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

Daniel Roche 1 Danielle Allison Brackenridge 2 Liam James Mcguffin 2
1 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : 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.
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Article dans une revue
International Journal of Molecular Sciences, MDPI, 2015, 16 (12), pp.29829-29842. 〈10.3390/ijms161226202〉
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Soumis le : vendredi 11 mars 2016 - 17:48:22
Dernière modification le : jeudi 24 mai 2018 - 15:59:22

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Daniel Roche, Danielle Allison Brackenridge, Liam James Mcguffin. Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods. International Journal of Molecular Sciences, MDPI, 2015, 16 (12), pp.29829-29842. 〈10.3390/ijms161226202〉. 〈lirmm-01287102〉

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