.handle.net/21.15107/rcub_vinar_7695 .

Paessler, Slobodan, Huang, Cheng, Senćanski, Milan V., Veljković, Nevena V., Perović, Vladimir R., Glišić, Sanja, Veljković, Veljko, "Ibuprofen as a template molecule for drug design against Ebola virus" in Frontiers in Bioscience - Landmark, 23, no. 5 (2018):947-953,
https://hdl.handle.net/21.15107/rcub_vinar_7695 .

TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Marsh, Lindsey A.
AU  - Radovanović, Sandro
AU  - Vukićević, Milan
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2018
UR  - http://www.nature.com/articles/s41598-018-28815-x
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7811
AB  - Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).
T2  - Scientific Reports
T1  - IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins
VL  - 8
IS  - 1
SP  - 10563
DO  - 10.1038/s41598-018-28815-x
ER  - 

@article{
author = "Perović, Vladimir R. and Šumonja, Neven and Marsh, Lindsey A. and Radovanović, Sandro and Vukićević, Milan and Roberts, Stefan G. E. and Veljković, Nevena V.",
year = "2018",
abstract = "Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).",
journal = "Scientific Reports",
title = "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins",
volume = "8",
number = "1",
pages = "10563",
doi = "10.1038/s41598-018-28815-x"
}

Perović, V. R., Šumonja, N., Marsh, L. A., Radovanović, S., Vukićević, M., Roberts, S. G. E.,& Veljković, N. V.. (2018). IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports, 8(1), 10563.
https://doi.org/10.1038/s41598-018-28815-x

Perović VR, Šumonja N, Marsh LA, Radovanović S, Vukićević M, Roberts SGE, Veljković NV. IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports. 2018;8(1):10563.
doi:10.1038/s41598-018-28815-x .

Perović, Vladimir R., Šumonja, Neven, Marsh, Lindsey A., Radovanović, Sandro, Vukićević, Milan, Roberts, Stefan G. E., Veljković, Nevena V., "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins" in Scientific Reports, 8, no. 1 (2018):10563,
https://doi.org/10.1038/s41598-018-28815-x . .

TY  - CONF
AU  - Senćanski, Milan
AU  - Vrecl, Milka
AU  - Veljković, Nevena V.
AU  - Glišić, Sanja
PY  - 2018
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/11013
AB  - Stabilization of specific G-protein coupled receptor (GPCR) conformation is achieved by ligand binding to orthosteric or allosteric sites on a GPCRs. A crucial unresolved issue in GPCRs activation/signaling is the role of receptor structural conformations in G protein/effector protein selection. One of the possible approaches to get comprehensive depiction of GPCRs activation dynamics are molecular simulations and recently described nanobody-derived intrabodies. Monomeric single-domain antibody (nanobody) from the Camelid family was found to allosterically bind to and stabilizes distinct conformational states of the β2AR. By applying informational spectrum method (ISM), a virtual spectroscopy method for investigation of the protein-protein interactions, we have designed peptide mimetic of the nanobody related to the β2AR (nanobody derived peptide, NDP). Further, interaction between NDP and the ligand-bound β2AR active conformation have been studied by protein-peptide docking, molecular dynamics simulations and metadynamics calculations of free energy binding. Finally, the affinity of selected NDPs towards agonist-activated β2AR was also studied by microscale thermophoresis (MST) and by bioluminescence resonance energy transfer (BRET) based β-arrestin 2 recruitment assay. MST data predicted micromolar range interaction of selected NDPs with the β2AR, while the preliminary β-arrestin 2 recruitment results suggest prospective further modification and optimization of NDPs toward effective modulators of the β2AR.
PB  - Department of Biology and Ecology : Faculty of Sciences University of Novi Sad
C3  - Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22
T1  - Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)
VL  - 40
IS  - 1
SP  - 58
UR  - https://hdl.handle.net/21.15107/rcub_vinar_11013
ER  - 

@conference{
author = "Senćanski, Milan and Vrecl, Milka and Veljković, Nevena V. and Glišić, Sanja",
year = "2018",
abstract = "Stabilization of specific G-protein coupled receptor (GPCR) conformation is achieved by ligand binding to orthosteric or allosteric sites on a GPCRs. A crucial unresolved issue in GPCRs activation/signaling is the role of receptor structural conformations in G protein/effector protein selection. One of the possible approaches to get comprehensive depiction of GPCRs activation dynamics are molecular simulations and recently described nanobody-derived intrabodies. Monomeric single-domain antibody (nanobody) from the Camelid family was found to allosterically bind to and stabilizes distinct conformational states of the β2AR. By applying informational spectrum method (ISM), a virtual spectroscopy method for investigation of the protein-protein interactions, we have designed peptide mimetic of the nanobody related to the β2AR (nanobody derived peptide, NDP). Further, interaction between NDP and the ligand-bound β2AR active conformation have been studied by protein-peptide docking, molecular dynamics simulations and metadynamics calculations of free energy binding. Finally, the affinity of selected NDPs towards agonist-activated β2AR was also studied by microscale thermophoresis (MST) and by bioluminescence resonance energy transfer (BRET) based β-arrestin 2 recruitment assay. MST data predicted micromolar range interaction of selected NDPs with the β2AR, while the preliminary β-arrestin 2 recruitment results suggest prospective further modification and optimization of NDPs toward effective modulators of the β2AR.",
publisher = "Department of Biology and Ecology : Faculty of Sciences University of Novi Sad",
journal = "Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22",
title = "Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)",
volume = "40",
number = "1",
pages = "58",
url = "https://hdl.handle.net/21.15107/rcub_vinar_11013"
}

Senćanski, M., Vrecl, M., Veljković, N. V.,& Glišić, S.. (2018). Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR). in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22
Department of Biology and Ecology : Faculty of Sciences University of Novi Sad., 40(1), 58.
https://hdl.handle.net/21.15107/rcub_vinar_11013

Senćanski M, Vrecl M, Veljković NV, Glišić S. Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR). in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22. 2018;40(1):58.
https://hdl.handle.net/21.15107/rcub_vinar_11013 .

Senćanski, Milan, Vrecl, Milka, Veljković, Nevena V., Glišić, Sanja, "Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)" in Biologia Serbica : Belgrade BioInformatics Conference : BelBi2018 : program and the book of abstracts; June 18-22, 40, no. 1 (2018):58,
https://hdl.handle.net/21.15107/rcub_vinar_11013 .

TY  - CONF
AU  - Perović, Vladimir R.
AU  - Gemović, Branislava S.
AU  - Veljković, Veljko
AU  - Glišić, Sanja
AU  - Veljković, Nevena V.
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10770
AB  - Summary. Coding genetic variants can have profound effects on protein function. Computational tools for the prediction of these effects are used to complement and guide experimental biological studies. Phylogenetic analyses that determine the evolutionary relationship among related sequences are commonly used to distinguish between functionally significant and insignificant gene variations. Here, we have reviewed applications of the non-alignment sequence analyses method for phylogenetic analyses, ISTREE. Furthermore, we assessed how an unsupervised ISTREE-d3 method based on the universal d3 measure responds to this task compared to supervised and semi-supervised ISTREE methods that were previously used in two studies. The findings presented here suggest that ISTREE-d3 can efficiently substitute for the corresponding supervised models, given that it is more suitable for automatic applications. In conclusion, the ISTREE-d3 method has a broad biological relevance and represents a promising approach in functional assessment of coding gene variations.
C3  - Biologica Serbica
T1  - Annotation Of The Functional Impact Of Coding Genetic Variants
VL  - 39
IS  - 1
SP  - 74
EP  - 82
DO  - 10.5281/zenodo.826908
ER  - 

@conference{
author = "Perović, Vladimir R. and Gemović, Branislava S. and Veljković, Veljko and Glišić, Sanja and Veljković, Nevena V.",
year = "2017",
abstract = "Summary. Coding genetic variants can have profound effects on protein function. Computational tools for the prediction of these effects are used to complement and guide experimental biological studies. Phylogenetic analyses that determine the evolutionary relationship among related sequences are commonly used to distinguish between functionally significant and insignificant gene variations. Here, we have reviewed applications of the non-alignment sequence analyses method for phylogenetic analyses, ISTREE. Furthermore, we assessed how an unsupervised ISTREE-d3 method based on the universal d3 measure responds to this task compared to supervised and semi-supervised ISTREE methods that were previously used in two studies. The findings presented here suggest that ISTREE-d3 can efficiently substitute for the corresponding supervised models, given that it is more suitable for automatic applications. In conclusion, the ISTREE-d3 method has a broad biological relevance and represents a promising approach in functional assessment of coding gene variations.",
journal = "Biologica Serbica",
title = "Annotation Of The Functional Impact Of Coding Genetic Variants",
volume = "39",
number = "1",
pages = "74-82",
doi = "10.5281/zenodo.826908"
}

Perović, V. R., Gemović, B. S., Veljković, V., Glišić, S.,& Veljković, N. V.. (2017). Annotation Of The Functional Impact Of Coding Genetic Variants. in Biologica Serbica, 39(1), 74-82.
https://doi.org/10.5281/zenodo.826908

Perović VR, Gemović BS, Veljković V, Glišić S, Veljković NV. Annotation Of The Functional Impact Of Coding Genetic Variants. in Biologica Serbica. 2017;39(1):74-82.
doi:10.5281/zenodo.826908 .

Perović, Vladimir R., Gemović, Branislava S., Veljković, Veljko, Glišić, Sanja, Veljković, Nevena V., "Annotation Of The Functional Impact Of Coding Genetic Variants" in Biologica Serbica, 39, no. 1 (2017):74-82,
https://doi.org/10.5281/zenodo.826908 . .

TY  - JOUR
AU  - 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  - https://vinar.vin.bg.ac.rs/handle/123456789/1465
T2  - Nucleic Acids Research
T1  - Erratum: DisProt 7.0: a major update of the database of disordered proteins
VL  - 45
IS  - D1
SP  - D1123
EP  - D1124
DO  - 10.1093/nar/gkw1279
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",
journal = "Nucleic Acids Research",
title = "Erratum: DisProt 7.0: a major update of the database of disordered proteins",
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). Erratum: DisProt 7.0: a major update of the database of disordered proteins. in 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. Erratum: DisProt 7.0: a major update of the database of disordered proteins. in Nucleic Acids Research. 2017;45(D1):D1123-D1124.
doi:10.1093/nar/gkw1279 .

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., "Erratum: DisProt 7.0: a major update of the database of disordered proteins" in Nucleic Acids Research, 45, no. D1 (2017):D1123-D1124,
https://doi.org/10.1093/nar/gkw1279 . .