Dr. Gennady Verkhivker
Professor
Schmid College of Science and Technology; Computational and Data Science; School of
Pharmacy
Office Location: Hashinger Science Center 118
Phone: (714) 516-4586
Email: verkhivk@chapman.edu
Website: http://compbiosciences.chapman.edu/
- Scholarly Works:
- Digital Commons
- Education:
- Lomonosov Moscow State University, Bachelor of Science
Lomonosov Moscow State University, Master of Science
Biography
Dr. Verkhivker is currently a Professor of Computational Biology. He is also an Adjunct
Professor of Pharmacology at the Department of Pharmacology, UC San Diego. His research
activities are in the areas of computational cancer biology, translational bioinformatics,
and computational pharmacology. He received his PhD in Physical Chemistry from Moscow
University and completed a postdoctoral fellowship in computational biophysics from
University of Illinois at Chicago. In 2000-2005, Dr. Verkhivker has held various research
and management positions at Pfizer Global Research and Development, San Diego. Since
2002, he has been Adjunct Professor of Pharmacology at the Skaggs School of Pharmacy
and Pharmaceutical Sciences, UC San Diego. In 2006, he joined School of Pharmacy and
Center for Bioinformatics, The University of Kansas as a Professor of Pharmaceutical
Chemistry and Bioinformatics. Dr. Verkhivker returned to California in 2011 and joined
Chapman University in August 2011 as a Full Professor of Computational Biology. Upon
arrival to Chapman, Dr. Verkhivker has established a dynamic research group engaged
in translational research that attracted a large cohort of undergraduate and graduate
students. He has been involved in various global University initiatives and collaborations.
Dr. Verkhivker has served on a number of important committees including Search Committee
for new Found Dean of BioPharmacy School. He is also chairing the Doctoral Steering
Committee of the newly approved PhD Graduate Program in Computational Sciences.
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Recent Creative, Scholarly Work and Publications
- Raisinghani N, Parikh V, Foley B, Verkhivker G. Assessing Structures and Conformational Ensembles of Apo and Holo Protein States Using Randomized Alanine Sequence Scanning Combined with Shallow Subsampling in AlphaFold2 : Insights and Lessons from Predictions of Functional Allosteric Conformations. bioRxiv. 2024 Nov 6:2024.11.04.621947. doi: 10.1101/2024.11.04.621947.
- Raisinghani N, Alshahrani M, Gupta G, Tian H, Xiao S, Tao P, Verkhivker G. Probing Functional Allosteric States and Conformational Ensembles of the Allosteric Protein Kinase States and Mutants: Atomistic Modeling and Comparative Analysis of AlphaFold2, OmegaFold, and AlphaFlow Approaches and Adaptations.J Phys Chem B. 2024 Nov 14;128(45):11088-11107. doi: 10.1021/acs.jpcb.4c04985.
- Raisinghani N, Alshahrani M, Gupta G, Xiao S, Tao P, Verkhivker G. AlphaFold2-Enabled Atomistic Modeling of Structure, Conformational Ensembles and Binding Energetics of the SARS-CoV-2 Omicron BA.2.86 Spike Protein with ACE2 Host Receptor and Antibodies: Compensatory Functional Effects of Binding Hotspots in Modulating Mechanisms of Receptor Binding and Immune Escape. J. Chem Inf Model. 2023 accepted, in press
- Xiao S, Ibrahim MT, Verkhivker GM, Zoltowski BD, Tao P. ß-sheets mediate the conformational change and allosteric signal transmission between the As LOV2 termini. J. Comput. Chem. 2023, accepted, in press
- Verkhivker G. Computational Modeling and Engineering of Allosteric Regulatory Mechanisms in Signaling Proteins: Integration of Multiscale Simulations, Network Biology and Machine Learning. Biophysical journal. 2020 February; 118(3):206A. doi: https://doi.org/10.1016/j.bpj.2019.11.1238.
- Generative Machine Learning Models for Discovery of selective chemical probes to interrogate protein kinase mechanisms. Agajanian S, Oluyemi O, Verkhivker GM. Nature Communications, Submitted 2019