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  3. 复原生物合成的人工智能方法和模型:一个范围审查
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  3. 复原生物合成的人工智能方法和模型:一个范围审查

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复原生物合成的人工智能方法和模型:一个范围审查

Guillaume Gricourt1, Philippe Meyer1, Thomas Duigou1

  • 1Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, 78350 Jouy-en-Josas, France.

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在PubMed 上查看摘要

概括
此摘要是机器生成的。

人工智能 (AI) 推进了化学合成规划的逆合成和逆生物合成. 这些人工智能方法加速发现更绿色的化学生产途径.

关键词:
人工智能的人工智能是人工智能.反复生物合成的生物合成.复杂合成的复杂合成

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科学领域:

  • 化学 化学 化学
  • 生物技术是生物技术.
  • 计算机科学 计算机科学

背景情况:

  • 逆合成将分子战略性地分解成有效合成的构建块.
  • 反复生物合成在生物催化和合成生物学中应用了类似的原理.
  • 人工智能 (AI) 为化学合成和勘探提供了新的前沿.

研究的目的:

  • 审查人工智能的最新进展,以设计复合成和复生物合成路径.
  • 突出AI在促进绿色化学和生物生产中的作用.
  • 讨论当前的局限性和未来的研究方向.

主要方法:

  • 使用基于反应模板或生成模型的AI方法.
  • 评分功能和规划策略被用来导航复杂的合成路径.
  • 该评论总结了这些人工智能技术在路径设计中的应用.

主要成果:

  • 人工智能显著提高了化学合成的规划和化学空间的探索.
  • 人工智能驱动的方法促进了与绿色化学原则一致的生物生产.
  • 最近的进步在设计复杂的逆合成和逆生物合成途径方面显示出希望.

结论:

  • 人工智能正在彻底改变化学合成计划,特别是在逆合成和逆生物合成方面.
  • 人工智能的整合促进了对环境友好的化学实践和生物生产.
  • 需要进一步的研究来解决局限性,并释放AI在这个领域的全部潜力.