Abstract

Molecular modeling methodologies such as molecular docking, pharmacophore modeling, and 3D-QSAR, rely on conformational searches of small molecules as a starting point. All of these methodologies seek conformations of the small molecules as they bind to target proteins, i.e., their active conformations. Thus the question as to whether active conformations can be separated from inactive conformations is extremely relevant. In this paper, 3D-descriptors that separate random conformations from active conformations of small molecules are sought. To select appropriate descriptors, 65 protein-ligand complexes were taken from the protein data bank. For each ligand the active conformation was compared to randomly generated low energy conformations. Descriptors such as solvent accessible surface area, number of internal interactions and radius of gyration appear to be useful for separating the active conformations from the random conformations. The results with all these descriptors indicate that active conformations are less compact that random conformations, i.e., they have more solvent accessible surface area, fewer internal interactions and a larger radius of gyration than random conformations. Thus these descriptors could be useful as weights to bias conformational search procedures to conformations more likely to bind to proteins or as filters to eliminate conformations unlikely to bind to any protein.

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