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Recognizing protein folds by cluster distance geometry
Author(s) -
Crippen Gordon M.
Publication year - 2005
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.20488
Subject(s) - cluster analysis , protein folding , protein data bank , cluster (spacecraft) , geometry , generalization , protein structure , contact order , protein structure prediction , folding (dsp implementation) , crystallography , combinatorics , chemistry , computer science , native state , mathematics , artificial intelligence , biochemistry , engineering , mathematical analysis , electrical engineering , programming language
Abstract Cluster distance geometry is a recent generalization of distance geometry whereby protein structures can be described at even lower levels of detail than one point per residue. With improvements in the clustering technique, protein conformations can be summarized in terms of alternative contact patterns between clusters, where each cluster contains four sequentially adjacent amino acid residues. A very simple potential function involving 210 adjustable parameters can be determined that favors the native contacts of 31 small, monomeric proteins over their respective sets of nonnative contacts. This potential then favors the native contacts for 174 small, monomeric proteins that have low sequence identity with any of the training set. A broader search finds 698 small protein chains from the Protein Data Bank where the native contacts are preferred over all alternatives, even though they have low sequence identity with the training set. This amounts to a highly predictive method for ab initio protein folding at low spatial resolution. Proteins 2005;. © 2005 Wiley‐Liss, Inc.