Predicting protein-protein interfaces as clusters of optimal docking area points.
Desolvation property is used here to predict protein-protein binding sites exploiting the fact that lower-valued 'optimal docking area' ODA (Fernandez-Recio et al., 2005) points form cluster at the interface. The proposed method involves two steps; clustering the ODA points and representing ODA points by average ODA values. On 51 nonredundant proteins, results show the success rate improved considerably. Considering only significant ODA, the previous ODA method has obtained a success rate of 65% with overall success rate of 39%. The proposed method improved the overall success rate to 61%. Further, comparable results were found for X-ray and NMR structures.
Faculty of Medicine, Department of Biochemistry and Molecular Biology, Monash University, VIC 3800, Australia. yasir.arafat@med.monash.edu.au
Yasir
Y
Arafat
Joarder
J
Kamruzzaman
Gour C
GC
Karmakar
Juan
J
Fernandez-Recio
D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D008956:Models, Chemical; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000648:ultrastructure; D020539:Sequence Analysis, Protein / Q000379:methods*
D011506:Proteins