用于蛋白质复合物结构预测的深度学习

Deep learning for protein complex structure prediction.

作者信息

Bryant Patrick

机构信息

Science for Life Laboratory, 172 21 Solna, Sweden; Department of Biochemistry and Biophysics, Stockholm University, 106 91 Stockholm, Sweden.

出版信息

Curr Opin Struct Biol. 2023 Apr;79:102529. doi: 10.1016/j.sbi.2023.102529. Epub 2023 Jan 31.

DOI:10.1016/j.sbi.2023.102529

PMID:36731337

Abstract

Recent developments in the structure prediction of protein complexes have resulted in accuracies rivalling experimental methods in many cases. The high accuracy is mainly observed in dimeric complexes and other problems such as protein disorder and predicting the structure of host-pathogen interactions remain. This review highlights the foundation for current accurate structure prediction of protein complexes and possible ways to address the remaining limitations.

摘要

蛋白质复合物结构预测的最新进展已在许多情况下实现了与实验方法相媲美的准确性。高准确性主要体现在二聚体复合物中，而诸如蛋白质无序以及预测宿主-病原体相互作用结构等其他问题仍然存在。本综述强调了当前蛋白质复合物准确结构预测的基础以及解决其余局限性的可能方法。