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Bioinformatics Advance Access published online on March 16, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl095
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received January 11, 2006
Revised March 9, 2006
Accepted March 9, 2006

Article

Prediction of viable circular permutants using a graph theoretic approach

Konrad H. Paszkiewicz 1 *, Michael J. E. Sternberg 1, and Michael Lappe 2

1 Structural Bioinformatics Group, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK
2 Max-Planck-Institute for Molecular Genetics, IIhnestraße 63-73, 14195 Berlin, Germany

* To whom correspondence should be addressed.
Konrad H. Paszkiewicz, E-mail: konrad.paszkiewicz{at}imperial.ac.uk


  Abstract

Motivation: In recent years graph-theoretic descriptions have been applied to aid the analysis of a number of complex biological systems. However, such an approach has only just begun to be applied to examine protein structures and the network of interactions between residues with promising results. Here we examine whether a graph measure known as closeness is capable of predicting regions where a protein can be split to form a viable circular permutant. Circular permutants are a powerful experimental tool to probe folding mechanisms and more recently have been used to design split enzyme reporter proteins.

Results: We test our method on an extensive set of experiments carried out on dihydrofolate reductase in which circular permutants were constructed for every amino acid position in the sequence, together with partial data from studies on other proteins. Results show that closeness is capable of correctly identifying significantly more residues which are suitable for circular permutation than solvent accessibility. This has potential implications for the design of successful split enzymes having particular importance for the development of protein-protein interaction screening methods and offers new perspectives on protein folding. More generally, the method illustrates the success with which graph-theoretic measures encapsulate the variety of long and short range interactions between residues during the folding process.

Associate Editor: Keith A Crandall
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