ConfGen: A Conformational Search Method for Efficient Generation of Bioactive Conformers

We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reason...

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Bibliographic Details
Published in:	Journal of chemical information and modeling Vol. 50; no. 4; pp. 534 - 546
Main Authors:	Watts, K. Shawn, Dalal, Pranav, Murphy, Robert B, Sherman, Woody, Friesner, Rich A, Shelley, John C
Format:	Journal Article
Language:	English
Published:	Washington, DC American Chemical Society 26-04-2010
Subjects:	Atoms & subatomic particles Biological and medical sciences Computational Biology Computational Chemistry Crystal structure Drug Evaluation, Preclinical General pharmacology Heuristic Ligands Medical sciences Models, Molecular Molecular Conformation Pharmacology. Drug treatments Physicochemical properties. Structure-activity relationships Physics Software Time Factors Test validation High resolution Heuristic method Crystal lattice Parameterization Modeling Pharmacophore Biological activity Search algorithm Conformation Crystalline structure
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Summary:	We describe the methodology, parametrization, and application of a conformational search method, called ConfGen, designed to efficiently generate bioactive conformers. We define efficiency as the ability to generate a bioactive conformation within a small total number of conformations using a reasonable amount of computer time. The method combines physics-based force field calculations with empirically derived heuristics designed to achieve efficient searching and prioritization of the ligand’s conformational space. While many parameter settings are supported, four modes spanning a range of speed and quality trades-offs are defined and characterized. The validation set used to test the method is composed of ligands from 667 crystal structures covering a broad array of target and ligand classes. With the fastest mode, ConfGen uses an average of 0.5 s per ligand and generates only 14.3 conformers per ligand, at least one of which lies within 2.0 Å root-mean-squared deviation of the crystal structure for 96% of the ligands. The most computationally intensive mode raises this recovery rate to 99%, while taking 8 s per ligand. Combining multiple search modes to “fill-in” holes in the conformation space or energy minimizing using an all-atom force field each lead to improvements in the recovery rates at higher resolutions. Overall, ConfGen is at least as good as competing programs at high resolution and demonstrates higher efficiency at resolutions sufficient for many downstream applications, such as pharmacophore modeling.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1549-9596 1549-960X
DOI:	10.1021/ci100015j