Abstract

The p38 MAP kinases 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. We explore here 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 (or the reference modes of structural changes) inferred from principal component analysis of 134 experimentally resolved p38 kinase structures. ANM-generated conformations are found to provide a significantly better coverage of the inhibitor-bound conformational space observed experimentally, compared to MD simulations performed in explicit water, suggesting that ANM-based sampling of conformations can be advantageously employed as input structural models in docking simulations. 1. Introduction The p38 mitogen-activated protein (MAP) kinase, referred to as p38, is a key signaling protein activated in response to external stress; it regulates the production of proinflammatory cytokines, and as such serves as an important target for the treatment of inflammatory diseases (1). The structure of p38 in the presence of a variety of inhibitors/ligands has been resolved. However, the intrinsic flexibility of the enzyme has been a major challenge in accurate design and docking of potent inhibitors, and the necessity to gain a better understanding of the conformational variability of p38 has been pointed out (2). Our recent analysis of a set of p38 X-ray structures suggests that the structural changes observed in different ligand-bound forms of the enzyme correlate with its conformational motions intrinsically accessible in the ligand-free form (3). Effective generation of a representative set of conformers that would be utilized for flexible docking appears therefore as a feasible task. The development of such efficient tools for generating representative subsets of potentially bound conformers would greatly facilitate computational efforts for drug discovery, not only for this particular family, but for many target proteins, especially in the absence of sufficient structural data on their alternative conformers (4). There is a multitude of approaches at different resolutions for generating conformational ensembles. Molecular