Draft:Gennady Verkhivker
American computational biologist
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Gennady M. Verkhivker is a Russian-born American computational biologist and theoretical biophysicist. He is a professor of computational biosciences in the Schmid College of Science and Technology and a professor of biomedical and pharmaceutical sciences in the School of Pharmacy at Chapman University, and an adjunct professor of pharmacology at the Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego.[1][2] His research applies computational modeling and machine learning to problems in structure-based drug design, molecular docking and the allosteric regulation of proteins.[1][3]
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Comment: Sourcing does not demonstrate WP:NPROF. Sources are all connected to Verkhivker (by him or his employers). We need significant coverage in independent sources, or evidence of a major international award or leadership of a major scientific organization (see WP:NPROF). WeirdNAnnoyed (talk) 21:21, 14 August 2026 (UTC)
- Comment: In accordance with Wikipedia's Conflict of interest guideline, I disclose that I have a conflict of interest regarding the subject of this article. Reyoza (talk) 18:53, 30 July 2026 (UTC)
Institute of Physical Chemistry, Russian Academy of Sciences (Ph.D.)
Gennady Verkhivker | |
|---|---|
| Born | Gennady M. Verkhivker Odesa, Ukrainian SSR, Soviet Union |
| Citizenship | United States |
| Education | Lomonosov Moscow State University (M.S.) Institute of Physical Chemistry, Russian Academy of Sciences (Ph.D.) |
| Known for | Structure-based drug design; molecular docking; computational studies of allosteric regulation in proteins |
| Scientific career | |
| Fields | Computational biology, biophysics, bioinformatics, drug discovery |
| Workplaces | Chapman University University of California, San Diego University of Kansas Pfizer Agouron Pharmaceuticals |
| Website | www |
Early life and education
Verkhivker was born in Odesa, then part of the Soviet Union.[2] He earned a Master of Science degree in physics and chemistry from Lomonosov Moscow State University and a Ph.D. in physical chemistry from the Institute of Physical Chemistry of the Russian Academy of Sciences in Moscow in 1989.[2] He subsequently emigrated to the United States and completed a postdoctoral fellowship in computational biophysics at the University of Illinois at Chicago from 1990 to 1992.[2][1]
Career
Industry
In the early 1990s Verkhivker joined Agouron Pharmaceuticals in San Diego, California, one of the early biotechnology companies to pursue structure-based drug design.[4] While at Agouron, he co-authored computational studies of ligand–protein docking and lead discovery, including work on flexible docking methods applied to inhibitors of HIV-1 protease and on energy-landscape approaches to identifying molecular "anchor" fragments in drug design.[4][5][6] He subsequently held research and management positions at Warner-Lambert and, following its acquisition by Pfizer, at Pfizer Global Research and Development in La Jolla, California, where his roles included director of structure-based drug design.[7][2]
Academia
Since 2002, Verkhivker has held a secondary appointment as adjunct professor of pharmacology at the Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego.[1][2] In 2006 he joined the School of Pharmacy and Center for Bioinformatics at the University of Kansas as a full professor of pharmaceutical chemistry and bioinformatics.[2][1] In 2011 he moved to Chapman University in Orange County, California, where he is professor of computational biosciences at the Schmid College of Science and Technology and professor of biomedical and pharmaceutical sciences at the Chapman University School of Pharmacy.[1][2] At Chapman, he leads the Quantitative Biology and Computational Intelligence (QBCI) research group, based at the university's Keck Center for Science and Engineering.[8][9]
Research
Verkhivker's research combines structural and computational biology with machine learning to study the dynamics of proteins, including protein kinases, molecular chaperones such as Hsp70 and Hsp90, KRAS, and the SARS-CoV-2 spike protein, with the aim of identifying allosteric mechanisms and binding sites relevant to drug discovery.[10][3][1] His early work at Agouron Pharmaceuticals with colleagues including Daniel Gehlhaar and Paul Rejto applied concepts from the energy landscape theory of protein folding to problems of ligand–protein recognition and lead discovery, contributing to methods later used in computational structure-based drug design.[4][5][11]
He has authored or co-authored more than 300 peer-reviewed papers and book chapters.[12] As of mid-2026, his publications had received more than 16,000 citations, with an h-index of 61, according to his Google Scholar profile.[13]
His research has received external funding, including a National Institutes of Health-supported project on the structural dynamics of the HIV-1 envelope glycoprotein during viral entry, awarded to Chapman University in 2024.[14]
Editorial and professional activities
Verkhivker has served as a guest editor for special issues of the MDPI journal International Journal of Molecular Sciences, including an issue on computational pharmacology in drug discovery.[15]
Recognition
In 2026, Verkhivker's scholarly work was recognized through Chapman University's Support for Open Access Research and Scholarship (SOARS) program, which assists faculty with publication in open-access journals.[16]
Selected publications
- Gehlhaar, D. K.; Verkhivker, G. M.; Rejto, P. A.; Sherman, C. J.; Fogel, D. B.; Fogel, L. J.; Freer, S. T. (1995). "Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming". Chemistry & Biology. 2 (5): 317–324. doi:10.1016/1074-5521(95)90050-0. PMID 9383433.
- Rejto, P. A.; Verkhivker, G. M. (1996). "Unraveling principles of lead discovery: from unfrustrated energy landscapes to novel molecular anchors". Proceedings of the National Academy of Sciences. 93 (17): 8945–8950. doi:10.1073/pnas.93.17.8945. PMID 8799133. PMC 38574.
- Verkhivker, G. M.; Rejto, P. A. (1996). "A mean field model of ligand–protein interactions: implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding". Proceedings of the National Academy of Sciences. 93 (1): 60–64. doi:10.1073/pnas.93.1.60. PMID 8552675.
- Verkhivker, G. M.; Bouzida, D.; Gehlhaar, D. K.; Rejto, P. A.; Freer, S. T.; Rose, P. W. (2003). "Simulating disorder–order transitions in molecular recognition of unstructured proteins: where folding meets binding". Proceedings of the National Academy of Sciences. 100 (9): 5148–5153. PMID 12697905. PMC 154313.
- Stetz, G.; Verkhivker, G. M. (2017). "Computational analysis of residue interaction networks and coevolutionary relationships in the Hsp70 chaperones: a community-hopping model of allosteric regulation and communication". PLOS Computational Biology. 13 (1): e1005299. doi:10.1371/journal.pcbi.1005299. PMID 28095400.
- Xiao, S.; Verkhivker, G. M.; Tao, P. (2023). "Machine learning and protein allostery". Trends in Biochemical Sciences. 48 (4): 375–390. doi:10.1016/j.tibs.2022.12.001. PMID 36564251.
External links
- Faculty profile at Chapman University
- Verkhivker (QBCI) Lab home page
- Gennady Verkhivker publications indexed by Google Scholar
- ORCID 0000-0002-4507-4471
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