Skip Navigation



Bioinformatics Advance Access published online on December 6, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti810
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
22/3/278    most recent
bti810v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Idicula-Thomas, S.
Right arrow Articles by Balaji, P. V.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Idicula-Thomas, S.
Right arrow Articles by Balaji, P. V.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received April 30, 2005
Revised November 26, 2005
Accepted December 1, 2005

Article

A support vector machine-based method for predicting the propensity of a protein to be soluble or to form inclusion body on over-expression in Escherichia coli

Susan Idicula-Thomas 1 #, Abhijit J. Kulkarni 2 #, Bhaskar D. Kulkarni 2, Valadi K. Jayaraman 2, and Petety V. Balaji 1 *

1 School of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India
2 Chemical Engineering and Process Development Division, National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411 008, India

* To whom correspondence should be addressed.
Petety V. Balaji, E-mail: balaji{at}iitb.ac.in


  Abstract

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 E. 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 SVM-based classifier to predict the over-expression status in Escherichia coli. The prediction accuracy is ~72% suggesting that it performs reasonably well in predicting the propensity of a protein to be soluble or 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.

Availability: On request from the authors.

Supplementary Information: Available at the journal's web site.

#These authors have contributed equally to this work.
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
C. N. Magnan, A. Randall, and P. Baldi
SOLpro: accurate sequence-based prediction of protein solubility
Bioinformatics, September 1, 2009; 25(17): 2200 - 2207.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Microbiol.Home page
D. Saxena, P. W. Caufield, Y. Li, S. Brown, J. Song, and R. Norman
Genetic Classification of Severe Early Childhood Caries by Use of Subtracted DNA Fragments from Streptococcus mutans
J. Clin. Microbiol., September 1, 2008; 46(9): 2868 - 2873.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
P. Smialowski, A. J. Martin-Galiano, A. Mikolajka, T. Girschick, T. A. Holak, and D. Frishman
Protein solubility: sequence based prediction and experimental verification
Bioinformatics, October 1, 2007; 23(19): 2536 - 2542.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
C.-W. Tung and S.-Y. Ho
POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties
Bioinformatics, April 15, 2007; 23(8): 942 - 949.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.