Abstract:
:RNA is a unique bio-macromolecule that can both record genetic information and perform biological functions in a variety of molecular processes, including transcription, splicing, translation, and even regulating protein function. RNAs adopt specific three-dimensional conformations to enable their functions. Experimental determination of high-resolution RNA structures using x-ray crystallography is both laborious and demands expertise, thus, hindering our comprehension of RNA structural biology. The computational modeling of RNA structure was a milestone in the birth of bioinformatics. Although computational modeling has been greatly improved over the last decade showing many successful cases, the accuracy of such computational modeling is not only length-dependent but also varies according to the complexity of the structure. To increase credibility, various experimental data were integrated into computational modeling. In this review, we summarize the experiments that can be integrated into RNA structure modeling as well as the computational methods based on these experimental data. We also demonstrate how computational modeling can help the experimental determination of RNA structure. We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.
journal_name
Front Genetjournal_title
Frontiers in geneticsauthors
Li B,Cao Y,Westhof E,Miao Zdoi
10.3389/fgene.2020.574485subject
Has Abstractpub_date
2020-10-26 00:00:00pages
574485issn
1664-8021journal_volume
11pub_type
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journal_title:Frontiers in genetics
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pub_type: 杂志文章,评审
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pub_type: 杂志文章,评审
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pub_type: 杂志文章
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journal_title:Frontiers in genetics
pub_type: 杂志文章
doi:10.3389/fgene.2015.00113
更新日期:2015-03-23 00:00:00
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journal_title:Frontiers in genetics
pub_type: 杂志文章
doi:10.3389/fgene.2016.00208
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