SH2 Ligand Prediction-Guidance for In-Silico Screening

Shawn S C Li; Lei Li

doi:10.1007/978-1-4939-6762-9_5

SH2 Ligand Prediction-Guidance for In-Silico Screening

Methods Mol Biol. 2017:1555:77-81. doi: 10.1007/978-1-4939-6762-9_5.

Authors

Shawn S C Li^{1

2}, Lei Li^{3

4}

Affiliations

¹ Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 5C1, Canada. sli@uwo.ca.
² Children's Health Research Institute, 800 Commissioners Road East, London, ON, N6C 2V5, Canada. sli@uwo.ca.
³ Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 5C1, Canada.
⁴ Medical College of Qingdao University, Qingdao, 266021, China.

PMID: 28092028
DOI: 10.1007/978-1-4939-6762-9_5

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.

Keywords: DomPep; Ligand prediction; SH2; SH2-peptide interactions; SMALI.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology / methods*
Computer Simulation*
Ligands*
Protein Binding
Protein Interaction Mapping / methods*
Software
Web Browser
src Homology Domains*

Substances

Ligands