Mapping the resources and approaches facilitating computer-aided synthesis planning,Organic Chemistry Frontiers

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Mapping the resources and approaches facilitating computer-aided synthesis planning
Organic Chemistry Frontiers ( IF 4.6 ) Pub Date : 2020-08-28 , DOI: 10.1039/d0qo00946f
Zheng Wang _{1,

2,

3,

4,

5} , Wei Zhao _{1,

2,

3,

4,

5} , Gefei Hao _{1,

2,

3,

4,

5} , Baoan Song _{1,

2,

3,

4,

5}

Affiliation

Despite continuously significant breakthroughs in academia, organic synthesis remains the rate-limiting step everywhere, especially in a research environment where budget, manpower, and materials are increasingly restricted. Computer-aided synthesis planning (CASP) is a promising area of research with potential to have a tremendous impact on drug discovery, industrial chemistry, and materials science. Recently, there has been a boom in the growth of synthesis data and the application of artificial intelligence (AI) in CASP has been revitalized. However, a study of the available resources and approaches that can facilitate AI-driven organic synthesis has not been performed. This review critically examines the state of resources and approaches necessary in CASP, including big data, algorithms, and their features, advantages, limitations, and programming barriers. We conclude by outlining routes to lower the threshold for CASP research, as well as addressing research questions for the present and forecasting their role in next-generation CASP systems.

中文翻译：

绘制资源和方法以促进计算机辅助综合规划

尽管学术界不断取得重大突破，但有机合成仍然是各地限制速率的步骤，尤其是在预算，人力和物力日益受到限制的研究环境中。计算机辅助合成计划（CASP）是一个有前途的研究领域，有可能对药物发现，工业化学和材料科学产生巨大影响。最近，合成数据的增长迅速，并且在CASP中的人工智能（AI）应用得到了振兴。但是，尚未进行可促进AI驱动的有机合成的可用资源和方法的研究。这篇评论严格审查了CASP中必要的资源和方法的状态，包括大数据，算法及其功能，优势，局限性，和编程障碍。最后，我们概述了降低降低CASP研究门槛的途径，以及解决了当前的研究问题并预测了它们在下一代CASP系统中的作用。

更新日期：2020-11-03

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