Fast protein fold recognition via sequence to structure alignment and contact capacity potentials.
We propose new empirical scoring potentials and associated alignment procedures for optimally aligning protein sequences to protein structures. The method has two main applications: first, the recognition of a plausible fold for a protein sequence of unknown structure out of a database of representative protein structures and, second, the improvement of sequence alignments by using structural information in order to find a better starting point for homology based modelling. The empirical scoring function is derived from an analysis of a nonredundant database of known structures by converting relative frequencies into pseudoenergies using a normalization according to the inverse Bolzmann law. These-so called contact capacity-potentials turn out to be discriminative enough to detect structural folds in the absence of significant sequence similarity and at the same time simple enough to allow for a very fast optimization in an alignment procedure.
Alexandrov
N N
NN
Laboratory of Mathematical Biology, NCI-FCRF, Frederick, MD 21702-1201, USA. nicka@ncifcrf.gov
Nussinov
R
R
Zimmer
R M
RM
D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D016208:Databases, Factual; D008969:Molecular Sequence Data; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software; D013816:Thermodynamics
D011506:Proteins