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Título : | DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation | Autor : | Franco, Bruno A. Luciano, Ezequiel R. Sarotti, Ariel M. Zanardi, María M. |
Palabras clave : | QUIMICA COMPUTACIONAL; DP4 | Fecha de publicación : | 2023 | Editorial : | ASC | Cita : | Franco, B. A. DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation [en línea]. Journal of Natural Products. 2023. doi: 10.1021/acs.jnatprod.3c00566. Disponible en: https://repositorio.uca.edu.ar/handle/123456789/17239 | Resumen : | Abstract: DP4+ is one of the most popular methods for the structure elucidation of natural products using NMR calculations. While the method is simple and easy to implement, it requires a series of procedures that can be tedious, coupled with the fact that its computational demand can be high in certain cases. In this work, we made a substantial improvement to these limitations. First, we deeply explored the effect of molecular mechanics architecture on the DP4+ formalism (MM-DP4+). In addition, a Python applet (DP4+App) was developed to automate the entire process, requiring only the Gaussian NMR output files and a spreadsheet containing the experimental NMR data and labels. The script is designed to use the statistical parameters from the original 24 levels of theory (employing B3LYP/6-31G* geometries) and the new 36 levels explored in this work (over MMFF geometries). Furthermore, it enables the development of customizable methods using any desired level of theory, allowing for a free choice of test molecules. | URI : | https://repositorio.uca.edu.ar/handle/123456789/17239 | ISSN : | 0163-3864 | Disciplina: | QUIMICA | DOI: | 10.1021/acs.jnatprod.3c00566 | Derechos: | Acceso abierto |
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