Journal
PROTEIN SCIENCE
Volume 21, Issue 12, Pages 1824-1836Publisher
WILEY
DOI: 10.1002/pro.2163
Keywords
knowledge-based torsion angle potential; adaptive kernel density estimation; NMR protein structure calculation; protein structure validation
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Funding
- NIH Intramural Research Program of CIT
- NIH Intramural Research Program of NIDDK
- AIDS Targeted Antiviral Program of the Office of the Director of the NIH
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Statistical potentials that embody torsion angle probability densities in databases of high-quality X-ray protein structures supplement the incomplete structural information of experimental nuclear magnetic resonance (NMR) datasets. By biasing the conformational search during the course of structure calculation toward highly populated regions in the database, the resulting protein structures display better validation criteria and accuracy. Here, a new statistical torsion angle potential is developed using adaptive kernel density estimation to extract probability densities from a large database of more than 106 quality-filtered amino acid residues. Incorporated into the Xplor-NIH software package, the new implementation clearly outperforms an older potential, widely used in NMR structure elucidation, in that it exhibits simultaneously smoother and sharper energy surfaces, and results in protein structures with improved conformation, nonbonded atomic interactions, and accuracy.
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