Consensus scoring with feature selection for structure-based virtual screening.

Consensus scoring with feature selection for structure-based virtual screening. Research Abstract Details 

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Consensus scoring with feature selection for structure-based virtual screening. Abstract Text:

The evaluation of ligand conformations is a crucial aspect of structure-based virtual screening, and scoring functions play significant roles in it. While consensus scoring (CS) generally improves enrichment by compensating for the deficiencies of each scoring function, the strategy of how individual scoring functions are selected remains a challenging task when few known active compounds are available. To address this problem, we propose feature selection-based consensus scoring (FSCS), which performs supervised feature selection with docked native ligand conformations to select complementary scoring functions. We evaluated the enrichments of five scoring functions (F-Score, D-Score, PMF, G-Score, and ChemScore), FSCS, and RCS (rank-by-rank consensus scoring) for four different target proteins: acetylcholine esterase (AChE), thrombin (thrombin), phosphodiesterase 5 (PDE5), and peroxisome proliferator-activated receptor gamma (PPARgamma). The results indicated that FSCS was able to select the complementary scoring functions and enhance ligand enrichments and that it outperformed RCS and the individual scoring functions for all target proteins. They also indicated that the performances of the single scoring functions were strongly dependent on the target protein. An especially favorable result with implications for practical drug screening is that FSCS performs well even if only one 3D structure of the protein-ligand complex is known. Moreover, we found that one can infer which scoring functions significantly enrich active compounds by using feature selection before actual docking and that the selected scoring functions are complementary.

Consensus scoring with feature selection for structure-based virtual screening. Publishing Authors By Initials

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MEDLINE DATE: 2008 Mar-Apr

Consensus scoring with feature selection for structure-based virtual screening. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Journal of chemical information and modeling

VOLUME: 48

Page Numbers: 288-95

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ISSN: 1549-9596

DAY: 30

MONTH: 01

YEAR: 2008

Consensus scoring with feature selection for structure-based virtual screening. Information

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LANGUAGE: eng

NlmUniqueID: 101230060

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Grant and Affiliation Information for Consensus scoring with feature selection for structure-based virtual screening.

AFFILIATION: Bio-IT Center and Nano Electronics Research Laboratories, NEC Corporation, 34, Miyukigaoka, Tsukuba, Ibaraki 305-8501, Japan.

Country: United States

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MEDLINETA: J Chem Inf Model

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