BCL::Conf: small molecule conformational sampling using a knowledge based rotamer library

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Abstract
The interaction of a small molecule with a protein target depends on its ability to adopt a three-dimensional structure that is complementary. Therefore, complete and rapid prediction of the conformational space a small molecule can sample is critical for both structure- and ligand-based drug discovery algorithms such as small molecule docking or three-dimensional quantitative structure–activity relationships. Here we have derived a database of small molecule fragments frequently sampled in experimental structures within the Cambridge Structure Database and the Protein Data Bank. Likely conformations of these fragments are stored as ‘rotamers’ in analogy to amino acid side chain rotamer libraries used for rapid sampling of protein conformational space. Explicit fragments take into account correlations between multiple torsion bonds and effect of substituents on torsional profiles. A conformational ensemble for small molecules can then be generated by recombining fragment rotamers with a Monte Carlo search strategy. BCL::Conf was benchmarked against other conformer generator methods including Confgen, Moe, Omega and RDKit in its ability to recover experimentally determined protein bound conformations of small molecules, diversity of conformational ensembles, and sampling rate. BCL::Conf recovers at least one conformation with a root mean square deviation of 2 Å or better to the experimental structure for 99 % of the small molecules in the Vernalis benchmark dataset. The ‘rotamer’ approach will allow integration of BCL::Conf into respective computational biology programs such as Rosetta.
Funding Information
  • National Institutes of Health (RO1 GM080403, RO1 GM099842, RO1 DK097376)
  • National Science Foundation (CHE 1305874)

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