Exploring Protein Sequence Space Using Knowledge-Based Potentials

Aderonke Babajide, Robert Farber, Ivo L. Hofacker, Jeff Inman, Alan S. Lapedes, , andeter F. Stadler

98-11-103

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.