美国哥伦比亚大学Sagi D. Shapira和Barry Honig等研究人员根据蛋白结构，合作描绘了人与病毒相互作用的图谱。相关论文2019年8月29日在线发表于《细胞》。

研究人员建立了被称为P-HIPSTer的计算机模拟框架（使用结构相似性的病原体宿主相互作用组预测），其使用结构信息来预测大约282000种泛病毒-人之间的蛋白相互作用，实验验证率约为76％。除了重新发现已知的生物学外，P-HIPSTer已经产生了一系列新的发现：人类感染病毒中使用的共享和独特机制、ZIKV-ESR1相互作用在调节病毒复制中的可能作用、区分具有高和低致癌潜力的人乳头瘤病毒（HPV）的蛋白互作鉴定、以及进化选择压力对人类蛋白质组产生的结构变化历史。此外，P-HIPSTer能够发现以前未被认可的细胞回路，这些回路对人类感染的病毒起作用，并为实验上难以对付的病毒提供新的见解。

据介绍，虽然蛋白质-蛋白质相互作用的认知对于理解病毒-宿主关系至关重要，但是高通量方法在扩展性上的限制阻碍了其在已有较多研究以外的病毒鉴定。

附：英文原文

Title: A Structure-Informed Atlas of Human-Virus Interactions

Author: Gorka Lasso, Sandra V. Mayer, Evandro R. Winkelmann, Tim Chu, Oliver Elliot, Juan Angel Patino-Galindo, Kernyu Park, Raul Rabadan, Barry Honig, Sagi D. Shapira

Issue&Volume: 29 August 2019

Abstract: While knowledge of protein-protein interactions (PPIs) is critical for understanding virus-host relationships, limitations on the scalability of high-throughput methods have hampered their identification beyond a number of well-studied viruses. Here, we implement an in silico computational framework (pathogen host interactome prediction using structure similarity [P-HIPSTer]) that employs structural information to predict ～282,000 pan viral-human PPIs with an experimental validation rate of ～76%. In addition to rediscovering known biology, P-HIPSTer has yielded a series of new findings: the discovery of shared and unique machinery employed across human-infecting viruses, a likely role for ZIKV-ESR1 interactions in modulating viral replication, the identification of PPIs that discriminate between human papilloma viruses (HPVs) with high and low oncogenic potential, and a structure-enabled history of evolutionary selective pressure imposed on the human proteome. Further, P-HIPSTer enables discovery of previously unappreciated cellular circuits that act on human-infecting viruses and provides insight into experimentally intractable viruses.

DOI: https://doi.org/10.1016/j.cell.2019.08.005

Source: https://www.cell.com/cell/fulltext/S0092-8674(19)30893-1