 
Summary: Conformational Sampling by SelfOrganization
Huafeng Xu, Sergei Izrailev, and Dimitris K. Agrafiotis*
3Dimensional Pharmaceuticals, Inc., 665 Stockton Drive, Exton, Pennsylvania 19341
Received March 25, 2003
A new stochastic algorithm for conformational sampling is described. 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. When compared to a conventional distance geometry algorithm based on the same
set of geometric constraints, our method is faster and generates conformations that are more diverse and
more energetically favorable.
INTRODUCTION
Since the physical properties and biological behavior of a
molecule usually depend on its accessible, low energy
conformations, fast and reliable computational methods for
producing such conformations are extremely valuable.1
For
molecules with only a few rotatable bonds, systematic
enumeration of discretized torsions can be used to search
exhaustively for these low energy conformations.25
