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Protein local structure prediction from sequence
Author(s) -
Hunter Cornelius G.,
Subramaniam Shankar
Publication year - 2003
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.10310
Subject(s) - centroid , sequence (biology) , mathematics , globular protein , set (abstract data type) , protein structure prediction , pattern recognition (psychology) , statistics , artificial intelligence , algorithm , computer science , protein structure , biology , chemistry , crystallography , genetics , biochemistry , programming language
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. Proteins 2003;50:572–579. © 2003 Wiley‐Liss, Inc.