Literature DB >> 24624489

An optimized potential function for the calculation of nucleic acid interaction energies I. base stacking.

R L Ornstein, R Rein.   

Abstract

An optimized potential function for base-stacking interactions is constructed. Stacking energies between the complementary pairs of a dimer are calculated as a function of the rotational angle and separation distance. Using several different sets of atomic charges, the electrostatic component in the monopole-monopole approximation (MMA) is compared to the more refined segmented multipole-multipole representation (SMMA); the general features of the stacking minima are found to be correctly reproduced with IEHT or CNDO atomic charges. The electrostatic component is observed to control the location of stacking minima.The MMA, in general, is not a reliable approximation of the SMMA in regions away from minima; however, the MMA is reliable in predicting the location and nature of stacking minima.The attractive part of the Lennard-Jones 6-12 potential is compared to and parameterized against the expressions for the second-order interaction terms composed of multipole-bond polarizability for the polarization energy and transition-dipole bond polariz abilities for approximation of the dispersion energy. The repulsive part of the Lennard-Jones potential is compared to a Kitaygorodski-type repulsive function; changing the exponent from its usual value of 12 to 11.7 gives significantly better agreement with the more refined repulsive function.Stacking minima calculated with the optimized potential method are compared with various perturbation-type treatments. The optimized potential method yields results that compare as well with melting data as do any of the more recent and expensive perturbation methods.

Entities:  

Year:  1978        PMID: 24624489     DOI: 10.1002/bip.1978.360171005

Source DB:  PubMed          Journal:  Biopolymers        ISSN: 0006-3525            Impact factor:   2.505


  50 in total

1.  Experimental Measurement of Aromatic Stacking Affinities in the Context of Duplex DNA.

Authors:  Kevin M Guckian; Barbara A Schweitzer; Rex X-F Ren; Charles J Sheils; Pamela L Paris; Deborah C Tahmassebi; Eric T Kool
Journal:  J Am Chem Soc       Date:  1996-08-28       Impact factor: 15.419

2.  Factors Contributing to Aromatic Stacking in Water: Evaluation in the Context of DNA.

Authors:  Kevin M Guckian; Barbara A Schweitzer; Rex X-F Ren; Charles J Sheils; Deborah C Tahmassebi; Eric T Kool
Journal:  J Am Chem Soc       Date:  2000-02-10       Impact factor: 15.419

3.  Structural analysis of DNA sequence: evidence for lateral gene transfer in Thermotoga maritima.

Authors:  P Worning; L J Jensen; K E Nelson; S Brunak; D W Ussery
Journal:  Nucleic Acids Res       Date:  2000-02-01       Impact factor: 16.971

4.  Bubbles and denaturation in DNA.

Authors:  T S van Erp; S Cuesta-López; M Peyrard
Journal:  Eur Phys J E Soft Matter       Date:  2006-09-07       Impact factor: 1.890

5.  Generic eukaryotic core promoter prediction using structural features of DNA.

Authors:  Thomas Abeel; Yvan Saeys; Eric Bonnet; Pierre Rouzé; Yves Van de Peer
Journal:  Genome Res       Date:  2007-12-20       Impact factor: 9.043

6.  Analyzing the flexibility of RNA structures by constraint counting.

Authors:  Simone Fulle; Holger Gohlke
Journal:  Biophys J       Date:  2008-02-15       Impact factor: 4.033

7.  Quantum chemical studies of nucleic acids: can we construct a bridge to the RNA structural biology and bioinformatics communities?

Authors:  Jiří Šponer; Judit E Šponer; Anton I Petrov; Neocles B Leontis
Journal:  J Phys Chem B       Date:  2010-11-04       Impact factor: 2.991

8.  Determination of base and backbone contributions to the thermodynamics of premelting and melting transitions in B DNA.

Authors:  Liviu Movileanu; James M Benevides; George J Thomas
Journal:  Nucleic Acids Res       Date:  2002-09-01       Impact factor: 16.971

9.  Abundant oligonucleotides common to most bacteria.

Authors:  Colin F Davenport; Burkhard Tümmler
Journal:  PLoS One       Date:  2010-03-23       Impact factor: 3.240

10.  ProSOM: core promoter prediction based on unsupervised clustering of DNA physical profiles.

Authors:  Thomas Abeel; Yvan Saeys; Pierre Rouzé; Yves Van de Peer
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

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