A distance geometry heuristic for expanding the range of geometries sampled during conformational search |
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Authors: | Izrailev Sergei Zhu Fangqiang Agrafiotis Dimitris K |
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Institution: | Johnson & Johnson Pharmaceutical Research and Development, L.L.C, 665 Stockton Drive, Exton, Pennsylvania 19341, USA. |
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Abstract: | 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. |
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Keywords: | conformational analysis bioactive conformation stochastic proximity embedding distance geometry boosting |
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