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DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids.
Novitskiy, Ivan M; Kutateladze, Andrei G.
Afiliação
  • Novitskiy IM; Department of Chemistry and Biochemistry, University of Denver, Denver, Colorado 80208, United States.
  • Kutateladze AG; Department of Chemistry and Biochemistry, University of Denver, Denver, Colorado 80208, United States.
J Org Chem ; 87(7): 4818-4828, 2022 04 01.
Article em En | MEDLINE | ID: mdl-35302771
Machine learning (ML) profoundly improves the accuracy of the fast DU8+ hybrid density functional theory/parametric computations of nuclear magnetic resonance spectra, allowing for high throughput in silico validation and revision of complex alkaloids and other natural products. Of nearly 170 alkaloids surveyed, 35 structures are revised with the next-generation ML-augmented DU8 method, termed DU8ML.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Alcaloides Idioma: En Revista: J Org Chem Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Alcaloides Idioma: En Revista: J Org Chem Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos