Authors: Guang Song, Shawna Thomas, Ken A. Dill, J. Martin Scholtz, Nancy M. Amato

Venue: In Proc. Pac. Symp. of Biocomputing (PSB)
DOI:
Link to Publication

Abstract:
We investigate a novel approach for studying protein folding that has evolvedfrom robotics motion planning techniques calledprobabilistic roadmapmethods(prms). Our focus is to study issues related to the folding process, such as theformation of secondary and tertiary structure,assumingweknowthenativefold.A feature of ourprm-based framework is that the large sets of folding pathwaysin the roadmaps it produces, in a few hours on a desktop PC, provide globalinformation about the protein’s energy landscape. This is an advantage over othersimulation methods such as molecular dynamics or Monte Carlo methods whichrequire more computation and produce only a single trajectory in each run. Inour initial studies, we obtained encouraging results for several small proteins. Inthis paper, we investigate more sophisticated techniques for analyzing the foldingpathways in our roadmaps. In addition to more formally revalidating our previousresults, we present a case study showing our technique captures known foldingdifferences between the structurally similar proteins G and L. 

@inproceedings{Song-appsop-2003, 
 author = {Guang {Song}, Shawna {Thomas}, Ken A. {Dill}, J. Martin {Scholtz}, Nancy M. {Amato}}, 
 booktitle = {In Proc. Pac. Symp. of Biocomputing (PSB)}, 
 doi = {}, 
 number = {}, 
 pages = {240-251}, 
 title = {A Path Planning-based Study of Protein Folding With a Case Study of Hairpin Formation in Protein G and L}, 
 volume = {8}, 
 year = {2003} 
}