Exploring Protein Sequence Space Using Knowledge-Based Potentials

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

Working Papers from Santa Fe Institute

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.

Submitted to Prot.Sci.

Keywords: Knowledge-based potentials; inverse folding; neutral networks; protein evolution (search for similar items in EconPapers)
Date: 1998-11
References: View complete reference list from CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wop:safiwp:98-11-103

Access Statistics for this paper

More papers in Working Papers from Santa Fe Institute Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().