Computational Methods for RNA Structure Validation and Improvement.

Published

Journal Article

With increasing recognition of the roles RNA molecules and RNA/protein complexes play in an unexpected variety of biological processes, understanding of RNA structure-function relationships is of high current importance. To make clean biological interpretations from three-dimensional structures, it is imperative to have high-quality, accurate RNA crystal structures available, and the community has thoroughly embraced that goal. However, due to the many degrees of freedom inherent in RNA structure (especially for the backbone), it is a significant challenge to succeed in building accurate experimental models for RNA structures. This chapter describes the tools and techniques our research group and our collaborators have developed over the years to help RNA structural biologists both evaluate and achieve better accuracy. Expert analysis of large, high-resolution, quality-conscious RNA datasets provides the fundamental information that enables automated methods for robust and efficient error diagnosis in validating RNA structures at all resolutions. The even more crucial goal of correcting the diagnosed outliers has steadily developed toward highly effective, computationally based techniques. Automation enables solving complex issues in large RNA structures, but cannot circumvent the need for thoughtful examination of local details, and so we also provide some guidance for interpreting and acting on the results of current structure validation for RNA.

Full Text

Duke Authors

Cited Authors

  • Jain, S; Richardson, DC; Richardson, JS

Published Date

  • January 2015

Published In

Volume / Issue

  • 558 /

Start / End Page

  • 181 - 212

PubMed ID

  • 26068742

Pubmed Central ID

  • 26068742

Electronic International Standard Serial Number (EISSN)

  • 1557-7988

International Standard Serial Number (ISSN)

  • 0076-6879

Digital Object Identifier (DOI)

  • 10.1016/bs.mie.2015.01.007

Language

  • eng