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A flexible volumetric comparison of protein cavities can reveal patterns in ligand binding specificity

Published: 20 September 2014 Publication History

Abstract

Conformational flexibility is an underlying cause of error in all comparisons of protein structure. Using flexible representations, some comparison algorithms can identify subtle functional similarities among distantly related proteins even when they exhibit different backbone conformations. The same techniques are not designed to identify subtle variations among closely related proteins that might cause differences in specificity. In such cases, molecular flexibility obscures structural details that influence the specific recognition of similar but non-identical ligands.
To enhance the analysis of ligand binding specificity, this paper presents FAVA (Flexible Aggregate Volumetric Analysis), a conformationally robust tool for comparing similar binding cavities with different binding preferences. FAVA examines a large number of conformational samples to characterize local flexibility using Constructive Solid Geometry. Using molecular dynamics simulations as a source for conformational samples, we used FAVA to analyze a nonredundant sample of serine protease and enolase structures. Different snapshots from the same proteins exhibited significant variations in binding cavity shape. Nonetheless, analysis with FAVA revealed subfamilies with different binding preferences. FAVA also identified amino acids associated with differences in binding preferences, predicting established experimental results. These results illustrate a new approach to flexible comparison that uses sampled conformational data. It reveals that detailed comparisons of very similar proteins, such as those within small ligand binding cavities, are possible even in the presence of conformational flexibility. Identifying influences on specificity in this manner points to new applications of protein engineering and drug design.

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Cited By

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  • (2022)Explaining Small Molecule Binding Specificity with Volumetric Representations of Protein Binding SitesAlgorithms and Methods in Structural Bioinformatics10.1007/978-3-031-05914-8_2(17-45)Online publication date: 28-Apr-2022
  • (2016)A map of binding cavity conformations reveals differences in binding specificity2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM.2016.7822486(13-19)Online publication date: Dec-2016
  • (2015)Predicting protein-ligand binding specificity based on ensemble clusteringProceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM.2015.7359858(1239-1245)Online publication date: 9-Nov-2015
  • Show More Cited By

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        cover image ACM Conferences
        BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
        September 2014
        851 pages
        ISBN:9781450328944
        DOI:10.1145/2649387
        • General Chairs:
        • Pierre Baldi,
        • Wei Wang
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        Published: 20 September 2014

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        View all
        • (2022)Explaining Small Molecule Binding Specificity with Volumetric Representations of Protein Binding SitesAlgorithms and Methods in Structural Bioinformatics10.1007/978-3-031-05914-8_2(17-45)Online publication date: 28-Apr-2022
        • (2016)A map of binding cavity conformations reveals differences in binding specificity2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM.2016.7822486(13-19)Online publication date: Dec-2016
        • (2015)Predicting protein-ligand binding specificity based on ensemble clusteringProceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM.2015.7359858(1239-1245)Online publication date: 9-Nov-2015
        • (2015)Conformational Sampling Reveals Amino Acids with a Steric Influence on SpecificityJournal of Computational Biology10.1089/cmb.2015.011722:9(861-875)Online publication date: Sep-2015
        • (2014)Variational Bayesian clustering on protein cavity conformations for detecting influential amino acidsProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/2649387.2660837(703-710)Online publication date: 20-Sep-2014

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