Literature DB >> 28102461

RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs.

Dhananjay Bhattacharyya1, Sukanya Halder2, Sankar Basu3,4, Debasish Mukherjee2, Prasun Kumar5, Manju Bansal6.   

Abstract

Comprehensive analyses of structural features of non-canonical base pairs within a nucleic acid double helix are limited by the availability of a small number of three dimensional structures. Therefore, a procedure for model building of double helices containing any given nucleotide sequence and base pairing information, either canonical or non-canonical, is seriously needed. Here we describe a program RNAHelix, which is an updated version of our widely used software, NUCGEN. The program can regenerate duplexes using the dinucleotide step and base pair orientation parameters for a given double helical DNA or RNA sequence with defined Watson-Crick or non-Watson-Crick base pairs. The original structure and the corresponding regenerated structure of double helices were found to be very close, as indicated by the small RMSD values between positions of the corresponding atoms. Structures of several usual and unusual double helices have been regenerated and compared with their original structures in terms of base pair RMSD, torsion angles and electrostatic potentials and very high agreements have been noted. RNAHelix can also be used to generate a structure with a sequence completely different from an experimentally determined one or to introduce single to multiple mutation, but with the same set of parameters and hence can also be an important tool in homology modeling and study of mutation induced structural changes.

Keywords:  Base pair parameters; Dinucleotide step parameters; Electrostatic potential; Molecular modeling; Non Watson–Crick base pairs; RNA

Mesh:

Substances:

Year:  2017        PMID: 28102461     DOI: 10.1007/s10822-016-0007-0

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  51 in total

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Journal:  J Mol Biol       Date:  1993-04-05       Impact factor: 5.469

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Authors:  S R Holbrook; C Cheong; I Tinoco; S H Kim
Journal:  Nature       Date:  1991-10-10       Impact factor: 49.962

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