Literature DB >> 18464992

The interaction of carbohydrates and amino acids with aromatic systems studied by density functional and semi-empirical molecular orbital calculations with dispersion corrections.

Raman Sharma1, Jonathan P McNamara, Rajesh K Raju, Mark A Vincent, Ian H Hillier, Claudio A Morgado.   

Abstract

Density functional theory (DFT-D) and semi-empirical (PM3-D) methods having an added dispersion correction have been used to study stabilising carbohydrate-aromatic and amino acid-aromatic interactions. The interaction energy for three simple sugars in different conformations with benzene, all give interaction energies close to 5 kcal mol(-1). Our original parameterization of PM3 (PM3-D) seriously overestimates this value, and has prompted a reparametrization which includes a modified core-core interaction term. With two additional parameters, the carbohydrate complexes, as well as the S22 data set, are well reproduced. The new PM3 scheme (PM3-D*) is found to describe the peptide bond-aromatic ring interactions accurately and, together with the DFT-D method, it is used to investigate the interaction of six amino acids with pyrene. Whilst the peptide backbone can adopt both stacked and T-shaped structures in the complexes with similar interaction energies, there is a preference for the unsaturated ring to adopt a stacked structure. Thus, peptides in which the latter interactions are maximised are likely to be the most effective for the functionalisation of carbon nanotubes.

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Year:  2008        PMID: 18464992     DOI: 10.1039/b719764k

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


  8 in total

1.  The post-SCF quantum chemistry characteristics of inter- and intra-strand stacking interactions in d(CpG) and d(GpC) steps found in B-DNA, A-DNA and Z-DNA crystals.

Authors:  Piotr Cysewski
Journal:  J Mol Model       Date:  2008-11-28       Impact factor: 1.810

2.  DNA-protein π-interactions in nature: abundance, structure, composition and strength of contacts between aromatic amino acids and DNA nucleobases or deoxyribose sugar.

Authors:  Katie A Wilson; Jennifer L Kellie; Stacey D Wetmore
Journal:  Nucleic Acids Res       Date:  2014-04-17       Impact factor: 16.971

3.  Stacking interactions between carbohydrate and protein quantified by combination of theoretical and experimental methods.

Authors:  Michaela Wimmerová; Stanislav Kozmon; Ivona Nečasová; Sushil Kumar Mishra; Jan Komárek; Jaroslav Koča
Journal:  PLoS One       Date:  2012-10-08       Impact factor: 3.240

Review 4.  Enhanced semiempirical QM methods for biomolecular interactions.

Authors:  Nusret Duygu Yilmazer; Martin Korth
Journal:  Comput Struct Biotechnol J       Date:  2015-02-28       Impact factor: 7.271

5.  CH-π Interaction Driven Macroscopic Property Transition on Smart Polymer Surface.

Authors:  Minmin Li; Guangyan Qing; Yuting Xiong; Yuekun Lai; Taolei Sun
Journal:  Sci Rep       Date:  2015-10-29       Impact factor: 4.379

6.  Influence of Trp flipping on carbohydrate binding in lectins. An example on Aleuria aurantia lectin AAL.

Authors:  Josef Houser; Stanislav Kozmon; Deepti Mishra; Sushil K Mishra; Patrick R Romano; Michaela Wimmerová; Jaroslav Koča
Journal:  PLoS One       Date:  2017-12-12       Impact factor: 3.240

Review 7.  CH/π Interactions in Carbohydrate Recognition.

Authors:  Vojtěch Spiwok
Journal:  Molecules       Date:  2017-06-23       Impact factor: 4.411

Review 8.  Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods.

Authors:  Nusret Duygu Yilmazer; Martin Korth
Journal:  Int J Mol Sci       Date:  2016-05-16       Impact factor: 5.923

  8 in total

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