Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods

International Journal of Molecular Sciences

Daniel Barry Roche³  Danielle Allison Brackenridge²  Liam James McGuffin²  Tatyana Karabencheva-Christova¹ 

[1] id="af1-ijms-16-26202">1Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, Montpellier 34095, FranSchool of Biological Sciences, University of Reading, Reading RG6 6AS, UK;;Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, Montpellier 34095, France

关键词: protein–ligand binding site prediction;    protein function prediction;    binding-site residue prediction;    biochemical functional elucidation;    sequence-based function prediction;    structure-based function prediction;    biological and biochemical role of enzymes;    gene Ontology;    enzyme commission numbers;   

DOI  :  10.3390/ijms161226202

来源: mdpi

【 摘 要 】

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.