Chapman University - Computational Biology Sciences

Molecular Recognition and Energy Landcapes

• Dixit, AG. Verkhivker  The energy landscape analysis of cancer mutations in protein kinases.PLoS One. 2011;6(10):e26071. Epub 2011 Oct 6  [pdf]
• Torkamani A, Verkhivker G, Schork NJ.Cancer driver mutations in protein kinase genes.Cancer Lett.  281(2):117-127, 2009. [pdf]

Protein Kinases: Sturcture, Dynamics and Drug Design

• Dixit A, Verkhivker GM.Hierarchical modeling of activation mechanisms in the ABL and EGFR kinase domains: thermodynamic and mechanistic catalysts of kinase activation by cancer mutations.PLoS Comput. Biol. 5(8):e1000487, 2009.[pdf]
• A. Dixit, , G. Verkhivker.  Computational Modeling of Allosteric Communication Reveals Organizing Principles of Mutation-Induced Signaling in ABL and EGFR   Kinases.PLoS Comput Biol. 2011 Oct;7(10):e1002179. Epub 2011 Oct 6.[pdf]

Hsp90 Molecular Chaperone: Structure, Dynamics and Drug Design

• Colombo G, Morra G, Meli M, Verkhivker G. Understanding ligand-based modulation of the Hsp90   molecular chaperone dynamics at atomic resolution. Proc   Natl Acad Sci USA. 2008 Jun 10; 105(23): 7976-81. Epub 2008 May 29. PMID: 18511558 [pdf]
• Morra G, Verkhivker G, Colombo G. Modeling signal propagation mechanisms and ligand-based conformational dynamics of the Hsp90 molecular chaperone full-length dimer.PLoS Comput. Biol. 5(3):e1000323, 2009.[pdf]
• Verkhivker GM, Dixit A, Morra G, Colombo G.Structural and computational biology of the molecular chaperone Hsp90: from understanding molecular mechanisms to computer-based inhibitor design.Curr. Top. Med. Chem. 9:1369-1385, 2009.[pdf]
• G. Morra, M. A. C. Neves, C. J. Plescia, S. Tsustsumi, L. Neckers, G.M. Verkhivker, D. C. Altieri, G. Colombo. Dynamics-Based Discovery of Allosteric Inhibitors: Selection of New Ligands for the C-terminal Domain of Hsp90”J. Chem. Theory Comput., 6: 2978–2989, 2010.[pdf]
• R. L. Matts, A. Dixit, L.B. Peterson, L. Sun, S. Voruganti, . Kalyanaraman, S. D. Hartson, G. M. Verkhivker, B. S. J. Blagg. Elucidation and assessment of the Hsp90 C-terminal inhibitor binding site.  ACS Chem Biol. 2011 Aug 19;6(8):800-7. Epub 2011 May 17.[pdf]

Computational Biology and Translational Bioinformatics in Cancer Research: From Understanding Genetic and Molecular Signatures of Human Disease to Personalized Medicine.
The challenge of understanding biological systems at the molecular and systems level as well as the integration of   computational   and experimental approaches for bridging basic and clinical cancer research is what motivates our vibrant  research group. Our  scientific interests and research efforts are in the areas of Computational  Cancer Biology and Pharmacogenetics, Computational Genomics and Pharmacology, Translational Bioinformatics and Computational Medicine   with the focus  on the development and  integration of computational and experimental  approaches for (a) system-based analysis of evolutionary, genetic, molecular and clinical signatures associated with human disease; (b) modeling of complex phenotypes  and prediction of cancer biomarkers;  (c)  design and discovery of targeted and personalized cancer therapeutics  and development of expert systems for personalized medicine;  (d) integration of  computational biology and translational  informaticswith   chemical biology and  chemical genomics in translational cancer research; (e) enabling   information-driven biomedical  research  on the “bench to bedside” path.