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Statistical and Visual Morph Movie Analysis of Crystallographic Mutant Selection Bias in Protein Mutation Resource Data
Stanford, California August 11-August 14
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSB.2003.1227317IEEE Computer Society Bioinformatics ...
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Werner G. Krebs, San Diego Supercomputer Center MC
Philip E. Bourne, University of California, San Diego
The relationship between protein mutations and conformational change can potentially decipher the language relating sequence to structure. Elsewhere, we presented the Protein Mutant Resource (PMR), an online tool that systematically identified related mutants in the Protein DataBank (PDB), inferred mutant Gene Ontology classifications using data-mining, and allowed intuitive exploration of relationships between mutant structures. Here, we perform a comprehensive statistical analysis of PMR mutants. Although the PMR contains spectacular conformational changes, generally there is a counter-intuitive inverse relationship between conformational change and the number of mutations. That is, PDB mutations contrast naturally evolved mutations. We compare the frequencies of mutations in the PMR/PDB datasets against the PAM250 natural mutation frequencies to confirm this. We make available morph movies from PMR structure pairs, allowing visual analysis of conformational change and the ability to distinguish visually between conformational change due to motions (e.g.,ligand binding)and mutations. The PMR is at http://pmr.sdsc.edu.
Citation:
Werner G. Krebs, Philip E. Bourne, "Statistical and Visual Morph Movie Analysis of Crystallographic Mutant Selection Bias in Protein Mutation Resource Data," csb, pp.180, IEEE Computer Society Bioinformatics Conference (CSB'03), 2003
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