title: A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins.
abstract: We created a computational method to identify allosteric sites using a machine learning method trained and tested on protein structures containing bound ligand molecules. The Random Forest machine learning approach was adopted to build our three-way predictive model. Based on descriptors collated for each ligand and binding site, the classification model allows us to assign protein cavities as allosteric, regular or orthosteric, and hence to identify allosteric sites. 43 structural descriptors per complex were derived and were used to characterize individual protein-ligand binding sites belonging to the three classes, allosteric, regular and orthosteric. We carried out a separate validation on a further unseen set of protein structures containing the ligand 2-(N-cyclohexylamino) ethane sulfonic acid (CHES).
authors: Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK.|Current address: Paul Brear, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.
authors: Ava S-Y
authors: AS
authors: Chen
authors: Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK. njw3@st-andrews.ac.uk.|Current address: Paul Brear, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK. njw3@st-andrews.ac.uk.
authors: Nicholas J
authors: NJ
authors: Westwood
authors: Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK. pdb47@cam.ac.uk.|Current address: Paul Brear, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK. pdb47@cam.ac.uk.
authors: Paul
authors: P
authors: Brear
authors: Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK.|Current address: Paul Brear, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.
authors: Graeme W
authors: GW
authors: Rogers
authors: School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. l.mavridis@qmul.ac.uk.
authors: Lazaros
authors: L
authors: Mavridis
authors: Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK. j.born@st-andrews.ac.uk, syc3@st-andrews.ac.uk.|Current address: Paul Brear, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK. j.born@st-andrews.ac.uk, syc3@st-andrews.ac.uk.
authors: John B O
authors: JB
authors: Mitchell
mesh_terms: D000465:Algorithms; D000495:Allosteric Site; D019295:Computational Biology / Q000379:methods; D030562:Databases, Protein; D000069550:Machine Learning; D008962:Models, Theoretical; D011506:Proteins / Q000737:chemistry* / Q000235:genetics
chemical_list: D011506:Proteins
keywords: Allosteric site; Cheminformatics; Drug Design; Machine Learning; Random Forest