Verkhivker Lab

Complex biophysical processes such as protein folding and molecular recognition underlie the function of all biological systems, which are characterized by remarkable structural complexity at all levels of organization. The challenge of understanding biological systems at the molecular level and the systems level is what motivates my research. In our laboratory work is undertaken in areas of protein structure modeling and dynamics, structural bioinformatics, computational proteomics and chemical genomics, ligand-protein docking, and structural systems biology.

The overarching goal of the research is to enhance quantitative understanding of protein structure, dynamics and binding in complex biomolecular networks and develop integrated computational approaches and tools for predicting molecular signatures of human disease and translational research.

Major areas of research:

• Computer simulation and bioinformatics methods in exploring mechanisms of coupling between protein folding and binding in signal transduction interaction networks
• Computational proteomics and computational chemical genomics approaches in studies of protein kinases and nuclear receptors binding with ligands and interacting proteins
• Structural systems biology analysis of protein kinases binding with SH2 and PTB domains in kinase cascades and signal transduction pathways
• Computational pharmacogenetics: development computational tools for molecular fingerprinting the effects of genetic variations on the protein structure and dynamics and in silico drug discovery
• Structure-based design of molecularly-targeted cancer and diabetes therapeutics based on computational proteomics and chemical genomics studies

Representative Publications

• G. Verkhivker, P. Rejto, A mean field model of ligand-protein interactions: Implications for the structural assessment of HIV-1 protease complexes and receptor-specific binding, Proc. Natl. Acad. Sci. USA 93:  60-64, 1996.
• P. Rejto, G. Verkhivker, Unraveling principles of lead discovery: from unfrustrated energy landscapes to novel molecular anchors, Proc. Nathl. Acad. Sci. USA 93 : 8945-8950, 1996.
• L. Schaffer, G. Verkhivker Predicting structural effects in HIV-1 protease mutant complexes with flexible ligand docking and protein side-chain optimization, Proteins: Struct. Funct. Genet.  33(2): 1-16, 1998.
• G. M. Verkhivker, D. Bouzida, D. K. Gehlhaar, P.A. Rejto, S. Arthurs, A. B. Colson, S.T. Freer, V. Larson, B. A. Luty, T. Marrone and P. W. Rose, Deciphering common failures in molecular docking of ligand—protein complexes, J. Comput.-- Aided Mol. Des. 14 (8): 731-751, 2000.
• G. M. Verkhivker, D. Bouzida, D. K. Gehlhaar, P.A. Rejto, S.T. Freer, and P. W. Rose, Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective, Curr.  Opin.  Struct.  Biol, 12 (2) :  197-203, 2002.
• G. M. Verkhivker, D. Bouzida, D. K. Gehlhaar, P.A. Rejto, S.T. Freer, and P. W. Rose, Monte Carlo simulations of the peptide binding at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface, Proteins: Struct. Funct. Genet. , 48 : 539-557, 2002.
• G. M. Verkhivker, D. Bouzida, D. K. Gehlhaar, P.A. Rejto, S.T. Freer Simulating  disorder—order transitions in molecular recognition of unstructured proteins: Where folding meets binding , Proc. Natl. Acad. Sci, USA,  100:  5148-5153, 2003.
• J. Wang, G.M. Verkhivker, Energy Landscape Theory, Funnels, Specificity, and Optimal Criterion of Biomolecular Binding, Phys. Rev. Lett.  V. 90, N18,  188101-188104, 2003  
• G. M. Verkhivker, D. Bouzida, D. K. Gehlhaar, P.A. Rejto, S.T. Freer, P. W. Rose, Computational detection of the binding site hot spot at the remodeled human growth hormone-receptor interface, Proteins: Struct. Funct. Genet,  53, 201-219, 2003.
• G. M. Verkhivker, Protein conformational transitions  coupled to binding in molecular recognition of unstructured proteins : Hierarchy of structural loss from all-atom Monte Carlo simulations of p27 unfolding–unbinding and structural  determinants of the Binding Mechanism, Biopolymers, 75, p.420-433, 2004  
• G. M. Verkhivker, Protein conformational transitions  coupled to binding in molecular recognition of unstructured proteins : Deciphering the role of intermolecular  interactions in computational structure prediction  of the p27 protein bound to the cyclin A-cyclin- dependent kinase 2 complex. Proteins: Struct. Funct.  Bionformatics, 58, 706-716, 2005
• G. M. Verkhivker, Imprint of evolutionary conservation and protein structure variation on the binding function of protein tyrosine kinases.  Bioinformatics, 2006, 22,1846-1854.
• G. M. Verkhivker, Computational proteomics of  biomolecular interactions in the sequence and structure space of the tyrosine kinome : deciphering the molecular basis of the kinase inhibitors selectivity, Proteins: Struct. Funct. Bionformatics, 2006, in press
• G.M. Verkhivker  In silico profiling of tyrosine kinases binding specificity and drug resistance using replica--exchange Monte Carlo simulations with ensembles of protein conformations, Biopolymers, 2006, in press
• Yongliang Yang, Wei Yang, Dale G. Drueckhammer, G.M. Verkhivker, Jin Wang  Quantifying intrinsic specificity provides a possibility of  two–dimensional drug screening with both affinity and specificity, Proc. Natl. Acad. Sci, USA, in press