Book of Abstracts: Albany 2011

category image Albany 2011
Conversation 17
June 14-18 2011
©Adenine Press (2010)

Computational Generation of Inhibitor-bound Conformers of p38 MAP Kinase and Comparison with Experiments

We developed an extensible framework, ProDy, for structure-based analysis of protein dynamics (http://www.csb.pitt.edu/ProDy/). ProDy allows for quantitative analysis of heterogeneous experimental structural datasets and comparison with theoretically predicted conformational dynamics (1). Datasets include structural ensembles composed of a given family or subfamily members, mutants and sequence homologues, in the presence/absence of their substrates, ligands or inhibitors. We demonstrate the utility of ProDy by way of application to exploring the dynamics of p38 MAP kinases, a family of enzymes which play a critical role in regulating stress-activated pathways, and serve as molecular targets for controlling inflammatory diseases. Computer-aided efforts for developing p38 inhibitors have been hampered by the necessity to include the enzyme conformational flexibility in ligand docking simulations. A useful strategy in such complicated cases is to perform ensemble-docking provided that a representative set of conformers is available for the target protein either from computations or experiments. Using ProDy, we explore the abilities of two computational approaches, molecular dynamics (MD) simulations and anisotropic network model (ANM) normal mode analysis, for generating potential ligand-bound conformers starting from the apo state of p38, and benchmark them against the space of conformers inferred from the principal component analysis of 134 experimentally resolved p38 kinase structures (2). The ANM-generated conformations are found to provide a significantly better coverage of the inhibitor-bound conformational space observed in experiments, compared to the conformers generated by MD simulations performed in explicit water. The results suggest that ANM-based sampling of conformations can be advantageously employed for generating structural models to be used as input in docking simulations.

Support from NIH grants 1R01GM086238-01, 5R01GM086238-02 and 5R01LM007994-06 is gratefully acknowledged by I. Bahar.


  1. A. Bakan and I. Bahar. Proc.Natl.Acad.Sci.U.S.A, 106, 14349-14354 (2009).
  2. A. Bakan and I. Bahar. Pacific Symposium on Biocomputing, 16, 181-192 (2011).

Ahmet Bakan
Ivet Bahar

Department of Computational and Systems Biology
School of Medicine
University of Pittsburgh
3501 Fifth Ave, Suite 3064 BST3
Pittsburgh, PA 15260 USA

Ph: (412) 648-3333
Fx: (412) 648-3163