Adaptive torsion-angle quasi-statics: a general simulation method with applications to protein structure analysis and design


MOTIVATION The cost of molecular quasi-statics or dynamics simulations increases with the size of the simulated systems, which is a problem when studying biological phenomena that involve large molecules over long time scales. To address this problem, one has often to either increase the processing power (which might be expensive), or make arbitrary simplifications to the system (which might bias the study). RESULTS We introduce adaptive torsion-angle quasi-statics, a general simulation method able to rigorously and automatically predict the most mobile regions in a simulated system, under user-defined precision or time constraints. By predicting and simulating only these most important regions, the adaptive method provides the user with complete control on the balance between precision and computational cost, without requiring him or her to perform a priori, arbitrary simplifications. We build on our previous research on adaptive articulated-body simulation and show how, by taking advantage of the partial rigidification of a molecule, we are able to propose novel data structures and algorithms for adaptive update of molecular forces and energies. This results in a globally adaptive molecular quasi-statics simulation method. We demonstrate our approach on several examples and show how adaptive quasi-statics allows a user to interactively design, modify and study potentially complex protein structures.

DOI: 10.1093/bioinformatics/btm191

Extracted Key Phrases

9 Figures and Tables


Citations per Year

61 Citations

Semantic Scholar estimates that this publication has 61 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Rossi2007AdaptiveTQ, title={Adaptive torsion-angle quasi-statics: a general simulation method with applications to protein structure analysis and design}, author={Romain Rossi and Mathieu Isorce and Sandy Morin and Julien Flocard and Karthik Arumugam and Serge Crouzy and Michel Vivaudou and St{\'e}phane Redon}, journal={Bioinformatics}, year={2007}, volume={23 13}, pages={i408-17} }