以多变量线性回归分析为指导的非选择性Negishi合优化:KRAS G12C共价抑制剂GDC-6036的不对称合成
Jie Xu1, Samantha Grosslight2, Kyle A Mack1
1Department of Small Molecule Process Chemistry, Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States.
通过选择性Negishi合开发了KRAS G12C抑制剂GDC-6036的高效合成. 这种方法提供了一个可扩展的途径,
科学领域:
- 有机化学
- 医学化学
- 催化剂
背景情况:
- KRAS G12C突变是各种癌症的关键驱动因素.
- 开发强效和选择性的KRAS G12C抑制剂是一个关键的治疗目标.
- 有效的合成途径对于大规模生产向癌症药物至关重要.
研究的目的:
- 报告KRAS G12C共价抑制剂GDC-6036的有效不对称合成.
- 建立一个可扩展和选择性的方法来构建GDC-6036的核心结构.
- 优化关键催化步骤的配体选择.
主要方法:
- 由Palladium/Walphos系统催化的一种选择性Negishi合.
- 统计建模和计算描述器来选择最佳的性双素配体 (W057-2).
- 一个望远镜反应序列,包括氧化,脱保护和烯胺形成.
主要成果:
- 在Negishi合步骤中,通过配体W057-2实现了高选性.
- GDC-6036从皮里丁和金纳的原料中成功合成了40%的总产量.
- 通过望远镜测试的序列简化了这个过程,提高了效率.
结论:
- 开发的合成途径对GDC-6036生产具有高效性和可扩展性.
- 在联体选择中使用统计建模是催化优化的先进方法.
- 这项工作为KRAS G12C抑制剂提供了有价值的合成策略.
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