Exploring protein sequence space using knowledge-based potentials

被引:37
作者
Babajide, A
Farber, R
Hofacker, IL
Inman, J
Lapedes, AS
Stadler, PF
机构
[1] Univ Vienna, Inst Theoret Chem & Mol Strukturbiol, A-1090 Vienna, Austria
[2] Los Alamos Natl Lab, Div Theoret, Los Alamos, NM 87545 USA
[3] Santa Fe Inst, Santa Fe, NM 87501 USA
[4] Natl Ctr Genome Resources, Santa Fe, NM 87505 USA
关键词
D O I
10.1006/jtbi.2001.2343
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Knowledge-based potentials can be used to decide whether an amino. acid sequence is likely to fold into a prescribed native protein structure. We use this idea to survey the sequence-structure relations in protein space. In particular, we test the following two propositions which were found to be important for efficient evolution: the sequences folding into a particular native fold form extensive neutral networks that percolate through sequence space. The neutral networks of any two native folds approach each other to within a few point mutations. Computer simulations using two very different potential functions, M. Sippl's PP,OSA pair potential and a neural network based potential, are used to verify these claims. (C) 2001 Academic Press.
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收藏
页码:35 / 46
页数:12
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