Computational Methods for RNA Structure Validation and Improvement.
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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.
RNA backbone conformers
Data Interpretation, Statistical
Nucleic Acid Conformation
Published Version (Please cite this version)10.1016/bs.mie.2015.01.007
Publication InfoJain, Swati; Richardson, David C; & Richardson, Jane S (2015). Computational Methods for RNA Structure Validation and Improvement. Methods Enzymol, 558. pp. 181-212. 10.1016/bs.mie.2015.01.007. Retrieved from https://hdl.handle.net/10161/10807.
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Professor of Biochemistry
Protein structure, folding, and design; 3D computer graphics; x-ray crystallography.
James B. Duke Distinguished Professor of Medicine
3D structure of macromolecules; molecular graphics; protein folding and design; all-atom contacts; x-ray crystallography; structure validation.
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