| Literature DB >> 35705797 |
Debasish Mukherjee1,2, Satyabrata Maiti3,4, Prasanta Kumar Gouda3, Richa Sharma3, Parthajit Roy5, Dhananjay Bhattacharyya3,4.
Abstract
The stable three-dimensional structure of RNA is known to play several important biochemical roles, from post-transcriptional gene regulation to enzymatic action. These structures contain double-helical regions, which often have different types of non-canonical base pairs in addition to Watson-Crick base pairs. Hence, it is important to study their structures from experimentally obtained or even predicted ones, to understand their role, or to develop a drug against the potential targets. Molecular Modeling of RNA double helices containing non-canonical base pairs is a difficult process, particularly due to the unavailability of structural features of non-Watson-Crick base pairs. Here we show a composite web-server with an associated database that allows one to generate the structure of RNA double helix containing non-canonical base pairs using consensus parameters obtained from the database. The database classification is followed by an evaluation of the central tendency of the structural parameters as well as a quantitative estimation of interaction strengths. These parameters are used to construct three-dimensional structures of double helices composed of Watson-Crick and/or non-canonical base pairs. Our benchmark study to regenerate double-helical fragments of many experimentally derived RNA structures indicate very high accuracy. This composite server is expected to be highly useful in understanding functions of various pre-miRNA by modeling structures of the molecules and estimating binding efficiency. The database can be accessed from http://hdrnas.saha.ac.in/rnabpdb .Entities:
Keywords: Base pair parameters; Base pair stacking energy; DFT-D; Non-canonical base pair; RNA double-helix generation; Stacking interaction
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Year: 2022 PMID: 35705797 DOI: 10.1007/s12539-022-00528-w
Source DB: PubMed Journal: Interdiscip Sci ISSN: 1867-1462 Impact factor: 3.492