Document Detail


Multiscale Modeling of Double-Helical DNA and RNA: A Unification through Lie Groups.
MedLine Citation:
PMID:  22676719     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Several different mechanical models of double-helical nucleic-acid structures that have been presented in the literature are reviewed here together with a new analysis method that provides a reconciliation between these disparate models. In all cases, terminology and basic results from the theory of Lie groups are used to describe rigid-body motions in a coordinate-free way, and when necessary, coordinates are introduced in a way in which simple equations result. We consider double-helical DNAs and RNAs which, in their unstressed referential state, have backbones that are either straight, slightly precurved, or bent by the action of a protein or other bound molecule. At the coarsest level, we consider worm-like chains with anisotropic bending stiffness. Then, we show how bi-rod models converge to this for sufficiently long filament lengths. At a finer level, we examine elastic networks of rigid bases and show how these relate to the coarser models. Finally, we show how results from molecular dynamics simulation at full atomic resolution (which is the finest scale considered here) and AFM experimental measurements (which is at the coarsest scale) relate to these models.
Authors:
Kevin C Wolfe; Whitney A Hastings; Samrat Dutta; Andrew Long; Bruce A Shapiro; Thomas B Woolf; Martin Guthold; Gregory S Chirikjian
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-6-7
Journal Detail:
Title:  The journal of physical chemistry. B     Volume:  -     ISSN:  1520-5207     ISO Abbreviation:  -     Publication Date:  2012 Jun 
Date Detail:
Created Date:  2012-6-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101157530     Medline TA:  J Phys Chem B     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Department of Mechanical Engineering, Johns Hopkins University , Baltimore, Maryland, United States.
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