当前位置： SCI文献检索 > JOURNAL OF MOLECULAR BIOLOGY期刊下所有文献 > Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure.

Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure.

Abstract：

:Quantitatively describing RNA structure and conformational elements remains a formidable problem. Seven standard torsion angles and the sugar pucker are necessary to characterize the conformation of an RNA nucleotide completely. Progress has been made toward understanding the discrete nature of RNA structure, but classifying simple and ubiquitous structural elements such as helices and motifs remains a difficult task. One approach for describing RNA structure in a simple, mathematically consistent, and computationally accessible manner involves the invocation of two pseudotorsions, eta (C4'(n-1), P(n), C4'(n), P(n+1)) and theta (P(n), C4'(n), P(n+1), C4'(n+1)), which can be used to describe RNA conformation in much the same way that varphi and psi are used to describe backbone configuration of proteins. Here, we conduct an exploration and statistical evaluation of pseudotorsional space and of the Ramachandran-like eta-theta plot. We show that, through the rigorous quantitative analysis of the eta-theta plot, the pseudotorsional descriptors eta and theta, together with sugar pucker, are sufficient to describe RNA backbone conformation fully in most cases. These descriptors are also shown to contain considerable information about nucleotide base conformation, revealing a previously uncharacterized interplay between backbone and base orientation. A window function analysis is used to discern statistically relevant regions of density in the eta-theta scatter plot and then nucleotides in colocalized clusters in the eta-theta plane are shown to have similar 3-D structures through RMSD analysis of the RNA structural constituents. We find that major clusters in the eta-theta plot are few, underscoring the discrete nature of RNA backbone conformation. Like the Ramachandran plot, the eta-theta plot is a valuable system for conceptualizing biomolecular conformation, it is a useful tool for analyzing RNA tertiary structures, and it is a vital component of new approaches for solving the 3-D structures of large RNA molecules and RNA assemblies.

journal_name

J Mol Biol

journal_title

Journal of molecular biology

authors

Wadley LM,Keating KS,Duarte CM,Pyle AM

doi

10.1016/j.jmb.2007.06.058

subject

Has Abstract

pub_date

2007-09-28 00:00:00

pages

942-957

issue

eissn

0022-2836

issn

1089-8638

pii

S0022-2836(07)00850-9

journal_volume

372

pub_type

杂志文章

在线工具

Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure.