Protein folding by motion planning

Shawna Thomas, Guang Song, Nancy M. Amato

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)S148-S155
JournalPhysical Biology
Volume2
Issue number4
DOIs
StatePublished - Dec 1 2005
Externally publishedYes

ASJC Scopus subject areas

  • Biophysics
  • Structural Biology
  • Molecular Biology
  • Cell Biology

Fingerprint Dive into the research topics of 'Protein folding by motion planning'. Together they form a unique fingerprint.

Cite this