Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis

被引:140
|
作者
Nugent, Timothy [1 ]
Jones, David T. [1 ]
机构
[1] UCL, Dept Comp Sci, Bioinformat Grp, London WC1E 6BT, England
基金
英国医学研究理事会; 英国生物技术与生命科学研究理事会;
关键词
structural bioinformatics; protein modeling; compressed sensing; amino acid contacts; INVERSE COVARIANCE ESTIMATION; RESIDUE CONTACTS; INFORMATION; TOPOLOGY; FAMILIES; MAPS;
D O I
10.1073/pnas.1120036109
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
A new de novo protein structure prediction method for transmembrane proteins (FILM3) is described that is able to accurately predict the structures of large membrane proteins domains using an ensemble of two secondary structure prediction methods to guide fragment selection in combination with a scoring function based solely on correlated mutations detected in multiple sequence alignments. This approach has been validated by generating models for 28 membrane proteins with a diverse range of complex topologies and an average length of over 300 residues with results showing that TM-scores > 0.5 can be achieved in almost every case following refinement using MODELLER. In one of the most impressive results, a model of mitochondrial cytochrome c oxidase polypeptide I was obtained with a TM-score > 0.75 and an rmsd of only 5.7 angstrom over all 514 residues. These results suggest that FILM3 could be applicable to a wide range of transmembrane proteins of as-yet-unknown 3D structure given sufficient homologous sequences.
引用
收藏
页码:E1540 / E1547
页数:8
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