PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A simple genetic algorithm for the optimization of multidomain protein homology models driven by NMR residual dipolar coupling and small angle X-ray scattering data
Fabien Mareuil, Christina Sizun, Javier Perez, Marc Schoenauer, Jean-Yves Lallemand and François Bontems
European Biophysics Journal Volume 37, Number 1, 95-1-4, 2007.

Abstract

Most proteins comprise several domains and/or participate in functional complexes. Owing to ongoing structural genomic projects, it is likely that it will soon be possible to predict, with reasonable accuracy, the con- served regions of most structural domains. Under these circumstances, it will be important to have methods, based on simple-to-acquire experimental data, that allow to build and refine structures of multi-domain proteins or of protein complexes from homology models of the individual do- mains/proteins. It has been recently shown that small angle X-ray scattering (SAXS) and NMR residual dipolar cou- pling (RDC) data can be combined to determine the architecture of such objects when the X-ray structures of the domains are known and can be considered as rigid objects. We developed a simple genetic algorithm to achieve the same goal, but by using homology models of the domains considered as deformable objects. We applied it to two model systems, an S1KH bi-domain of the NusA protein and the cS-crystallin protein. Despite its simplicity our algorithm is able to generate good solutions when driven by SAXS and RDC data.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3170
Deposited By:Marc Schoenauer
Deposited On:03 January 2008