机器学习驱动的多替代基因酸的自动合成
Jiaolong Meng1, Hongbin Yang2, Chengliang Li1
1Hainan Institute of East China Normal University, Shanghai Key Laboratory of Green Chemistry and Chemical Processes, State Key Laboratory of Petroleum Molecular & Process Engineering, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Road, Shanghai, 200062, P.R. China.
计算机辅助合成规划开发了一种制造多替代甘酸盐 (PGAs) 的新方法. 这种自动流系统简化了合成,为制药应用提供了工业潜力.
科学领域:
- 有机化学 有机化学
- 计算化学的计算化学
- 化学工程是化学工程的重要组成部分.
背景情况:
- 丁是制药的关键组成部分.
- 目前的合成方法是低效的,昂贵的,耗时的.
- 需要一种新的回合成方法来提高效率并减少合成冗余.
研究的目的:
- 开发一种破坏性复合方法,用于多替代甘酸盐 (PGAs).
- 建立一个自动化合成过程,以高效地构建PGA图书馆.
- 通过计算研究来阐明反应机制.
主要方法:
- 计算机辅助合成规划 (CASP) 算法用于路线扣除.
- 自动化流量系统用于简化合成.
- 密度函数理论 (DFT) 用于机械学研究.
主要成果:
- 对合成路径向PGAs进行系统的扣除.
- 开发一种自动化流量系统,用于选择性6端循环.
- 确定二基中间体和一个1,5原子转移机制.
- 快速建立PGAs的图书馆.
结论:
- 这项研究提出了一个创新的模型,用于集成分子库的构建.
- 开发的方法提高了环形形成能力,减少了合成冗余.
- 这些发现突显了可扩展的PGA合成和应用的工业潜力.
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