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Universal similarity measure for comparing protein structures
Author(s) -
Betancourt Marcos R.,
Skolnick Jeffrey
Publication year - 2001
Publication title -
biopolymers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 125
eISSN - 1097-0282
pISSN - 0006-3525
DOI - 10.1002/1097-0282(20011015)59:5<305::aid-bip1027>3.0.co;2-6
Subject(s) - chemistry , measure (data warehouse) , similarity measure , structural similarity , similarity (geometry) , computational biology , biochemistry , data mining , artificial intelligence , computer science , biology , image (mathematics)
We introduce a new variant of the root mean square distance (RMSD) for comparing protein structures whose range of values is independent of protein size. This new dimensionless measure (relative RMSD, or RRMSD) is zero between identical structures and one between structures that are as globally dissimilar as an average pair of random polypeptides of respective sizes. The RRMSD probability distribution between random polypeptides converges to a universal curve as the chain length increases. The correlation coefficients between aligned random structures are computed as a function of polypeptide size showing two characteristic lengths of 4.7 and 37 residues. These lengths mark the separation between phases of different structural order between native protein fragments. The implications for threading are discussed. © 2001 John Wiley & Sons, Inc. Biopolymers 59: 305–309, 2001