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Enhanced protein fold recognition using secondary structure information from nmr
Author(s) -
Ayers Daniel J.,
Gooley Paul R.,
WidmerCooper Asaph,
Torda Andrew E.
Publication year - 1999
Publication title -
protein science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.353
H-Index - 175
eISSN - 1469-896X
pISSN - 0961-8368
DOI - 10.1110/ps.8.5.1127
Subject(s) - fold (higher order function) , chemistry , computational biology , crystallography , nuclear magnetic resonance , computer science , biology , physics , programming language
NMR offers the possibility of accurate secondary structure for proteins that would be too large for structure determination. In the absence of an X‐ray crystal structure, this information should be useful as an adjunct to protein fold recognition methods based on low resolution force fields. The value of this information has been tested by adding varying amounts of artificial secondary structure data and threading a sequence through a library of candidate folds. Using a literature test set, the threading method alone has only a one‐third chance of producing a correct answer among the top ten guesses. With realistic secondary structure information, one can expect a 60–80% chance of finding a homologous structure. The method has then been applied to examples with published estimates of secondary structure. This implementation is completely independent of sequence homology, and sequences are optimally aligned to candidate structures with gaps and insertions allowed. Unlike work using predicted secondary structure, we test the effect of differing amounts of relatively reliable data.