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      NMR and DFT investigations of structure of colchicine in various solvents including density functional theory calculations

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      Scientific Reports
      Nature Publishing Group UK

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          Abstract

          A detailed NMR investigation of the chemical shifts of hydrogen and carbon atoms associated with the structure of the naturally occurring alkaloid colchicine was conducted using high field NMR. Initially, the experimental chemical shifts for colchicine in chloroform and DMSO were compared to the values calculated using density functional theory (DFT). There were significant deviations observed for the chloroform solvent, but these were only slight in the DMSO solution. Dilution of the chloroform solution changed the experimental chemical shifts and improved agreement with the DFT calculations, suggesting self-aggregation at higher concentrations. A dimeric model was proposed for which agreement with the DFT calculated chemical shifts was better than for corresponding monomeric structures. Three further solvents were studied to evaluate changes in chemical shift values at different dilutions. Chloroform, benzene and water showed significant chemical shift changes implying self-aggregation, whereas DMSO and acetone did not show significant change upon dilution.

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          The IEF version of the PCM solvation method: an overview of a new method addressed to study molecular solutes at the QM ab initio level

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            Computational prediction of 1H and 13C chemical shifts: a useful tool for natural product, mechanistic, and synthetic organic chemistry.

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              A guide to small-molecule structure assignment through computation of (¹H and ¹³C) NMR chemical shifts.

              This protocol is intended to provide chemists who discover or make new organic compounds with a valuable tool for validating the structural assignments of those new chemical entities. Experimental ¹H and/or ¹³C NMR spectral data and its proper interpretation for the compound of interest is required as a starting point. The approach involves the following steps: (i) using molecular mechanics calculations (with, e.g., MacroModel) to generate a library of conformers; (ii) using density functional theory (DFT) calculations (with, e.g., Gaussian 09) to determine optimal geometry, free energies and chemical shifts for each conformer; (iii) determining Boltzmann-weighted proton and carbon chemical shifts; and (iv) comparing the computed chemical shifts for two or more candidate structures with experimental data to determine the best fit. For a typical structure assignment of a small organic molecule (e.g., fewer than ∼10 non-H atoms or up to ∼180 a.m.u. and ∼20 conformers), this protocol can be completed in ∼2 h of active effort over a 2-d period; for more complex molecules (e.g., fewer than ∼30 non-H atoms or up to ∼500 a.m.u. and ∼50 conformers), the protocol requires ∼3-6 h of active effort over a 2-week period. To demonstrate the method, we have chosen the analysis of the cis- versus the trans-diastereoisomers of 3-methylcyclohexanol (1-cis versus 1-trans). The protocol is written in a manner that makes the computation of chemical shifts tractable for chemists who may otherwise have only rudimentary computational experience.
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                Author and article information

                Contributors
                t.venkatachalam@uq.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                17 July 2017
                17 July 2017
                2017
                : 7
                : 5605
                Affiliations
                ISNI 0000 0000 9320 7537, GRID grid.1003.2, The Centre for Advanced Imaging, , The University of Queensland, ; Building 57, Research Road, St. Lucia, Queensland 4072 Australia
                Author information
                http://orcid.org/0000-0002-4731-4045
                Article
                6005
                10.1038/s41598-017-06005-5
                5514032
                28717218
                781c7bf1-d97e-4a8d-9753-84d766d2dc8b
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 December 2016
                : 5 June 2017
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