在成功的优化中会发生什么? 2018-2024年文学的一项调查
1Paul Leeson Consulting Ltd, Nuneaton CV13 6LZ, U.K.
Journal of medicinal chemistry
|March 4, 2026
概括
药物候选人优化涉及增加分子复杂性和重量,从而提高疗效. 大多数口头候选人会遇到Lipinski.
科学领域:
- 药用化学 医学化学
- 药物发现 药物发现 药物发现
- 计算化学计算化学
背景情况:
- 分析了478个从2018-2024年文献中开始的复合到候选优化对.
- 专注于分子性质,目标类,起源,机制,疾病区域和施用途径.
- 研究药物优化的趋势和策略.
研究的目的:
- 在药物候选者优化过程中分析分子性质变化.
- 确定影响优化结果的关键因素.
- 为了评估"领先的相似性"和优化趋势.
主要方法:
- 分子性质的定量分析 (例如分子量,脂性,复杂性).
- 根据目标,疾病区域和施用途径进行分类.
- 检查结构保留和常见碎片的发生.
主要成果:
- 优化导致"候选规范"的趋同,目标类差异持续存在.
- 平均分子量增加了81 Da,与强度的增加相关;脂友性保持不变.
- 复杂性增加,sp3碳,H键受体和天然产品碎片是突出的因素;碳芳香环减少.
结论:
- 药物优化涉及增加分子复杂性和重量,提高功效.
- 结构保持率平均为70%,使用常见环系统的使用增加.
- 起始化合物中的"相似性"是影响优化策略的理想属性.
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