Molecular Recognition and Energy Landcapes
Protein Kinases: Sturcture, Dynamics and Drug Design
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]
Who We Are
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.