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J Comput Chem. 2014 Sep 30;35(25):1824-34. doi: 10.1002/jcc.23690. Epub 2014 Jul 22.

Shape-based virtual screening with volumetric aligned molecular shapes.

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Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.


Shape-based virtual screening is an established and effective method for identifying small molecules that are similar in shape and function to a reference ligand. We describe a new method of shape-based virtual screening, volumetric aligned molecular shapes (VAMS). VAMS uses efficient data structures to encode and search molecular shapes. We demonstrate that VAMS is an effective method for shape-based virtual screening and that it can be successfully used as a prefilter to accelerate more computationally demanding search algorithms. Unique to VAMS is a novel minimum/maximum shape constraint query for precisely specifying the desired molecular shape. Shape constraint searches in VAMS are particularly efficient and millions of shapes can be searched in a fraction of a second. We compare the performance of VAMS with two other shape-based virtual screening algorithms a benchmark of 102 protein targets consisting of more than 32 million molecular shapes and find that VAMS provides a competitive trade-off between run-time performance and virtual screening performance.


GSS tree; molecular shape; shape constraints; shape indexing; virtual screening

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