<br/>Computational methods for the prediction of NMR spectra are well established. Our group has previously developed the DP4 parameter, which provides a confidence level for the match between calculated and experimental NMR spectra. This method has been widely used to help assign the structures of many stereochemically-rich molecules. We present an improved version of the procedure, which can be downloaded as Python script instead of running within a web-browser, and which analyses output from open-source molecular modelling programs (TINKER and NWChem) in addition to being able to use output from commercial packages (Schrodinger's Macromodel and Jaguar; Gaussian). The new open-source workflow incorporates a method for the automatic generation of diastereomers using InChI strings and has been tested on a range of new structures. This improved workflow permits the rapid and convenient computational elucidation of structure and relative stereochemistry.<br/>Various improvements in the underlying statistical methods of DP4 have also been made. Fitted Gaussian distributions have been replaced by empirical distributions and this has lead to a more accurate estimate of confidence in the correct structure.<br/>The accuracy of current DFT methods of chemical shift prediction shows some dependence on the chemical shift. Chemical shift-dependant error models have been explored and improve the overall performance of the method.<br/>Coupling constants are sensitive to the geometry of organic molecules and contain useful information for the elucidation of relative stereochemistry. To exploit this, we have implemented the calculation of coupling constants using both a generalised Karplus equation and DFT methods in the DP4 workflow. The corresponding error models have been developed and the results are combined with the chemical shift data for improved overall performance in diastereomer identification.

Structure elucidation of organic compounds by NMR: DP4 made easy

251st National Meeting (2016)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.