title: Fold recognition and ab initio structure predictions using hidden Markov models and beta-strand pair potentials.
abstract: Protein structure predictions were submitted for 9 of the target sequences in the competition that ran during 1994. Targets sequences were selected that had no known homology with any sequence of known structure and were members of a reasonably sized family of related but divergent sequences. The objective was either to recognize a compatible fold for the target sequence in the database of known structures or to predict ab initio its rough 3D topology. The main tools used were Hidden Markov models (HMM) for fold recognition, a beta-strand pair potential to predict beta-sheet topology, and the PHD server for secondary structure prediction. Compatible folds were correctly identified in a number of cases and the beta-strand pair potential was shown to be a useful tool for ab initio topology prediction.
authors.affiliation: Centre for Protein Engineering (CPE), MRC Centre, Cambridge, UK.
authors.forename: T J
authors.initials: TJ
authors.lastname: Hubbard
authors.forename: J
authors.initials: J
authors.lastname: Park
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016208:Databases, Factual; D008390:Markov Chains; D008958:Models, Molecular; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D012984:Software
chemical_list: D011506:Proteins