Literature DB >> 17492099

Semi-empirical molecular orbital methods including dispersion corrections for the accurate prediction of the full range of intermolecular interactions in biomolecules.

Jonathan P McNamara1, Ian H Hillier.   

Abstract

Semi-empirical calculations including an empirical dispersive correction are used to calculate intermolecular interaction energies and structures for a large database containing 156 biologically relevant molecules (hydrogen-bonded DNA base pairs, interstrand base pairs, stacked base pairs and amino acid base pairs) for which MP2 and CCSD(T) complete basis set (CBS) limit estimates of the interaction energies are available. The dispersion corrected semi-empirical methods are parameterised against a small training set of 22 complexes having a range of biologically important non-covalent interactions. For the full molecule set (156 complexes), compared to the high-level ab initio database, the mean unsigned errors of the interaction energies at the corrected semi-empirical level are 1.1 (AM1-D) and 1.2 (PM3-D) kcal mol(-1), being a significant improvement over existing AM1 and PM3 methods (8.6 and 8.2 kcal mol(-1)). Importantly, the new semi-empirical methods are capable of describing the diverse range of biological interactions, most notably stacking interactions, which are poorly described by both current AM1 and PM3 methods and by many DFT functionals. The new methods require no more computer time than existing semi-empirical methods and therefore represent an important advance in the study of important biological interactions.

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Year:  2007        PMID: 17492099     DOI: 10.1039/b701890h

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  15 in total

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5.  Fragmentation Spectra Prediction and DNA Adducts Structural Determination.

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7.  Polarized Molecular Orbital Model Chemistry 3. The PMO Method Extended to Organic Chemistry.

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8.  Polarized Molecular Orbital Model Chemistry. II. The PMO Method.

Authors:  Peng Zhang; Luke Fiedler; Hannah R Leverentz; Donald G Truhlar; Jiali Gao
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Review 9.  Computational approaches to predicting the impact of novel bases on RNA structure and stability.

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Journal:  ACS Chem Biol       Date:  2013-10-08       Impact factor: 5.100

Review 10.  Enhanced semiempirical QM methods for biomolecular interactions.

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