QCRNA 1.0: A database of quantum calculations for RNA catalysis

Timothy J. Giese, Brent A. Gregersen, Yun Liu, Kwangho Nam, Evelyn Mayaan, Adam Moser, Kevin Range, Olalla Nieto Faza, Carlos Silva Lopez, Angel Rodriguez de Lera, Gijs Schaftenaar, Xabier Lopez, Tai Sung Lee, George Karypis, Darrin M. York

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

This work outlines a new on-line database of quantum calculations for RNA catalysis (QCRNA) available via the worldwide web at http://theory.chem.umn.edu/QCRNA. The database contains high-level density functional calculations for a large range of molecules, complexes and chemical mechanisms important to phosphoryl transfer reactions and RNA catalysis. Calculations are performed using a strict, consistent protocol such that a wealth of cross-comparisons can be made to elucidate meaningful trends in biological phosphate reactivity. Currently, around 2000 molecules have been collected in varying charge states in the gas phase and in solution. Solvation was treated with both the PCM and COSMO continuum solvation models. The data can be used to study important trends in reactivity of biological phosphates, or used as benchmark data for the design of new semiempirical quantum models for hybrid quantum mechanical/molecular mechanical simulations.

Original languageEnglish (US)
Pages (from-to)423-433
Number of pages11
JournalJournal of Molecular Graphics and Modelling
Volume25
Issue number4
DOIs
StatePublished - Dec 2006

Bibliographical note

Funding Information:
D.Y. is grateful for financial support provided by the National Institutes of Health (Grant GM62248), and the Army High Performance Computing Research Center (AHPCRC) under the auspices of the Department of the Army, Army Research Laboratory (ARL) under Cooperative Agreement number DAAD19-01-2-0014. O.N.F. and X.L. thank the Minnesota Supercomputing Institute for funding through Research Scholar awards, and T.-S.L. thanks the University of Minnesota for partial funding as part of the Consortium for Bioinformatics and Computational Biology initiative. D.Y., G.K., and T.-S.L. thank the IBM-Rochester Life Sciences Group for graduate funding (Y.L.) for this project. Computational resources were provided by the Minnesota Super-computing Institute.

Keywords

  • Database
  • Density functional theory
  • Potential energy surfaces
  • RNA catalysis
  • Reaction mechanism

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