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Comprehensive 3D-RISM analysis of the hydration of small molecule binding sites in ligand-free protein structures.

ABSTRACT: Hydration is a critical factor in the ligand binding process. Herein, to examine the hydration states of ligand binding sites, the three-dimensional distribution function for the water oxygen site, gO (r), is computed for 3,706 ligand-free protein structures based on the corresponding small molecule-protein complexes using the 3D-RISM theory. For crystallographic waters (CWs) close to the ligand, gO (r) reveals that several CWs are stabilized by interaction networks formed between the ligand, CW, and protein. Based on the gO (r) for the crystallographic binding pose of the ligand, hydrogen bond interactions are dominant in the highly hydrated regions while weak interactions such as CH-O are dominant in the moderately hydrated regions. The polar heteroatoms of the ligand occupy the highly hydrated and moderately hydrated regions in the crystallographic (correct) and wrongly docked (incorrect) poses, respectively. Thus, the gO (r) of polar heteroatoms may be used to distinguish the correct binding poses.

SUBMITTER: Yoshidome T

PROVIDER: S-EPMC7540010 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Comprehensive 3D-RISM analysis of the hydration of small molecule binding sites in ligand-free protein structures.

Yoshidome Takashi T Ikeguchi Mitsunori M Ohta Masateru M

Journal of computational chemistry 20200819 28

Hydration is a critical factor in the ligand binding process. Herein, to examine the hydration states of ligand binding sites, the three-dimensional distribution function for the water oxygen site, g<sub>O</sub> (r), is computed for 3,706 ligand-free protein structures based on the corresponding small molecule-protein complexes using the 3D-RISM theory. For crystallographic waters (CWs) close to the ligand, g<sub>O</sub> (r) reveals that several CWs are stabilized by interaction networks formed ...[more]

PMID: 32815201

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Project description:Background Analysis of the 3D structures of protein–ligand binding sites can provide valuable insights for drug discovery. Binding site comparison (BSC) studies can be employed to elucidate the function of orphan proteins or to predict the potential for polypharmacology. Many previous binding site analyses only consider binding sites surrounding an experimentally observed bound ligand. Results To encompass potential protein–ligand binding sites that do not have ligands known to bind, we have incorporated fpocket cavity detection software and assessed the impact of this inclusion on BSC performance. Using fpocket, we generated a database of ligand-independent potential binding sites and applied the BSC tool, SiteHopper, to analyze similarity relationships between protein binding sites. We developed a method for clustering potential binding sites using a curated dataset of structures for six therapeutically relevant proteins from diverse protein classes in the protein data bank. Two clustering methods were explored; hierarchical clustering and a density-based method adept at excluding noise and outliers from a dataset. We introduce circular plots to visualize binding site structure space. From the datasets analyzed in this study, we highlight a structural relationship between binding sites of cationic trypsin and prothrombin, protein targets known to bind structurally similar small molecules, exemplifying the potential utility of objectively and holistically mapping binding site space from the structural proteome. Conclusions We present a workflow for the objective mapping of potential protein–ligand binding sites derived from the currently available structural proteome. We show that ligand-independent binding site detection tools can be introduced without excessive penalty on BSC performance. Clustering combined with intuitive visualization tools can be applied to map relationships between the 3D structures of protein binding sites.Graphical abstract Mapping binding site space. Electronic supplementary material The online version of this article (doi:10.1186/s13321-016-0180-0) contains supplementary material, which is available to authorized users.

Dataset Information

Comprehensive 3D-RISM analysis of the hydration of small molecule binding sites in ligand-free protein structures.

Publications

Comprehensive 3D-RISM analysis of the hydration of small molecule binding sites in ligand-free protein structures.

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