title: Predicting coiled coils by use of pairwise residue correlations.
abstract: A method is presented that predicts coiled-coil domains in protein sequences by using pairwise residue correlations obtained from a (two-stranded) coiled-coil database of 58,217 amino acid residues. A program called PAIRCOIL implements this method and is significantly better than existing methods at distinguishing coiled coils from alpha-helices that are not coiled coils. The database of pairwise residue correlations suggests structural features that stabilize or destabilize coiled coils.
authors.affiliation: Mathematics Department, Massachusetts Institute of Technology, Cambridge, 02139, USA.
authors.forename: B
authors.initials: B
authors.lastname: Berger
authors.forename: D B
authors.initials: DB
authors.lastname: Wilson
authors.forename: E
authors.initials: E
authors.lastname: Wolf
authors.forename: T
authors.initials: T
authors.lastname: Tonchev
authors.forename: M
authors.initials: M
authors.lastname: Milla
authors.forename: P S
authors.initials: PS
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D019883:Alkyl and Aryl Transferases; D003198:Computer Simulation; D051231:Farnesyltranstransferase; D019204:GTP-Binding Proteins / Q000737:chemistry; D016328:NF-kappa B / Q000737:chemistry; D011336:Probability; D011487:Protein Conformation; D014166:Transferases / Q000737:chemistry; D014404:Tubulin / Q000737:chemistry
chemical_list: D016328:NF-kappa B; D014404:Tubulin; D014166:Transferases; D019883:Alkyl and Aryl Transferases; D051231:Farnesyltranstransferase; D019204:GTP-Binding Proteins