title: SH3 domain-peptide binding energy calculations based on structural ensemble and multiple peptide templates.
abstract: SH3 domains mediate signal transduction by recognizing short peptides. Understanding of the driving forces in peptide recognitions will help us to predict the binding specificity of the domain-peptide recognition and to understand the molecular interaction networks of cells. However, accurate calculation of the binding energy is a tough challenge. In this study, we propose three ideas for improving our ability to predict the binding energy between SH3 domains and peptides: (1) utilizing the structural ensembles sampled from a molecular dynamics simulation trajectory, (2) utilizing multiple peptide templates, and (3) optimizing the sequence-structure mapping. We tested these three ideas on ten previously studied SH3 domains for which SPOT analysis data were available. The results indicate that calculating binding energy using the structural ensemble was most effective, clearly increasing the prediction accuracy, while the second and third ideas tended to give better binding energy predictions. We applied our method to the five SH3 targets in DREAM4 Challenge and selected the best performing method.
authors.affiliation: Department of Bio and Brain Engineering, KAIST, Daejeon, South Korea.
authors.forename: Seungpyo
authors.initials: S
authors.lastname: Hong
authors.forename: Taesu
authors.initials: T
authors.lastname: Chung
authors.forename: Dongsup
authors.initials: D
authors.lastname: Kim
mesh_terms: D000595:Amino Acid Sequence; D001665:Binding Sites; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry* / Q000378:metabolism; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D013816:Thermodynamics; D018909:src Homology Domains
chemical_list: D010455:Peptides; D011506:Proteins