Skip Navigation


Bioinformatics Advance Access originally published online on August 3, 2009
Bioinformatics 2009 25(19):2537-2543; doi:10.1093/bioinformatics/btp445
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
25/19/2537    most recent
btp445v2
btp445v1
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 Dehouck, Y.
Right arrow Articles by Rooman, M.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Dehouck, Y.
Right arrow Articles by Rooman, M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0

Yves Dehouck 1,*, Aline Grosfils 2, Benjamin Folch 1, Dimitri Gilis 1, Philippe Bogaerts 2 and Marianne Rooman 1

1Bioinformatique génomique et structurale and 2Modélisation et contrôle de bioprocédés, Université Libre de Bruxelles. Av Fr. Roosevelt 50, CP165/61, 1050 Brussels, Belgium

*To whom correspondence should be addressed.


  Abstract

Motivation: The rational design of proteins with modified properties, through amino acid substitutions, is of crucial importance in a large variety of applications. Given the huge number of possible substitutions, every protein engineering project would benefit strongly from the guidance of in silico methods able to predict rapidly, and with reasonable accuracy, the stability changes resulting from all possible mutations in a protein.

Results: We exploit newly developed statistical potentials, based on a formalism that highlights the coupling between four protein sequence and structure descriptors, and take into account the amino acid volume variation upon mutation. The stability change is expressed as a linear combination of these energy functions, whose proportionality coefficients vary with the solvent accessibility of the mutated residue and are identified with the help of a neural network. A correlation coefficient of R = 0.63 and a root mean square error of {sigma}c = 1.15 kcal/mol between measured and predicted stability changes are obtained upon cross-validation. These scores reach R = 0.79, and {sigma}c = 0.86 kcal/mol after exclusion of 10% outliers. The predictive power of our method is shown to be significantly higher than that of other programs described in the literature.

Availability: http://babylone.ulb.ac.be/popmusic

Contact: ydehouck{at}ulb.ac.be

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Anna Tramontano

Received on March 18, 2009; revised on July 7, 2009; accepted on July 15, 2009

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




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.