An Artificial Intelligence Approach for Tackling Conformational Energy Uncertainties in Chiroptical Spectroscopies,Angewandte Chemie International Edition

当前位置： X-MOL 学术 › Angew. Chem. Int. Ed. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

An Artificial Intelligence Approach for Tackling Conformational Energy Uncertainties in Chiroptical Spectroscopies
Angewandte Chemie International Edition ( IF 16.1 ) Pub Date : 2023-08-01 , DOI: 10.1002/anie.202310358
Gabriel Marton ₁ , Mark A. J. Koenis ₂ , Hong‐Bing Liu ₃ , Carole A. Bewley ₃ , Wybren Jan Buma _{2,

4} , Valentin Paul Nicu ₁

Affiliation

The assignment of the absolute configuration of chiral compounds critically depends on the comparison with predictions of chiroptical spectra with intrinsically inaccurate quantum chemical calculations. Wybren Jan Buma, Valentin Paul Nicu et al. report in their Research Article (e202307053) a novel protocol based on genetic algorithm analyses and hierarchical clustering that overcomes these inaccuracies as demonstrated by the elucidation of the absolute configuration and conformational landscape of natural products derived from the Haliclona sp. marine sponge.

中文翻译：

解决手性光学光谱中构象能量不确定性的人工智能方法

手性化合物绝对构型的分配关键取决于与手性光谱预测与本质上不准确的量子化学计算的比较。Wybren Jan Buma、Valentin Paul Nicu 等人。在他们的研究文章（e202307053）中报告了一种基于遗传算法分析和层次聚类的新颖协议，该协议克服了这些不准确性，这一点通过阐明源自 Haliclona sp 的天然产物的绝对构型和构象景观即可证明。海洋海绵。

更新日期：2023-08-02

点击分享查看原文

点击收藏

公开下载

阅读更多本刊新发论文本刊介绍/投稿指南