Biomedical subjects

Werner G Krebs

Publications and source records attributed to Werner G Krebs.

3 recordsLinked to original sources

PubMed2004

Statistically rigorous automated protein annotation.

MOTIVATION: Assignment of putative protein functional annotation by comparative analysis using pre-defined experimental annotations is performed routinely by molecular biologists. The number and statistical significance of these assignments remains a challenge in this era of high-throughput proteomics. A combined statistical method that enables robust, automated protein annotation by reliably expanding existing annotation sets is described. An existing clustering scheme, based on relevant experimental information (e.g. sequence identity, keywords or gene expression data) is required. The method assigns new proteins to these clusters with a measure of reliability. It can also provide human reviewers with a reliability score for both new and previously classified proteins. RESULTS: A dataset of 27 000 annotated Protein Data Bank (PDB) polypeptide chains (of 36 000 chains currently in the PDB) was generated from 23 000 chains classified a priori. AVAILABILITY: PDB annotations and sample software implementation are freely accessible on the Web at http://pmr.sdsc.edu/go

Abstracting and Indexing↗

PubMed2004

Statistical and visual morph movie analysis of crystallographic mutant selection bias in protein mutation resource data.

Structural studies of the effects of non-silent mutations on protein conformational change are an important key in deciphering the language that relates protein amino acid primary structure to tertiary structure. Elsewhere, we presented the Protein Mutant Resource (PMR) database, a set of online tools that systematically identified groups of related mutant structures in the Protein DataBank (PDB), accurately inferred mutant classifications in the Gene Ontology using an innovative, statistically rigorous data-mining algorithm with more general applicability, and illustrated the relationship of these mutant structures via an intuitive user interface. Here, we perform a comprehensive statistical analysis of the effect of PMR mutations on protein tertiary structure. We find that, although the PMR does contain spectacular examples of conformational change, in general there is a counter-intuitive inverse relationship between conformational change (measured as C-alpha displacement or RMS of the core structure) and the number of mutations in a structure. That is, point mutations by structural biologists present in the PDB contrast naturally evolved mutations. We compare the frequency of mutations in the PMR/PDB datasets against the accepted PAM250 natural amino acid mutation frequency to confirm these observations. We generated morph movies from PMR structure pairs using technology previously developed for the Macromolecular Motions Database (http://molmovdb.org), allowing bioinformaticians, geneticists, protein engineers, and rational drug designers to analyze visually the mechanisms of protein conformational change and distinguish between conformational change due to motions (e.g., ligand binding) and mutations. The PMR morph movies and statistics can be freely viewed from the PMR website, http://pmr.sdsc.edu.

Amino Acid Sequence↗

PubMed2003

Statistical and visual morph movie analysis of crystallographic mutant selection bias in protein mutation resource data.

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.

Bias↗