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De novo protein design using pairwise potentials and a genetic algorithm
Author(s) -
Jones David T.
Publication year - 1994
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1002/pro.5560030405
Subject(s) - pairwise comparison , protein design , protein folding , computer science , sequence (biology) , algorithm , fold (higher order function) , computational biology , protein structure , biology , artificial intelligence , genetics , biochemistry , programming language
One of the major goals of molecular biology is to understand how protein chains fold into a unique 3‐dimensional structure. Given this knowledge, perhaps the most exciting prospect will be the possibility of designing new proteins to perform designated tasks, an application that could prove to be of great importance in medicine and biotechnology. It is possible that effective protein design may be achieved without the requirement for a full understanding of the protein folding process. In this paper a simple method is described for designing an amino acid sequence to fit a given 3‐dimensional structure. The compatibility of a designed sequence with a given fold is assessed by means of a set of statistically determined potentials (including interresidue pairwise and solvation terms), which have been previously applied to the problem of protein fold recognition. In order to generate sequences that best fit the fold, a genetic algorithm is used, whereby the sequence is optimized by a stochastic search in the style of natural selection.