噬菌体展示
计算生物学
计算机科学
双杂交筛选
生物
蛋白质-蛋白质相互作用
免疫沉淀
肽
人工智能
酵母
遗传学
化学
药物发现
交互网络
生物系统
基因
生物化学
作者
Amy Tong,Becky Drees,Giuliano Nardelli,Gary D. Bader,Barbara Brannetti,Luisa Castagnoli,Marie Evangelista,Silvia Ferracuti,Bryce Nelson,Serena Paoluzi,Michele Quondam,Adriana Zucconi,Christopher W. V. Hogue,Stanley Fields,Charles Boone,Gianni Cesareni
出处
期刊:Science
[American Association for the Advancement of Science (AAAS)]
日期:2002-01-11
卷期号:295 (5553): 321-324
被引量:671
标识
DOI:10.1126/science.1064987
摘要
Peptide recognition modules mediate many protein-protein interactions critical for the assembly of macromolecular complexes. Complete genome sequences have revealed thousands of these domains, requiring improved methods for identifying their physiologically relevant binding partners. We have developed a strategy combining computational prediction of interactions from phage-display ligand consensus sequences with large-scale two-hybrid physical interaction tests. Application to yeast SH3 domains generated a phage-display network containing 394 interactions among 206 proteins and a two-hybrid network containing 233 interactions among 145 proteins. Graph theoretic analysis identified 59 highly likely interactions common to both networks. Las17 (Bee1), a member of the Wiskott-Aldrich Syndrome protein (WASP) family of actin-assembly proteins, showed multiple SH3 interactions, many of which were confirmed in vivo by coimmunoprecipitation.
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