Literature DB >> 35302771

DU8ML: Machine Learning-Augmented Density Functional Theory Nuclear Magnetic Resonance Computations for High-Throughput In Silico Solution Structure Validation and Revision of Complex Alkaloids.

Ivan M Novitskiy1, Andrei G Kutateladze1.   

Abstract

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.

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Year:  2022        PMID: 35302771     DOI: 10.1021/acs.joc.2c00169

Source DB:  PubMed          Journal:  J Org Chem        ISSN: 0022-3263            Impact factor:   4.354


  1 in total

1.  Collective total synthesis of C4-oxygenated securinine-type alkaloids via stereocontrolled diversifications on the piperidine core.

Authors:  Sangbin Park; Gyumin Kang; Chansu Kim; Dongwook Kim; Sunkyu Han
Journal:  Nat Commun       Date:  2022-09-02       Impact factor: 17.694

  1 in total

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