title: Protein local structure prediction from sequence.
abstract: A basis set of protein canonical fragments, or centroids, represents the range of local structure found in globular proteins. We develop a methodology to predict centroids from the amino acid sequence. The predictor gives the probability of each centroid in the basis set, at each loci along the backbone. The predictor selects the best-fit centroid at about 40% of the loci. The predicted probabilities are accurate and can be used to judge the confidence of each centroid prediction. For example, when filtering out centroids with <0.50 probability, the predictor is 65% accurate, although such high-probability centroids occur at only 28% of the loci. Centroids with high probability can be interpreted as segments that are highly influenced by the amino acid sequence, whereas centroids with low probability can be interpreted as segments that are more likely influenced by tertiary contacts. Low-resolution, starting point structures, can be generated by fitting the predicted centroids together.
authors.affiliation: Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Illinois, USA.
authors.forename: Cornelius G
authors.initials: CG
authors.lastname: Hunter
authors.forename: Shankar
authors.initials: S
authors.lastname: Subramaniam
mesh_terms: D000818:Animals; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins