The Evolution of Data-Driven Modeling in Organic Chemistry.

The Evolution of Data-Driven Modeling in Organic Chemistry.
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有机化学中数据驱动建模的演变

DOI:
10.1021/acscentsci.1c00535
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发表时间:
2021-10-27
影响因子:
18.2
通讯作者:
Anslyn EV
Anslyn EV
中科院分区:
化学1区
文献类型:
--
作者:
Williams WL;Zeng L;Gensch T;Sigman MS;Doyle AG;Anslyn EV

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有机化学充满了复杂的关系:例如,反应物的结构如何与所形成的产物相关;反应条件如何与产率相关;催化剂的结构如何与对映选择性相关。像这样的问题是理解反应性和开发新的和改进的反应的基础。探索这些问题的一种方法是数据驱动建模,这种方法既存在又现代。在这里,我们简要介绍了有机化学中数据驱动建模的历史以及用于描述这些努力的术语。我们包括导致其当前状态的步骤的时间轴。案例研究包括强调如何,作为一个社区,我们有先进的物理有机化学工具与计算机和数据的帮助下,以增强专家化学家的直觉,并促进结构活性和结构性质关系的预测。数据科学已经成为研究有机化学的有力工具。在这里,我们提供了有机化学中数据驱动建模的历史,并讨论了该领域的现状。
Organic chemistry is replete with complex relationships: for example, how a reactant’s structure relates to the resulting product formed; how reaction conditions relate to yield; how a catalyst’s structure relates to enantioselectivity. Questions like these are at the foundation of understanding reactivity and developing novel and improved reactions. An approach to probing these questions that is both longstanding and contemporary is data-driven modeling. Here, we provide a synopsis of the history of data-driven modeling in organic chemistry and the terms used to describe these endeavors. We include a timeline of the steps that led to its current state. The case studies included highlight how, as a community, we have advanced physical organic chemistry tools with the aid of computers and data to augment the intuition of expert chemists and to facilitate the prediction of structure–activity and structure–property relationships. Data science has emerged as a powerful tool to study organic chemistry. Herein, we provide a history of data-driven modeling in organic chemistry and a discussion of the current state of the field.
DOI: 10.1126/science.166.3902.178
发表时间: 1969-01-01
期刊: SCIENCE
影响因子: 56.9
作者:
COREY, EJ;WIPKE, WT
通讯作者: WIPKE, WT
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发表时间: 1936-01-01
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DOI: 10.1016/s0169-7439(03)00094-7
发表时间: 2003-11-28
影响因子: 3.9
作者:
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通讯作者: Mura, GM