title: SH2 Ligand Prediction-Guidance for In-Silico Screening.
abstract: Systematic identification of binding partners for SH2 domains is important for understanding the biological function of the corresponding SH2 domain-containing proteins. Here, we describe two different web-accessible computer programs, SMALI and DomPep, for predicting binding ligands for SH2 domains. The former was developed using a Scoring Matrix method and the latter based on the Support Vector Machine model.
authors.affiliation: Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 5C1, Canada. sli@uwo.ca.|Children's Health Research Institute, 800 Commissioners Road East, London, ON, N6C 2V5, Canada. sli@uwo.ca.
authors.forename: Shawn S C
authors.initials: SS
authors.lastname: Li
authors.affiliation: Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 5C1, Canada.|Medical College of Qingdao University, Qingdao, 266021, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Li
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D008024:Ligands; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D012984:Software; D064878:Web Browser; D018909:src Homology Domains
chemical_list: D008024:Ligands
keywords: DomPep; Ligand prediction; SH2; SH2-peptide interactions; SMALI