Statistical Measures on Residue-Level Protein Structural Properties
Zhijun Wu, Math, Bioinformatics, & Computational Biology, Iowa State University (April 26, 2011)
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Structural properties on protein residue-level, such as the distances between two residues and the angles formed by short sequences of residues, can be important for structural analysis and modeling, but they have not been examined and documented in great detail. While these properties are difficult to measure experimentally, they can be statistically estimated based on their distributions in known protein structures.
Our work has involved in developing databases and software packages to estimate, document, and analyze the statistical distributions and correlations of various residue-level protein structural properties. We have found the high probability distributions of these properties and strong correlations among some of them. The results provide systematic and quantitative assessments on these properties, which can otherwise be estimated only individually and qualitatively.
Of particular interest is our recent work on an R-package called PRESS for the study of protein residue-level structural statistics. With this software, we can compute and display statistical distributions and correlations of certain residue-level structural properties in known protein structures, and use them to define statistical potentials and generate residue-level Ramachandran-like plots for structural analysis and assessment.
-- Joint work with Yuanyuan Huang, Stephen Bonett, Andrzej Kloczkowiski, and Robert Jernigan.