Using motion planning to study RNA folding kinetics. Conference Paper

abstract

• We propose a novel, motion planning based approach to approximately map the energy landscape of an RNA molecule. A key feature of our method is that it provides a sparse map that captures the main features of the energy landscape which can be analyzed to compute folding kinetics. Our method is based on probabilistic roadmap motion planners that we have previously successfully applied to protein folding. In this paper, we provide evidence that this approach is also well suited to RNA. We compute population kinetics and transition rates on our roadmaps using the master equation for a few moderately sized RNA and show that our results compare favorably with results of other existing methods.

authors

• Amato, Nancy
• Thomas, Shawna

published proceedings

• J Comput Biol

author list (cited authors)

• Tang, X., Kirkpatrick, B., Thomas, S., Song, G., & Amato, N. M.

citation count

• 29

complete list of authors

• Tang, Xinyu||Kirkpatrick, Bonnie||Thomas, Shawna||Song, Guang||Amato, Nancy M

publication date

• January 2005

publisher

• Mary Ann Liebert  Publisher

published in

• Journal of Computational Biology  Journal

keywords

• Computational Biology
• Kinetics
• Models, Biological
• Models, Chemical
• Nucleic Acid Conformation
• RNA
• Thermodynamics

PubMed Central ID

• 16108722

Digital Object Identifier (DOI)

• 10.1089/cmb.2005.12.862

start page

• 862

end page

• 881

volume

• 12

issue

• 6

URL

• http://dx.doi.org/10.1089/cmb.2005.12.862