An evaluation of automated homology modelling methods at low target–template sequence similarity | Zendy

James A. R. Dalton | Zendy; Richard M. Jackson | Zendy

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An evaluation of automated homology modelling methods at low target–template sequence similarity

Author(s) -

James A. R. Dalton,

Richard M. Jackson

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm262

Subject(s) - computer science , similarity (geometry) , sequence (biology) , homology (biology) , sequence alignment , computational biology , homology modeling , software , artificial intelligence , biology , peptide sequence , genetics , programming language , biochemistry , gene , image (mathematics) , enzyme

There are two main areas of difficulty in homology modelling that are particularly important when sequence identity between target and template falls below 50%: sequence alignment and loop building. These problems become magnified with automatic modelling processes, as there is no human input to correct mistakes. As such we have benchmarked several stand-alone strategies that could be implemented in a workflow for automated high-throughput homology modelling. These include three new sequence-structure alignment programs: 3D-Coffee, Staccato and SAlign, plus five homology modelling programs and their respective loop building methods: Builder, Nest, Modeller, SegMod/ENCAD and Swiss-Model. The SABmark database provided 123 targets with at least five templates from the same SCOP family and sequence identities </=50%.

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