Department of Chemistry and Biochemistry, University of Denver, Denver, Colorado 80208, United States.
J Org Chem. 2022 Apr 1;87(7):4818-4828. doi: 10.1021/acs.joc.2c00169. Epub 2022 Mar 18.
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.
机器学习 (ML) 极大地提高了快速 DU8+ 杂化密度泛函理论/参数计算核磁共振谱的准确性，使得复杂生物碱和其他天然产物的高通量计算机模拟验证和修正成为可能。在近 170 种调查的生物碱中，有 35 种结构使用新一代 ML 增强的 DU8 方法进行了修正，称为 DU8ML。
