Improved mutation tagging with gene identifiers applied to membrane protein stability prediction
| Autor: | Conrad Plake, Michael Schroeder, Rainer Winnenburg |
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| Rok vydání: | 2009 |
| Předmět: |
PubMed
Sequence analysis biotechnology bioinformatics Information Storage and Retrieval Genomics Computational biology Biology Biochemistry Pattern Recognition Automated Domain (software engineering) Structural Biology ddc:570 Databases Genetic Animals Humans Point Mutation ddc:610 Molecular Biology Biotechnologie Bioinformatik Genetics Models Genetic Protein Stability Research Applied Mathematics Point mutation Computational Biology Membrane Proteins food and beverages Computer Science Applications Identifier Phenotype Amino Acid Substitution Genes Mutation Mutation (genetic algorithm) Pattern recognition (psychology) Periodicals as Topic ddc:004 DNA microarray Sequence Analysis Algorithms |
| Zdroj: | BMC Bioinformatics |
| ISSN: | 1471-2105 |
| Popis: | Background The automated retrieval and integration of information about protein point mutations in combination with structure, domain and interaction data from literature and databases promises to be a valuable approach to study structure-function relationships in biomedical data sets. Results We developed a rule- and regular expression-based protein point mutation retrieval pipeline for PubMed abstracts, which shows an F-measure of 87% for the mutation retrieval task on a benchmark dataset. In order to link mutations to their proteins, we utilize a named entity recognition algorithm for the identification of gene names co-occurring in the abstract, and establish links based on sequence checks. Vice versa, we could show that gene recognition improved from 77% to 91% F-measure when considering mutation information given in the text. To demonstrate practical relevance, we utilize mutation information from text to evaluate a novel solvation energy based model for the prediction of stabilizing regions in membrane proteins. For five G protein-coupled receptors we identified 35 relevant single mutations and associated phenotypes, of which none had been annotated in the UniProt or PDB database. In 71% reported phenotypes were in compliance with the model predictions, supporting a relation between mutations and stability issues in membrane proteins. Conclusion We present a reliable approach for the retrieval of protein mutations from PubMed abstracts for any set of genes or proteins of interest. We further demonstrate how amino acid substitution information from text can be utilized for protein structure stability studies on the basis of a novel energy model. |
| Databáze: | OpenAIRE |
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