期刊
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
卷 78, 期 16, 页码 3353-3362出版社
WILEY
DOI: 10.1002/prot.22842
关键词
flexibility prediction; NMR structures; neural networks; torsion-angle restraints
资金
- National Institutes of Health [R01 GM 085003, R01 GM 067168]
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM085003, R01GM067168] Funding Source: NIH RePORTER
Protein molecules exhibit varying degrees of flexibility throughout their three-dimensional structures. Protein structural flexibility is often characterized by fluctuations in the Cartesian coordinate space. On the other hand, the protein backbone can be mostly defined by two torsion angles phi and psi only. We introduce a new flexibility descriptor, backbone torsion-angle fluctuation derived from the variation of backbone torsion angles from different NMR models. The torsion-angle fluctuations correlate with mean-squared spatial fluctuations derived from the same collection of NMR models. We developed a neural-network based real-value predictor based on sequence information only. The predictor achieved ten-fold cross-validated correlation coefficients of 0.59 and 0.60, and mean absolute errors of 22.7 degrees and 24.3 degrees for the angle fluctuation of phi and psi, respectively. This predictor is expected to be useful for function prediction and protein structure prediction when predicted torsion angles are used as restraints. Both sequence- and structure-based prediction of torsion-angle fluctuation will be available at http://sparks.informatics.iupui.edu within the SPINE-X package.
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