Summary: RESEARCH FRONT
Aust. J. Chem. 2006, 59, 874878 www.publish.csiro.au/journals/ajc
Dimitris K. Agrafiotis,A,D Alan Gibbs,A Fangqiang Zhu,A
Sergei Izrailev,A,B and Eric MartinC
A Johnson & Johnson Pharmaceutical Research & Development, 665 Stockton Drive, Exton, PA 19341, USA.
B Current address: Fortress Investment Group, 1345 Avenue of the Americas, New York, NY 10105, USA.
C Chiron Corporation, 4560 Horton Street, Emeryville, CA 94608, USA.
D Corresponding author. Email: firstname.lastname@example.org
Stochastic proximity embedding (SPE) is a novel self-organizing algorithm for sampling conformational space
using geometric constraints derived from the molecular connectivity table. Here, we describe a simple heuristic
that can be used in conjunction with SPE to bias the conformational search towards more extended or compact
conformations, and thus greatly expand the range of geometries sampled during the search. The method uses a
boosting strategy to generate a series of conformations, each of which is at least as extended (or compact) as the
previous one. The approach is compared to several popular conformational sampling techniques using a reference
set of 59 bioactive ligands extracted from the Protein Data Bank, and is shown to be significantly more effective in
sampling the full range of molecular radii, with the exception of the Catalyst program, which was equally effective.
Manuscript received: 21 June 2006.
Final version: 21 October 2006.