AUTO-MUTE 2.0: A Portable Framework with Enhanced Capabilities for Predicting Protein Functional Consequences upon Mutation
Author(s) -
Majid Masso,
Iosif I. Vaisman
Publication year - 2014
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2014/278385
Subject(s) - computer science , disk formatting , protein data bank (rcsb pdb) , software , protein data bank , mutation , upload , nonsynonymous substitution , data mining , computational biology , machine learning , protein structure , bioinformatics , operating system , genetics , biology , biochemistry , genome , gene
The AUTO-MUTE 2.0 stand-alone software package includes a collection of programs for predicting functional changes to proteins upon single residue substitutions, developed by combining structure-based features with trained statistical learning models. Three of the predictors evaluate changes to protein stability upon mutation, each complementing a distinct experimental approach. Two additional classifiers are available, one for predicting activity changes due to residue replacements and the other for determining the disease potential of mutations associated with nonsynonymous single nucleotide polymorphisms (nsSNPs) in human proteins. These five command-line driven tools, as well as all the supporting programs, complement those that run our AUTO-MUTE web-based server. Nevertheless, all the codes have been rewritten and substantially altered for the new portable software, and they incorporate several new features based on user feedback. Included among these upgrades is the ability to perform three highly requested tasks: to run “big data” batch jobs; to generate predictions using modified protein data bank (PDB) structures, and unpublished personal models prepared using standard PDB file formatting; and to utilize NMR structure files that contain multiple models.
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