Predicting the accuracy of protein–ligand docking on homology models
Open accessAbstract
Ligand–protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large‐scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand–protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target–template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state‐of‐the‐art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010
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Early computational approaches suffered limitations from the use of apo template structures for homology modeling and from neglecting the ligand induced fit effect on the protein conformation.
“However, these early computational approaches suffered from several known limitations given by the use of apo template structures for homology modeling and the neglecting of the ligand induced fit effect on the protein conformation22,23.”
From Modeling the binding of diverse ligands within the Ah receptor ligand binding domain (2019) · cites this paper as [22]
The Discussion (page unavailable) identifies the failure to account for binding-site changes upon ligand binding as a docking limitation, and says the authors did not use protein side-chain flexibility. The Results, “Test Set Variety” (page unavailable), says the templates included both apo and holo structures, but does not establish that using apo templates was a limitation of the early approaches described in the claim. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe accuracy of binding geometries predicted by molecular docking to homology models strongly depends on the quality of the model, particularly in the binding site.
“The accuracy of the binding geometries predicted by molecular docking to homology models strongly depends on the quality of the model, particularly in the binding site22,40,41.”
From Modeling the binding of diverse ligands within the Ah receptor ligand binding domain (2019) · cites this paper as [22]
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“Provided a scoring function achieves enrichment of bioactive compounds against a protein target (which can be established on existing datasets where data is available, but where otherwise estimates can be made based on the character of the binding pocket and protein type [38, 39]), then the chemical space to be scored…”
BackgroundLow-resolution structural modeling of protein interactome
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- Authors
- Bordogna, A., Pandini, A., & Bonati, L.
- Affiliations
- University of Milano-Bicocca (IT)
- National Institute for Medical Research (GB)
- Corresponding author
- Bonati, Laura
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2010-11-17
- Volume
- 32
- Issue
- 1
- Pages
- 81-98
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- PMC
- PMC3057020
- OpenAlex
- W2111143975
- Cited by
- 107
- References
- 56
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 11 · 2023: 10 · 2022: 8 · 2021: 12 · 2020: 6 · 2019: 7 · 2018: 6 · 2017: 8 · 2016: 3 · 2015: 8 · 2014: 2 · 2013: 9 · 2012: 2
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Computational Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- National Institute of Environmental Health Sciences (R01ES007685, ES007685)
- 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
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein-ligand docking, homology modeling, model quality assessment, binding sites, phylogenetic distance, AutoDock, ligand-protein complexes
- MeSH terms
- Binding Sites, Ligands, Models, Molecular, Protein Binding, Proteins, Drug Discovery
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