Predicting the Accuracy of Protein–Ligand Docking on Homology Models

By A. Bordogna, A. Pandini, L. Bonati. 2011

91 citations recorded by the source corpus.

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

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

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Citations in the corpus

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests (2013, methodology): “For example, dRMSD—the distance-based equivalent of RMSD—is used in chemoinformatics to assess differences in ligand poses in binding sites (Bordogna et al ., 2011).”
Latest developments in molecular docking: 2010–2011 in review (2013, methodology): “[148] Templates of varied evolutionary distances and different template-target alignment methods were sampled.”
How accurately can one predict drug binding modes using AlphaFold models? (2023, background): “Improvements in protein structure prediction are widely assumed to lead to better models of ligand binding pockets and thus more accurate predictions of ligand binding (Beuming & Sherman, 2012; Bordogna et al., 2011; Erickson et al., 2004), but to what extent do these assumptions hold?”
Computational protein structure refinement: Almost there, yet still so far to go (2017, background): “72,73 The docking of small molecules is expected to require high structural accuracy near the binding site and preferable models of holo structures since docking to apo structures may not be successful if, e.g., binding sites are occluded.”
Evaluation of AlphaFold2 structures as docking targets (2022, background): “Several survey studies have provided a few guidelines (Bordogna et al., 2011; Fan et al., 2009; McGovern & Shoichet, 2003).”