title: Exploring protein sequence space using knowledge-based potentials.
abstract: 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 PROSA pair potential and a neural network based potential, are used to verify these claims.
authors.affiliation: Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, A-1090 Vienna, Austria.
authors.forename: A
authors.initials: A
authors.lastname: Babajide
authors.forename: R
authors.initials: R
authors.lastname: Farber
authors.forename: I L
authors.initials: IL
authors.lastname: Hofacker
authors.forename: J
authors.initials: J
authors.lastname: Inman
authors.forename: A S
authors.initials: AS
authors.lastname: Lapedes
authors.forename: P F
authors.initials: PF
authors.lastname: Stadler
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D003198:Computer Simulation; D019143:Evolution, Molecular; D008956:Models, Chemical; D011487:Protein Conformation; D017510:Protein Folding