Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins.

Charifson, Paul S.; Corkery, Joseph J.; Murcko, Mark A.; Walters, W. Patrick

doi:10.1021/jm990352k

Cited by 698Computational Drug Discovery MethodsProtein Structure and DynamicsCholinesterase and Neurodegenerative Diseases

Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins.

Charifson, Paul S., Corkery, Joseph J., Murcko, Mark A., Walters, W. Patrick·1999·Journal of Medicinal Chemistry

DOI 10.1021/jm990352k

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Abstract

We present the results of an extensive computational study in which we show that combining scoring functions in an intersection-based consensus approach results in an enhancement in the ability to discriminate between active and inactive enzyme inhibitors. This is illustrated in the context of docking collections of three-dimensional structures into three different enzymes of pharmaceutical interest: p38 MAP kinase, inosine monophosphate dehydrogenase, and HIV protease. An analysis of two different docking methods and thirteen scoring functions provides insights into which functions perform well, both singly and in combination. Our data shows that consensus scoring further provides a dramatic reduction in the number of false positives identified by individual scoring functions, thus leading to a significant enhancement in hit-rates.

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Combining different scoring functions in a consensus scoring scheme is a promising data fusion strategy to improve VS enrichment, pose, and affinity prediction.
“The combination of different scoring functions on a scoring scheme (CS) is considered as a promising data fusion strategy to improve VS enrichment, pose, and affinity prediction (Charifson et al., 1999; Bissantz et al., 2000; Yang et al., 2005; Kaserer et al., 2015; Chaput et al., 2016a; Chaput and Mouawad, 2017; Ericksen et al., 2017).”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Charifson et al., 1999

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Authors: Charifson, P. S., Corkery, J. J., Murcko, M. A., & Walters, W. P.
Affiliations: Vertex Pharmaceuticals (United States) (US)
ORCID: Murcko, Mark A.
Walters, W. Patrick
Venue: Journal of Medicinal Chemistry
Publisher: American Chemical Society (ACS)
Published: 1999-11-25
Volume: 42
Issue: 25
Pages: 5100-5109
ISSN: 0022-2623 (ISSN-L)
1520-4804
DOI: 10.1021/jm990352k
OpenAlex: W2071717945
Cited by: 698
References: 36
Citations by year: 2026: 10 · 2025: 6 · 2024: 24 · 2023: 22 · 2022: 20 · 2021: 24 · 2020: 19 · 2019: 22 · 2018: 17 · 2017: 18 · 2016: 27 · 2015: 25 · 2014: 20 · 2013: 30 · 2012: 28
FWCI: 27.91
Type: journal article
Language: en
Open access: closed
Locations: Journal of Medicinal Chemistry (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Health Sciences › Medicine › Pharmacology › Cholinesterase and Neurodegenerative Diseases
Keywords: consensus scoring, docking scoring functions, virtual screening, hit rate, enzyme inhibitors, p38 MAPK, inosine monophosphate dehydrogenase, HIV protease, false positives
MeSH terms: Algorithms, IMP Dehydrogenase, Protein Conformation, Databases, Factual, HIV Protease, Mitogen-Activated Protein Kinases, p38 Mitogen-Activated Protein Kinases

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Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins.

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