Abstract:
:We investigate a novel approach for studying protein folding that has evolved from robotics motion planning techniques called probabilistic roadmap methods (PRMs). Our focus is to study issues related to the folding process, such as the formation of secondary and tertiary structures, assuming we know the native fold. A feature of our PRM-based framework is that the large sets of folding pathways in the roadmaps it produces, in just a few hours on a desktop PC, provide global information about the protein's energy landscape. This is an advantage over other simulation methods such as molecular dynamics or Monte Carlo methods which require more computation and produce only a single trajectory in each run. In our initial studies, we obtained encouraging results for several small proteins. In this paper, we investigate more sophisticated techniques for analyzing the folding pathways in our roadmaps. In addition to more formally revalidating our previous results, we present a case study showing that our technique captures known folding differences between the structurally similar proteins G and L.
journal_name
Phys Bioljournal_title
Physical biologyauthors
Thomas S,Song G,Amato NMdoi
10.1088/1478-3975/2/4/S09keywords:
subject
Has Abstractpub_date
2005-11-09 00:00:00pages
S148-55issue
4eissn
1478-3967issn
1478-3975pii
S1478-3975(05)06767-1journal_volume
2pub_type
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