BINDING SPECIFICITY OF PEPTIDE RECOGNITION DOMAINS

肽识别域的结合特异性

• 批准号: 7367782
• 负责人: WEI WANG
• 金额: $ 2.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7367782
• 关键词: BINDING; SPECIFICITY; PEPTIDE; RECOGNITION; DOMAINS

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We have developed a computational method called Virtual Mutagenesis (VM) to determine the peptide sequences recognized by peptide binding protein domains, such as SH3 and SH2 domains, and predict their physiological interacting partners of these domains. In the proof of concept study, we applied this method to SH3 domain of human protein Abl. Based on a complex structure of the SH3 domain and a binding peptide, we mutated every amino acid of the template peptide to all other 19 amino acids and calculated the binding free energy difference between the template and mutated peptides, which reflects how favorable/unfavorable an amino acid is at each position of the peptide. This free energy difference is used to generate a position specific scoring matrix (PSFM) to screen all peptides in the human proteome and identify the putative interacting partners of the Abl SH3 domain. In the top ten candidates, we found four proteins were known to interact with the SH3 domain and the performance of VM was much better than Scansite, a method relying on the PSFM generated from random peptide library experiments.

本子项目是利用由NIH/NCRR资助的中心赠款提供的资源的众多研究子项目之一。子项目和研究者（PI）可能已经从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。列出的机构是中心的，不一定是研究者的机构。我们开发了一种称为虚拟诱变（Virtual Mutagenesis， VM）的计算方法来确定肽结合蛋白结构域（如SH3和SH2结构域）识别的肽序列，并预测这些结构域的生理相互作用伙伴。在概念验证研究中，我们将该方法应用于人Abl蛋白的SH3结构域。基于SH3结构域和结合肽的复杂结构，我们将模板肽的每个氨基酸突变为所有其他19个氨基酸，并计算模板和突变肽之间的结合自由能差，这反映了氨基酸在肽的每个位置的有利/不利程度。该自由能差用于生成位置特异性评分矩阵（PSFM），以筛选人类蛋白质组中的所有肽，并确定Abl SH3结构域的推定相互作用伙伴。在前10个候选蛋白中，我们发现有4个蛋白已知与SH3结构域相互作用，VM的性能远远优于Scansite，后者依赖于随机肽库实验生成的PSFM方法。