Evidence map›Paper›PMID 26082804›Full record

ArticleJournal of cheminformatics2015

Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets.

Wei P Feinstein, Michal Brylinski

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Article in Journal of cheminformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers.

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104citing papers in PubMed
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3 · Its place in the literature

Who cites it

104 citing papers in PubMed.

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  8. Evaluating generalization in protein-ligand cofolding methods.Nature structural & molecular biology · 2026
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44 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Wei P FeinsteinDepartment of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 USA ; Center for Computation & Technology, Louisiana State University, Baton Rouge, LA 70803 USA.
Michal BrylinskiDepartment of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 USA ; Center for Computation & Technology, Louisiana State University, Baton Rouge, LA 70803 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputational approaches have emerged as an instrumental methodology in modern research. For example, virtual screening by molecular docking is routinely used in computer-aided drug discovery. One of the critical parameters for ligand docking is the size of a search space used to identify low-energy binding poses of drug candidates. Currently available docking packages often come with a default protocol for calculating the box size, however, many of these procedures have not been systematically evaluated.

methodsIn this study, we investigate how the docking accuracy of AutoDock Vina is affected by the selection of a search space. We propose a new procedure for calculating the optimal docking box size that maximizes the accuracy of binding pose prediction against a non-redundant and representative dataset of 3,659 protein-ligand complexes selected from the Protein Data Bank. Subsequently, we use the Directory of Useful Decoys, Enhanced to demonstrate that the optimized docking box size also yields an improved ranking in virtual screening. Binding pockets in both datasets are derived from the experimental complex structures and, additionally, predicted by eFindSite.

resultsA systematic analysis of ligand binding poses generated by AutoDock Vina shows that the highest accuracy is achieved when the dimensions of the search space are 2.9 times larger than the radius of gyration of a docking compound. Subsequent virtual screening benchmarks demonstrate that this optimized docking box size also improves compound ranking. For instance, using predicted ligand binding sites, the average enrichment factor calculated for the top 1 % (10 %) of the screening library is 8.20 (3.28) for the optimized protocol, compared to 7.67 (3.19) for the default procedure. Depending on the evaluation metric, the optimal docking box size gives better ranking in virtual screening for about two-thirds of target proteins.

conclusionsThis fully automated procedure can be used to optimize docking protocols in order to improve the ranking accuracy in production virtual screening simulations. Importantly, the optimized search space systematically yields better results than the default method not only for experimental pockets, but also for those predicted from protein structures. A script for calculating the optimal docking box size is freely available at www.brylinski.org/content/docking-box-size. Graphical AbstractWe developed a procedure to optimize the box size in molecular docking calculations. Left panel shows the predicted binding pose of NADP (green sticks) compared to the experimental complex structure of human aldose reductase (blue sticks) using a default protocol. Right panel shows the docking accuracy using an optimized box size.

Indexed as

AutoDock VinaDocking box sizeDocking protocolsLigand binding site predictionLigand virtual screeningMolecular dockingSearch space

Identifiers

PMID26082804
PMCPMC4468813

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.