Computational approaches to predicting the impact of novel bases on RNA structure and stability

Jason G. Harrison, Yvonne B. Zheng, Peter A. Beal, Dean J. Tantillo

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The use of computational modeling techniques to gain insight into nucleobase interactions has been a challenging endeavor to date. Accurate treatment requires the tackling of many challenges but also holds the promise of great rewards. The development of effective computational approaches to predict the binding affinities of nucleobases and analogues can, for example, streamline the process of developing novel nucleobase modifications, which should facilitate the development of new RNAi-based therapeutics. This brief review focuses on available computational approaches to predicting base pairing affinity in RNA-based contexts such as nucleobase-nucleobase interactions in duplexes and nucleobase-protein interactions. The challenges associated with such modeling along with potential future directions for the field are highlighted.

Original languageEnglish (US)
Pages (from-to)2354-2359
Number of pages6
JournalACS Chemical Biology
Volume8
Issue number11
DOIs
StatePublished - Nov 15 2013

Fingerprint

RNA Stability
Reward
Base Pairing
RNA
Proteins
Therapeutics
RNAi Therapeutics
Direction compound

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Medicine
  • Medicine(all)

Cite this

Computational approaches to predicting the impact of novel bases on RNA structure and stability. / Harrison, Jason G.; Zheng, Yvonne B.; Beal, Peter A.; Tantillo, Dean J.

In: ACS Chemical Biology, Vol. 8, No. 11, 15.11.2013, p. 2354-2359.

Research output: Contribution to journalArticle

Harrison, Jason G. ; Zheng, Yvonne B. ; Beal, Peter A. ; Tantillo, Dean J. / Computational approaches to predicting the impact of novel bases on RNA structure and stability. In: ACS Chemical Biology. 2013 ; Vol. 8, No. 11. pp. 2354-2359.
@article{aaf38b3e6a10465a8149ed60610cce22,
title = "Computational approaches to predicting the impact of novel bases on RNA structure and stability",
abstract = "The use of computational modeling techniques to gain insight into nucleobase interactions has been a challenging endeavor to date. Accurate treatment requires the tackling of many challenges but also holds the promise of great rewards. The development of effective computational approaches to predict the binding affinities of nucleobases and analogues can, for example, streamline the process of developing novel nucleobase modifications, which should facilitate the development of new RNAi-based therapeutics. This brief review focuses on available computational approaches to predicting base pairing affinity in RNA-based contexts such as nucleobase-nucleobase interactions in duplexes and nucleobase-protein interactions. The challenges associated with such modeling along with potential future directions for the field are highlighted.",
author = "Harrison, {Jason G.} and Zheng, {Yvonne B.} and Beal, {Peter A.} and Tantillo, {Dean J.}",
year = "2013",
month = "11",
day = "15",
doi = "10.1021/cb4006062",
language = "English (US)",
volume = "8",
pages = "2354--2359",
journal = "ACS Chemical Biology",
issn = "1554-8929",
publisher = "American Chemical Society",
number = "11",

}

TY - JOUR

T1 - Computational approaches to predicting the impact of novel bases on RNA structure and stability

AU - Harrison, Jason G.

AU - Zheng, Yvonne B.

AU - Beal, Peter A.

AU - Tantillo, Dean J.

PY - 2013/11/15

Y1 - 2013/11/15

N2 - The use of computational modeling techniques to gain insight into nucleobase interactions has been a challenging endeavor to date. Accurate treatment requires the tackling of many challenges but also holds the promise of great rewards. The development of effective computational approaches to predict the binding affinities of nucleobases and analogues can, for example, streamline the process of developing novel nucleobase modifications, which should facilitate the development of new RNAi-based therapeutics. This brief review focuses on available computational approaches to predicting base pairing affinity in RNA-based contexts such as nucleobase-nucleobase interactions in duplexes and nucleobase-protein interactions. The challenges associated with such modeling along with potential future directions for the field are highlighted.

AB - The use of computational modeling techniques to gain insight into nucleobase interactions has been a challenging endeavor to date. Accurate treatment requires the tackling of many challenges but also holds the promise of great rewards. The development of effective computational approaches to predict the binding affinities of nucleobases and analogues can, for example, streamline the process of developing novel nucleobase modifications, which should facilitate the development of new RNAi-based therapeutics. This brief review focuses on available computational approaches to predicting base pairing affinity in RNA-based contexts such as nucleobase-nucleobase interactions in duplexes and nucleobase-protein interactions. The challenges associated with such modeling along with potential future directions for the field are highlighted.

UR - http://www.scopus.com/inward/record.url?scp=84887878749&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887878749&partnerID=8YFLogxK

U2 - 10.1021/cb4006062

DO - 10.1021/cb4006062

M3 - Article

C2 - 24063428

AN - SCOPUS:84887878749

VL - 8

SP - 2354

EP - 2359

JO - ACS Chemical Biology

JF - ACS Chemical Biology

SN - 1554-8929

IS - 11

ER -