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CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

[Image: see text] A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged w...

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Autores principales: Dunbar, James B., Smith, Richard D., Yang, Chao-Yie, Ung, Peter Man-Un, Lexa, Katrina W., Khazanov, Nickolay A., Stuckey, Jeanne A., Wang, Shaomeng, Carlson, Heather A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2011
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3180202/
https://www.ncbi.nlm.nih.gov/pubmed/21728306
http://dx.doi.org/10.1021/ci200082t
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author Dunbar, James B.
Smith, Richard D.
Yang, Chao-Yie
Ung, Peter Man-Un
Lexa, Katrina W.
Khazanov, Nickolay A.
Stuckey, Jeanne A.
Wang, Shaomeng
Carlson, Heather A.
author_facet Dunbar, James B.
Smith, Richard D.
Yang, Chao-Yie
Ung, Peter Man-Un
Lexa, Katrina W.
Khazanov, Nickolay A.
Stuckey, Jeanne A.
Wang, Shaomeng
Carlson, Heather A.
author_sort Dunbar, James B.
collection PubMed
description [Image: see text] A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged with organizing community-wide exercises based on the collected data. The first of these exercises was aimed to gauge the overall state of docking and scoring, using a large and diverse data set of protein–ligand complexes. Participants were asked to calculate the affinity of the complexes as provided and then recalculate with changes which may improve their specific method. This first data set was selected from existing PDB entries which had binding data (K(d) or K(i)) in Binding MOAD, augmented with entries from PDBbind. The final data set contains 343 diverse protein–ligand complexes and spans 14 pK(d). Sixteen proteins have three or more complexes in the data set, from which a user could start an inspection of congeneric series. Inherent experimental error limits the possible correlation between scores and measured affinity; R(2) is limited to ∼0.9 when fitting to the data set without over parametrizing. R(2) is limited to ∼0.8 when scoring the data set with a method trained on outside data. The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented. Many groups generously participated in improving the data set, and this underscores the value of a supportive, collaborative effort in moving our field forward.
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spelling pubmed-31802022011-09-26 CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes Dunbar, James B. Smith, Richard D. Yang, Chao-Yie Ung, Peter Man-Un Lexa, Katrina W. Khazanov, Nickolay A. Stuckey, Jeanne A. Wang, Shaomeng Carlson, Heather A. J Chem Inf Model [Image: see text] A major goal in drug design is the improvement of computational methods for docking and scoring. The Community Structure Activity Resource (CSAR) aims to collect available data from industry and academia which may be used for this purpose (www.csardock.org). Also, CSAR is charged with organizing community-wide exercises based on the collected data. The first of these exercises was aimed to gauge the overall state of docking and scoring, using a large and diverse data set of protein–ligand complexes. Participants were asked to calculate the affinity of the complexes as provided and then recalculate with changes which may improve their specific method. This first data set was selected from existing PDB entries which had binding data (K(d) or K(i)) in Binding MOAD, augmented with entries from PDBbind. The final data set contains 343 diverse protein–ligand complexes and spans 14 pK(d). Sixteen proteins have three or more complexes in the data set, from which a user could start an inspection of congeneric series. Inherent experimental error limits the possible correlation between scores and measured affinity; R(2) is limited to ∼0.9 when fitting to the data set without over parametrizing. R(2) is limited to ∼0.8 when scoring the data set with a method trained on outside data. The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented. Many groups generously participated in improving the data set, and this underscores the value of a supportive, collaborative effort in moving our field forward. American Chemical Society 2011-07-05 2011-09-26 /pmc/articles/PMC3180202/ /pubmed/21728306 http://dx.doi.org/10.1021/ci200082t Text en Copyright © 2011 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.
spellingShingle Dunbar, James B.
Smith, Richard D.
Yang, Chao-Yie
Ung, Peter Man-Un
Lexa, Katrina W.
Khazanov, Nickolay A.
Stuckey, Jeanne A.
Wang, Shaomeng
Carlson, Heather A.
CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title_full CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title_fullStr CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title_full_unstemmed CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title_short CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
title_sort csar benchmark exercise of 2010: selection of the protein–ligand complexes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3180202/
https://www.ncbi.nlm.nih.gov/pubmed/21728306
http://dx.doi.org/10.1021/ci200082t
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