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化学计算与化学信息学的标准化

Chemputation and the Standardization of Chemical Informatics.

作者信息

Hammer Alexander J S, Leonov Artem I, Bell Nicola L, Cronin Leroy

机构信息

School of Chemistry, University of Glasgow, University Avenue, Glasgow, G12 8QQ, United Kingdom.

出版信息

JACS Au. 2021 Aug 31;1(10):1572-1587. doi: 10.1021/jacsau.1c00303. eCollection 2021 Oct 25.

Abstract

The explosion in the use of machine learning for automated chemical reaction optimization is gathering pace. However, the lack of a standard architecture that connects the concept of chemical transformations universally to software and hardware provides a barrier to using the results of these optimizations and could cause the loss of relevant data and prevent reactions from being reproducible or unexpected findings verifiable or explainable. In this Perspective, we describe how the development of the field of digital chemistry or chemputation, that is the universal code-enabled control of chemical reactions using a standard language and ontology, will remove these barriers allowing users to focus on the chemistry and plug in algorithms according to the problem space to be explored or unit function to be optimized. We describe a standard hardware (the chemical processing programming architecture-the ChemPU) to encompass all chemical synthesis, an approach which unifies all chemistry automation strategies, from solid-phase peptide synthesis, to HTE flow chemistry platforms, while at the same time establishing a publication standard so that researchers can exchange chemical code (χDL) to ensure reproducibility and interoperability. Not only can a vast range of different chemistries be plugged into the hardware, but the ever-expanding developments in software and algorithms can also be accommodated. These technologies, when combined will allow chemistry, or chemputation, to follow computation-that is the running of code across many different types of capable hardware to get the same result every time with a low error rate.

摘要

机器学习在自动化化学反应优化中的应用正迅速发展。然而,缺乏一种将化学转化概念与软件和硬件普遍连接的标准架构,这为利用这些优化结果设置了障碍,可能导致相关数据丢失,并使反应无法重现,或使意外发现难以验证或解释。在这篇观点文章中,我们描述了数字化学或化学计算领域的发展,即使用标准语言和本体对化学反应进行通用的代码驱动控制,将如何消除这些障碍,让用户能够专注于化学本身,并根据要探索的问题空间或要优化的单元功能插入算法。我们描述了一种标准硬件(化学处理编程架构——ChemPU),它涵盖所有化学合成,这种方法统一了从固相肽合成到高通量实验(HTE)流动化学平台等所有化学自动化策略,同时建立了一种发表标准,以便研究人员能够交换化学代码(χDL)以确保可重复性和互操作性。不仅大量不同的化学过程可以接入该硬件,软件和算法方面不断扩展的发展也能得到适配。这些技术结合起来将使化学或化学计算能够像计算一样,即在许多不同类型的可用硬件上运行代码,每次都能以低错误率得到相同的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f9a/8549037/29acb5607022/au1c00303_0001.jpg

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