Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis.
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 Å 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.
Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London WC1E 6BT, United Kingdom.
Timothy
T
Nugent
David T
DT
Jones
D008565:Membrane Proteins / Q000737:chemistry* / Q000235:genetics; D008958:Models, Molecular; D009154:Mutation; D017433:Protein Structure, Secondary
D008565:Membrane Proteins