Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models

Andrey Krokhotin, Nikolay V. Dokholyan

Research output: Chapter in Book/Report/Conference proceedingChapter

12 Scopus citations


Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.

Original languageEnglish (US)
Title of host publicationMethods in Enzymology
PublisherAcademic Press Inc.
Number of pages25
StatePublished - 2015

Publication series

NameMethods in Enzymology
ISSN (Print)0076-6879
ISSN (Electronic)1557-7988

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology


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