DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation

Autores
Franco, Bruno A.; Luciano, Ezequiel R.; Sarotti, Ariel M.; Zanardi, María M.
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fil: Franco, Bruno A. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
Fil: Luciano, Ezequiel R. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
Fil: Sarotti, Ariel M. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Sarotti, Ariel M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Química Rosario; Argentina
Fil: Zanardi, María M. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
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.
Fuente
Journal of Natural Products. 2023.
Materia
QUIMICA COMPUTACIONAL
DP4
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
Repositorio Institucional (UCA)
Institución
Pontificia Universidad Católica Argentina
OAI Identificador
oai:ucacris:123456789/17239
Acceder
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oai_identifier_str oai:ucacris:123456789/17239
network_acronym_str RIUCA
repository_id_str 2585
network_name_str Repositorio Institucional (UCA)
spelling DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and AutomationFranco, Bruno A.Luciano, Ezequiel R.Sarotti, Ariel M.Zanardi, María M.QUIMICA COMPUTACIONALDP4Fil: Franco, Bruno A. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; ArgentinaFil: Luciano, Ezequiel R. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; ArgentinaFil: Sarotti, Ariel M. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; ArgentinaFil: Sarotti, Ariel M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Química Rosario; ArgentinaFil: Zanardi, María M. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; ArgentinaAbstract: 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.ASC2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://repositorio.uca.edu.ar/handle/123456789/172390163-386410.1021/acs.jnatprod.3c00566Franco, 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/123456789/17239Journal of Natural Products. 2023.reponame:Repositorio Institucional (UCA)instname:Pontificia Universidad Católica Argentinaenginfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/2025-07-03T10:59:33Zoai:ucacris:123456789/17239instacron:UCAInstitucionalhttps://repositorio.uca.edu.ar/Universidad privadaNo correspondehttps://repositorio.uca.edu.ar/oaiclaudia_fernandez@uca.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:25852025-07-03 10:59:33.948Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentinafalse
dc.title.none.fl_str_mv DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
title DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
spellingShingle DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
Franco, Bruno A.
QUIMICA COMPUTACIONAL
DP4
title_short DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
title_full DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
title_fullStr DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
title_full_unstemmed DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
title_sort DP4+App: Finding the Best Balance between Computational Cost and Predictive Capacity in the Structure Elucidation Process by DP4+. Factors Analysis and Automation
dc.creator.none.fl_str_mv Franco, Bruno A.
Luciano, Ezequiel R.
Sarotti, Ariel M.
Zanardi, María M.
author Franco, Bruno A.
author_facet Franco, Bruno A.
Luciano, Ezequiel R.
Sarotti, Ariel M.
Zanardi, María M.
author_role author
author2 Luciano, Ezequiel R.
Sarotti, Ariel M.
Zanardi, María M.
author2_role author
author
author
dc.subject.none.fl_str_mv QUIMICA COMPUTACIONAL
DP4
topic QUIMICA COMPUTACIONAL
DP4
dc.description.none.fl_txt_mv Fil: Franco, Bruno A. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
Fil: Luciano, Ezequiel R. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
Fil: Sarotti, Ariel M. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina
Fil: Sarotti, Ariel M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Química Rosario; Argentina
Fil: Zanardi, María M. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
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.
description Fil: Franco, Bruno A. Pontificia Universidad Católica Argentina. Facultad de Química e Ingeniería del Rosario. Instituto de Investigaciones en Ingeniería Ambiental, Química y Biotecnología Aplicada; Argentina
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://repositorio.uca.edu.ar/handle/123456789/17239
0163-3864
10.1021/acs.jnatprod.3c00566
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
url https://repositorio.uca.edu.ar/handle/123456789/17239
identifier_str_mv 0163-3864
10.1021/acs.jnatprod.3c00566
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
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv ASC
publisher.none.fl_str_mv ASC
dc.source.none.fl_str_mv Journal of Natural Products. 2023.
reponame:Repositorio Institucional (UCA)
instname:Pontificia Universidad Católica Argentina
reponame_str Repositorio Institucional (UCA)
collection Repositorio Institucional (UCA)
instname_str Pontificia Universidad Católica Argentina
repository.name.fl_str_mv Repositorio Institucional (UCA) - Pontificia Universidad Católica Argentina
repository.mail.fl_str_mv claudia_fernandez@uca.edu.ar
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score 13.13397

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