热点(计算机编程)
热点(地质)
斑点
化学
数据库
物理
计算机科学
地球物理学
操作系统
物理化学
作者
Yao Chi Chen,Yu‐Hsien Chen,Jon D. Wright,Carmay Lim
标识
DOI:10.1021/acs.jcim.2c00025
摘要
Single-point mutations of certain residues (so-called hot spots) impair/disrupt protein–protein interactions (PPIs), leading to pathogenesis and drug resistance. Conventionally, a PPI-hot spot is identified when its replacement decreased the binding free energy significantly, generally by ≥2 kcal/mol. The relatively few mutations with such a significant binding free energy drop limited the number of distinct PPI-hot spots. By defining PPI-hot spots based on mutations that have been manually curated in UniProtKB to significantly impair/disrupt PPIs in addition to binding free energy changes, we have greatly expanded the number of distinct PPI-hot spots by an order of magnitude. These experimentally determined PPI-hot spots along with available structures have been collected in a database called PPI-HotspotDB. We have applied the PPI-HotspotDB to create a nonredundant benchmark, PPI-Hotspot+PDBBM, for assessing methods to predict PPI-hot spots using the free structure as input. PPI-HotspotDB will benefit the design of mutagenesis experiments and development of PPI-hot spot prediction methods. The database and benchmark are freely available at https://ppihotspot.limlab.dnsalias.org.
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