title: Prediction of protein-mannose binding sites using random forest.
abstract: Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a great diversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebinding site is taken to be a sphere around the centroid of the ligand and the sphere is subdivided into different layers and atom wise and residue wise features were extracted for each layer. The method achieves 95.59 % of accuracy using Random Forest with 10 fold cross validation. Prediction of mannose binding site analysis will be quite useful in drug design.
authors.affiliation: Bioinformatics centre, University of Pune, Pune, India.
authors.forename: Harshvardan
authors.initials: H
authors.lastname: Khare
authors.forename: Vivek
authors.initials: V
authors.lastname: Ratnaparkhi
authors.forename: Sonali
authors.initials: S
authors.lastname: Chavan
authors.forename: Valadi
authors.initials: V
authors.lastname: Jayraman