High-accuracy prediction of transmembrane inter-helix contacts and application to GPCR 3D structure modeling

作者：Yang, Jing; Jang, Richard; Zhang, Yang; Shen, Hong Bin^*

来源：Bioinformatics, 2013, 29(20): 2579-2587.

DOI：10.1093/bioinformatics/btt440

Motivation: Residue-residue contacts across the transmembrane helices dictate the three-dimensional topology of alpha-helical membrane proteins. However, contact determination through experiments is difficult because most transmembrane proteins are hard to crystallize.
Results: We present a novel method (MemBrain) to derive transmembrane inter-helix contacts from amino acid sequences by combining correlated mutations and multiple machine learning classifiers. Tested on 60 non-redundant polytopic proteins using a strict leave-one-out cross-validation protocol, MemBrain achieves an average accuracy of 62%, which is 12.5% higher than the current best method from the literature. When applied to 13 recently solved G protein-coupled receptors, the MemBrain contact predictions helped increase the TM-score of the I-TASSER models by 37% in the transmembrane region. The number of foldable cases (TM-score >0.5) increased by 100%, where all G protein-coupled receptor templates and homologous templates with sequence identity >30% were excluded. These results demonstrate significant progress in contact prediction and a potential for contact-driven structure modeling of transmembrane proteins.

• 出版日期2013-10-15
• 单位上海交通大学