A reverse combination of structure-based and ligand-based strategies for virtual screening
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A new approach is presented that combines structure- and ligand-based virtual screening in a reverse way. Opposite to the majority of the methods, a docking protocol is first employed to prioritize small ligands (“fragments”) that are subsequently used as queries to search for similar larger ligands in a database. For a given chemical library, a three-step strategy is followed consisting of (1) contraction into a representative, non-redundant, set of fragments, (2) selection of the three best-scoring fragments docking into a given macromolecular target site, and (3) expansion of the fragments’ structures back into ligands by using them as queries to search the library by means of fingerprint descriptions and similarity criteria. We tested the performance of this approach on a collection of fragments and ligands found in the ZINC database and the directory of useful decoys, and compared the results with those obtained using a standard docking protocol. The new method provided better overall results and was several times faster. We also studied the chemical diversity that both methods cover using an in-house compound library and concluded that the novel approach performs similarly but at a much smaller computational cost.
KeywordsFragment screening Structure-based virtual screening Ligand-based virtual screening Docking Drug design
This work was supported by grants from Ministerio de Ciencia e Innovación (MICINN) BIO2008-04384 (to Antonio Morreale) and SAF2009-13914-C02-02 (to Federico Gago), and Comunidad Autónoma de Madrid (CAM) S-BIO-0214-2006 (BIPEDD) and S2010-BMD-2457 (BIPEDD-2). Antonio Morreale acknowledges CAM for financial support to the Fundación Severo Ochoa through the AMAROUTO program. Álvaro Cortés-Cabrera thanks Ministerio de Educación for the FPU Grant AP2009-0203. We are grateful to OpenEye Scientific Software, Inc. for providing us with an academic license for their software. The technical support and advice from the Bioinformatics team at CBMSO is gratefully acknowledged.
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