| Literature DB >> 34762488 |
Ian R Humphreys1,2, Jimin Pei3,4, Minkyung Baek1,2, Aditya Krishnakumar1,2, Qian Cong3,4, David Baker1,2,5, Ivan Anishchenko1,2, Sergey Ovchinnikov6,7, Jing Zhang3,4, Travis J Ness8, Sudeep Banjade9, Saket R Bagde9, Viktoriya G Stancheva10, Xiao-Han Li10, Kaixian Liu11, Zhi Zheng11,12, Daniel J Barrero13, Upasana Roy14, Jochen Kuper15, Israel S Fernández16, Barnabas Szakal17, Dana Branzei17,18, Josep Rizo4,19,20, Caroline Kisker15, Eric C Greene14, Sue Biggins13, Scott Keeney11,12,21, Elizabeth A Miller10, J Christopher Fromme9, Tamara L Hendrickson8.
Abstract
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning–based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the Saccharomyces cerevisiae proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as five subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.Entities:
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Year: 2021 PMID： 34762488 PMCID： PMC7612107 DOI： 10.1126/science.abm4805
Source DB: PubMed Journal: Science ISSN： 0036-8075 Impact factor: 63.714