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A distance geometry heuristic for expanding the range of geometries sampled during conformational search
Author(s) -
Izrailev Sergei,
Zhu Fangqiang,
Agrafiotis Dimitris K.
Publication year - 2006
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20506
Subject(s) - heuristic , sampling (signal processing) , range (aeronautics) , boosting (machine learning) , chemistry , statistical physics , computer science , algorithm , mathematics , physics , materials science , mathematical optimization , artificial intelligence , filter (signal processing) , composite material , computer vision
A recent study of crystal structures of protein–ligand complexes has shown that bioactive conformations tend to be more extended than random ones (Diller and Merz, J. Comput. Aid. Mol. Des. 2002, 16, 105–112). Existing conformational sampling techniques produce molecular conformations with a distribution of geometric sizes that may not cover that of the bioactive conformations. Here, we describe a simple heuristic for biasing the conformational search toward more extended or compact conformations, while maintaining excellent sampling. 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. We demonstrate that this method significantly expands the range of geometric sizes generated during the search and thus increases the efficiency of sampling bioactive conformations. © 2006 Wiley Periodicals, Inc. J Comput Chem, 2006