A self-organizing algorithm for generating biologically active conformations

CINF 25

Sergei Izrailev, 3-Dimensional Pharmaceuticals, Inc, 8 Clarke Drive, Cranbury, NJ 08512, Huafeng Xu, Department of Pharmaceutical Chemistry, University of California San Francisco, San Francsico, CA 94107, and Dimitris K. Agrafiotis, Johnson & Johnson Pharmaceutical Research & Development, L.L.C, 665 Stockton Drive, Exton, PA 19341.
Conformational sampling of small molecule structures has been a widely used technique in structure-based drug design and virtual screening. A stochastic algorithm for conformational sampling is presented. The algorithm generates molecular conformations that are consistent with a set of geometric constraints, which include interatomic distance bounds and chiral volumes derived from the molecular connectivity table. The algorithm repeatedly selects individual geometric constraints at random and updates the respective atomic coordinates toward satisfying the chosen constraint. The ability of the algorithm to generate low-energy and biologically active conformations is discussed.