Using pseudo amino acid composition to predict protein subnuclear localization: Approached with PSSM
Pattern Recognition Letters
WSEAS Transactions on Computers
Fuzzy pattern extraction for classification of protein sequences
ISB '10 Proceedings of the International Symposium on Biocomputing
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
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Motivation: Inclusion body formation has been a major deterrent for overexpression studies since a large number of proteins form insoluble inclusion bodies when overexpressed in Escherichia coli. The formation of inclusion bodies is known to be an outcome of improper protein folding; thus the composition and arrangement of amino acids in the proteins would be a major influencing factor in deciding its aggregation propensity. There is a significant need for a prediction algorithm that would enable the rational identification of both mutants and also the ideal protein candidates for mutations that would confer higher solubility-on-overexpression instead of the presently used trial-and-error procedures. Results: Six physicochemical properties together with residue and dipeptide-compositions have been used to develop a support vector machine-based classifier to predict the overexpression status in E.coli. The prediction accuracy is ∼72% suggesting that it performs reasonably well in predicting the propensity of a protein to be soluble or to form inclusion bodies. The algorithm could also correctly predict the change in solubility for most of the point mutations reported in literature. This algorithm can be a useful tool in screening protein libraries to identify soluble variants of proteins. Avalibility: Software is available on request from the authors. Contact:balaji@iitcb.ac.in; vk.jayaraman@ncl.res.in Supplementary information: Supplementary data are available at Bioinformatics Online web site.