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An evolutionary approach to folding small alpha-helical proteins that uses sequence information and an empirical guiding fitness function.
Author(s) -
James U. Bowie,
David Eisenberg
Publication year - 1994
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.91.10.4436
Subject(s) - sequence (biology) , fragment (logic) , protein design , protein folding , folding (dsp implementation) , protein structure , sequence space , protein structure prediction , protein evolution , protein sequencing , function (biology) , computational biology , protein secondary structure , peptide sequence , bioinformatics , biology , algorithm , computer science , evolutionary biology , genetics , mathematics , gene , biochemistry , engineering , banach space , pure mathematics , electrical engineering
Three short protein sequences have been guided by computer to folds resembling their crystal structures. Initially, peptide fragment conformations ranging in size from 9 to 25 residues were selected from a database of known protein structures. A fragment was selected if it was compatible with a segment of the sequence to be folded, as judged by three-dimensional profile scores. By linking the selected fragment conformations together, hundreds of trial structures were generated of the same length and sequence as the protein to be folded. These starting trial structures were then improved by an evolutionary algorithm. Selection pressure for improving the structures was provided by an energy function that was designed to guide the conformational search procedure toward the correct structure. We find that by evolution of only 400 structures for fewer than 1400 generations, the overall fold of some small helical proteins can be computed from the sequence, with deviations from observed structures of 2.5-4.0 A for C alpha atoms.

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