Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos

Detalhes bibliográficos
Autor(a) principal: Cabral, Patrik Ferreira Gandara
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
Texto Completo: https://tede.unioeste.br/handle/tede/7216
Resumo: The present work is in the field of Computational Chemistry combined with Density Functional Theory (DFT) to provide in silico approaches, which assist in experimental planning activities, processing of 1H and 13C Nuclear Magnetic Resonance (NMR) data, conformational search, and identification of compounds with unclear spatial structure. The compounds evaluated were Cannabidiol (CBD), Δ9 Tetrahydrocannabinol (THC) and Canabinol (CBN), which are specialized metabolites of Cannabis sativa and have clinical and forensic relevance. Macromodel® and Gaussian® were used, respectively, in Molecular Mechanics and Quantum Mechanics optimizations. Subsequently, the population distribution (Boltzman) of the conformers found was verified and the most representative ones were selected to simulate NMR spectra at eight levels of theory. It was found that the theoretical level DFT/PBE0/6-311G+(2d,p) was the most accurate for the compounds studied, obtaining MAD and RMSE values close to the experimental chemical shifts (δ). It was found that the use of the internal standard Dioxane significantly improved the accuracy of the theoretical δ for 13C. While the use of tetramethylsilane (TMS) or Dioxane did not show the same significance in the 1H simulations. A possible inversion of the C8 and C9 methyls of Δ9 THC attributed in the literature was investigated. Thus, it was concluded, by means of the MAD values and after an intentional inversion of the theoretical δ values, that these were diastereotopic carbons. Therefore, C8 and C9 methyls have been reported inverted in the literature. The best levels of theory were compared using the DFT method versus the Hartree-Fock method, and the DFT method was found to be the most accurate. Electronic property data was obtained, such as HOMO, LUMO, Hardness, Softness, electronegativity and electrophilicity, and reactivity issues were discussed together with the Electrostatic Potential Map. It was verified that the results were coherent regarding the chemical nature of the compounds under study. Finally, the computational processing time for each stage of this work was verified. It was observed that molecular flexibility is directly proportional to processing time. Therefore, the present work concluded that Computational Chemistry is an important tool in the optimization and prediction of molecular studies.
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spelling Rosset, Isac Georgehttp://lattes.cnpq.br/4493032120506685Rosset, Isac Georgehttp://lattes.cnpq.br/4493032120506685Oliveira, Adriana Ferla dehttp://lattes.cnpq.br/8320953119053085Melo, Eduardo Borges dehttp://lattes.cnpq.br/0732955060928431http://lattes.cnpq.br/2418001242586375Cabral, Patrik Ferreira Gandara2024-05-25T00:11:56Z2023-10-04CABRAL, Patrik Ferreira Gandara. Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos. 2023.99 f. Dissertação (Merstrado em Química) - Universidade Estadual do Oeste do Paraná, Toledo, 2023.https://tede.unioeste.br/handle/tede/7216The present work is in the field of Computational Chemistry combined with Density Functional Theory (DFT) to provide in silico approaches, which assist in experimental planning activities, processing of 1H and 13C Nuclear Magnetic Resonance (NMR) data, conformational search, and identification of compounds with unclear spatial structure. The compounds evaluated were Cannabidiol (CBD), Δ9 Tetrahydrocannabinol (THC) and Canabinol (CBN), which are specialized metabolites of Cannabis sativa and have clinical and forensic relevance. Macromodel® and Gaussian® were used, respectively, in Molecular Mechanics and Quantum Mechanics optimizations. Subsequently, the population distribution (Boltzman) of the conformers found was verified and the most representative ones were selected to simulate NMR spectra at eight levels of theory. It was found that the theoretical level DFT/PBE0/6-311G+(2d,p) was the most accurate for the compounds studied, obtaining MAD and RMSE values close to the experimental chemical shifts (δ). It was found that the use of the internal standard Dioxane significantly improved the accuracy of the theoretical δ for 13C. While the use of tetramethylsilane (TMS) or Dioxane did not show the same significance in the 1H simulations. A possible inversion of the C8 and C9 methyls of Δ9 THC attributed in the literature was investigated. Thus, it was concluded, by means of the MAD values and after an intentional inversion of the theoretical δ values, that these were diastereotopic carbons. Therefore, C8 and C9 methyls have been reported inverted in the literature. The best levels of theory were compared using the DFT method versus the Hartree-Fock method, and the DFT method was found to be the most accurate. Electronic property data was obtained, such as HOMO, LUMO, Hardness, Softness, electronegativity and electrophilicity, and reactivity issues were discussed together with the Electrostatic Potential Map. It was verified that the results were coherent regarding the chemical nature of the compounds under study. Finally, the computational processing time for each stage of this work was verified. It was observed that molecular flexibility is directly proportional to processing time. Therefore, the present work concluded that Computational Chemistry is an important tool in the optimization and prediction of molecular studies.O presente trabalho se situa no campo da Química Computacional combinada à Teoria Funcional de Densidade (DFT) no intuito de prover abordagens in silico, que auxiliem nas atividades de planejamento experimental, tratamento de dados de Ressonância Magnética Nuclear (RMN) de 1H e 13C, busca conformacional e identificação de compostos com indefinição da sua estrutura espacial. Os compostos avaliados foram o Canabidiol (CBD), Δ9 Tetrahidrocanabinol (THC) e Canabinol (CBN), que são metabólitos especializados da Cannabis sativa e possuem relevância clínica e forense. Utilizou-se o Macromodel® e o Gaussian®, respectivamente, nas otimizações de Mecânica Molecular e Mecânica Quântica. Posteriormente, a distribuição populacional (Boltzman) dos confôrmeros encontrados foi verificada e os mais representativos foram selecionados à simulação de espectros de RMN em oito níveis de teoria. Verificou-se que o nível teórico DFT/PBE0/6-311G+(2d,p) foi o de maior exatidão para os compostos estudados, obtendo-se valores de MAD e RMSE próximo aos deslocamentos químicos (δ) experimentais. Verificou-se que o uso do padrão interno Dioxano melhorou significativamente a exatidão do δ teórico para 13C. Enquanto, que o uso de tetrametilsilano (TMS) ou Dioxano não apresentaram a mesma significância nas simulações de 1H. Investigou-se uma possível inversão das metilas C8 e C9 do Δ9 THC atribuídas na literatura. Assim, concluiu-se, por meio dos valores de MAD e após uma inversão intencional dos valores do δ teóricos, que se tratava de carbonos diastereotópicos. Portanto, as metilas C8 e C9 foram reportadas invertidas na literatura. Comparou-se os melhores níveis de teoria pelo método DFT versus Método Hartree-Fock, verificou o método DFT foi o mais exato. Obtiveram-se os dados de propriedade eletrônica, tais como, HOMO, LUMO, Dureza, Moleza, eletronegatividade e eletrofilicidade, sendo discutidos questões de reatividade junto ao Mapa de Potencial Eletrostático. Verificou-se que os resultados tinham coerência quanto à natureza química dos compostos em estudo. Por fim, verificou-se o tempo de processamento computacional de cada etapa deste trabalho. Observou-se que a flexibilidade molecular é diretamente proporcional ao tempo de processamento. Portanto, o presente trabalho concluiu que a Química Computacional é uma importante ferramenta na otimização e predição de estudos moleculares.Submitted by Marilene Donadel (marilene.donadel@unioeste.br) on 2024-05-25T00:11:56Z No. of bitstreams: 1 Patrik_Cabral_2023.pdf: 4017670 bytes, checksum: 2a7e4f095707d9ab362c787b3b24418f (MD5)Made available in DSpace on 2024-05-25T00:11:56Z (GMT). No. of bitstreams: 1 Patrik_Cabral_2023.pdf: 4017670 bytes, checksum: 2a7e4f095707d9ab362c787b3b24418f (MD5) Previous issue date: 2023-10-04application/pdfpor-2624803687637593200500Universidade Estadual do Oeste do ParanáToledoPrograma de Pós-Graduação em QuímicaUNIOESTEBrasilCentro de Engenharias e Ciências Exatashttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessTeoria Funcional de Densidade (DFT)Ressonância Magnética Nuclear (RMN)Química computacionalCanabinoides e diastereotópicoDensity Functional Theory (DFT);Nuclear Magnetic Resonance (NMR)Computational chemistryCannabinoids and diastereotopicCIENCIAS EXATAS E DA TERRA::QUIMICACálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticosCalculations of 1H and 13C NMR chemical shifts and electronic properties of cannabinoids using quantum calculationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis1435648362225100898600600600-77344021240821469221571700325303117195reponame:Biblioteca Digital de Teses e Dissertações do UNIOESTEinstname:Universidade Estadual do Oeste do Paraná (UNIOESTE)instacron:UNIOESTEORIGINALPatrik_Cabral_2023.pdfPatrik_Cabral_2023.pdfapplication/pdf4017670http://tede.unioeste.br:8080/tede/bitstream/tede/7216/2/Patrik_Cabral_2023.pdf2a7e4f095707d9ab362c787b3b24418fMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://tede.unioeste.br:8080/tede/bitstream/tede/7216/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51tede/72162024-05-24 21:11:56.926oai:tede.unioeste.br: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Biblioteca Digital de Teses e Dissertaçõeshttp://tede.unioeste.br/PUBhttp://tede.unioeste.br/oai/requestbiblioteca.repositorio@unioeste.bropendoar:2024-05-25T00:11:56Biblioteca Digital de Teses e Dissertações do UNIOESTE - Universidade Estadual do Oeste do Paraná (UNIOESTE)false
dc.title.por.fl_str_mv Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
dc.title.alternative.eng.fl_str_mv Calculations of 1H and 13C NMR chemical shifts and electronic properties of cannabinoids using quantum calculations
title Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
spellingShingle Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
Cabral, Patrik Ferreira Gandara
Teoria Funcional de Densidade (DFT)
Ressonância Magnética Nuclear (RMN)
Química computacional
Canabinoides e diastereotópico
Density Functional Theory (DFT);
Nuclear Magnetic Resonance (NMR)
Computational chemistry
Cannabinoids and diastereotopic
CIENCIAS EXATAS E DA TERRA::QUIMICA
title_short Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
title_full Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
title_fullStr Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
title_full_unstemmed Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
title_sort Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos
author Cabral, Patrik Ferreira Gandara
author_facet Cabral, Patrik Ferreira Gandara
author_role author
dc.contributor.advisor1.fl_str_mv Rosset, Isac George
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/4493032120506685
dc.contributor.referee1.fl_str_mv Rosset, Isac George
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/4493032120506685
dc.contributor.referee2.fl_str_mv Oliveira, Adriana Ferla de
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/8320953119053085
dc.contributor.referee3.fl_str_mv Melo, Eduardo Borges de
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/0732955060928431
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/2418001242586375
dc.contributor.author.fl_str_mv Cabral, Patrik Ferreira Gandara
contributor_str_mv Rosset, Isac George
Rosset, Isac George
Oliveira, Adriana Ferla de
Melo, Eduardo Borges de
dc.subject.por.fl_str_mv Teoria Funcional de Densidade (DFT)
Ressonância Magnética Nuclear (RMN)
Química computacional
Canabinoides e diastereotópico
topic Teoria Funcional de Densidade (DFT)
Ressonância Magnética Nuclear (RMN)
Química computacional
Canabinoides e diastereotópico
Density Functional Theory (DFT);
Nuclear Magnetic Resonance (NMR)
Computational chemistry
Cannabinoids and diastereotopic
CIENCIAS EXATAS E DA TERRA::QUIMICA
dc.subject.eng.fl_str_mv Density Functional Theory (DFT);
Nuclear Magnetic Resonance (NMR)
Computational chemistry
Cannabinoids and diastereotopic
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA::QUIMICA
description The present work is in the field of Computational Chemistry combined with Density Functional Theory (DFT) to provide in silico approaches, which assist in experimental planning activities, processing of 1H and 13C Nuclear Magnetic Resonance (NMR) data, conformational search, and identification of compounds with unclear spatial structure. The compounds evaluated were Cannabidiol (CBD), Δ9 Tetrahydrocannabinol (THC) and Canabinol (CBN), which are specialized metabolites of Cannabis sativa and have clinical and forensic relevance. Macromodel® and Gaussian® were used, respectively, in Molecular Mechanics and Quantum Mechanics optimizations. Subsequently, the population distribution (Boltzman) of the conformers found was verified and the most representative ones were selected to simulate NMR spectra at eight levels of theory. It was found that the theoretical level DFT/PBE0/6-311G+(2d,p) was the most accurate for the compounds studied, obtaining MAD and RMSE values close to the experimental chemical shifts (δ). It was found that the use of the internal standard Dioxane significantly improved the accuracy of the theoretical δ for 13C. While the use of tetramethylsilane (TMS) or Dioxane did not show the same significance in the 1H simulations. A possible inversion of the C8 and C9 methyls of Δ9 THC attributed in the literature was investigated. Thus, it was concluded, by means of the MAD values and after an intentional inversion of the theoretical δ values, that these were diastereotopic carbons. Therefore, C8 and C9 methyls have been reported inverted in the literature. The best levels of theory were compared using the DFT method versus the Hartree-Fock method, and the DFT method was found to be the most accurate. Electronic property data was obtained, such as HOMO, LUMO, Hardness, Softness, electronegativity and electrophilicity, and reactivity issues were discussed together with the Electrostatic Potential Map. It was verified that the results were coherent regarding the chemical nature of the compounds under study. Finally, the computational processing time for each stage of this work was verified. It was observed that molecular flexibility is directly proportional to processing time. Therefore, the present work concluded that Computational Chemistry is an important tool in the optimization and prediction of molecular studies.
publishDate 2023
dc.date.issued.fl_str_mv 2023-10-04
dc.date.accessioned.fl_str_mv 2024-05-25T00:11:56Z
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dc.identifier.citation.fl_str_mv CABRAL, Patrik Ferreira Gandara. Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos. 2023.99 f. Dissertação (Merstrado em Química) - Universidade Estadual do Oeste do Paraná, Toledo, 2023.
dc.identifier.uri.fl_str_mv https://tede.unioeste.br/handle/tede/7216
identifier_str_mv CABRAL, Patrik Ferreira Gandara. Cálculos de deslocamentos químicos de RMN 1H e 13C e propriedades eletrônicas de canabinoides utilizando cálculos quânticos. 2023.99 f. Dissertação (Merstrado em Química) - Universidade Estadual do Oeste do Paraná, Toledo, 2023.
url https://tede.unioeste.br/handle/tede/7216
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language por
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dc.relation.confidence.fl_str_mv 600
600
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dc.publisher.none.fl_str_mv Universidade Estadual do Oeste do Paraná
Toledo
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Química
dc.publisher.initials.fl_str_mv UNIOESTE
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Centro de Engenharias e Ciências Exatas
publisher.none.fl_str_mv Universidade Estadual do Oeste do Paraná
Toledo
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