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In silico Identification and Characterization of Protein-Ligand Binding Sites

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Computational Design of Ligand Binding Proteins

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1414))

Abstract

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

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Acknowledgements

Daniel Barry Roche is a recipient of a Young Investigator Fellowship from the Institut de Biologie Computationnelle, Université de Montpellier (ANR Investissements D’Avenir Bio-informatique: projet IBC).

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Authors and Affiliations

  1. Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, 860 rue de St Priest, 34095, Montpellier, France

    Daniel Barry Roche

  2. Centre de Recherche en Biologie cellulaire de Montpellier, CNRS-UMR 5237, 1919 Route de Mende, Montpellier, 34293, France

    Daniel Barry Roche

  3. School of Biological Sciences, University of Reading, Reading, RG6 6AS, UK

    Liam James McGuffin

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  1. Daniel Barry Roche
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  2. Liam James McGuffin
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Correspondence to Daniel Barry Roche .

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Editors and Affiliations

  1. Division of Basic Sciences, Fred Hutchinson Cancer Research Cen, Seattle, Washington, USA

    Barry L. Stoddard

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Roche, D.B., McGuffin, L.J. (2016). In silico Identification and Characterization of Protein-Ligand Binding Sites. In: Stoddard, B. (eds) Computational Design of Ligand Binding Proteins. Methods in Molecular Biology, vol 1414. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3569-7_1

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  • DOI: https://doi.org/10.1007/978-1-4939-3569-7_1

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3567-3

  • Online ISBN: 978-1-4939-3569-7

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