SimShiftDB; local conformational restraints derived from chemical shift similarity searches on a large synthetic database.
We present SimShiftDB, a new program to extract conformational data from protein chemical shifts using structural alignments. The alignments are obtained in searches of a large database containing 13,000 structures and corresponding back-calculated chemical shifts. SimShiftDB makes use of chemical shift data to provide accurate results even in the case of low sequence similarity, and with even coverage of the conformational search space. We compare SimShiftDB to HHSearch, a state-of-the-art sequence-based search tool, and to TALOS, the current standard tool for the task. We show that for a significant fraction of the predicted similarities, SimShiftDB outperforms the other two methods. Particularly, the high coverage afforded by the larger database often allows predictions to be made for residues not involved in canonical secondary structure, where TALOS predictions are both less frequent and more error prone. Thus SimShiftDB can be seen as a complement to currently available methods.
Ginzinger
Simon W
SW
Department of Molecular Biology, Division of Bioinformatics, Center of Applied Molecular Engineering, University of Salzburg, Hellbrunnerstr. 34/3.OG, 5020, Salzburg, Austria. simon@came.sbg.ac.at
Coles
Murray
M
D000465:Algorithms; D003198:Computer Simulation; D030562:Databases, Protein; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012984:Software; D040681:Structural Homology, Protein; D014584:User-Computer Interface
D011506:Proteins