在药物发现中的化学信息学任务中利用分子支架的矢量模式多样性
Daniela Dolciami1, Robert M Ziolek1, Daniel W Davies1
1BenevolentAI, 4-8 Maple Street, London W1T 5HD, U.K.
Journal of chemical information and modeling
|March 4, 2024
概括
本研究介绍了利用的载体模式 (EVPs),以客观地描述药物发现中的化学多样性. 在成功识别,扩展和领先优化过程中,EVP 能够对化合物进行定量分析和优先排序.
科学领域:
- 药用化学 医学化学
- 药物发现 药物发现 药物发现
- 计算化学的计算化学
背景情况:
- 化学多样性至关重要,但在药物发现中客观量化具有挑战性.
- 目前用于评估化学多样性的方法可能是主观的和耗时的.
研究的目的:
- 通过利用载体模式 (EVPs) 提出一种定量和客观的方法来描述化学多样性.
- 在药物设计过程的各个阶段展示EVP的实用性,包括片段库设计,击中扩展和优化.
- 为分析结构-活动关系 (SAR) 数据和发现矢量相关性提供一个工具.
主要方法:
- 开发了一种简洁而快速的方法来列举和分析分子化合物系列的利用向量模式 (EVPs).
- 应用EVP来评估碎片库设计中的复合渐进性.
- 利用基于EVP的可定制多样性采样来优先考虑打击扩张中的化合物.
- 使用EVP来分析SAR数据而不预先确定分子支架.
主要成果:
- EVP提供了化学多样性的定量和客观衡量标准.
- 通过EVP方法,成功评估了碎片库设计中的复合渐进性.
- 以EVP为基础的采样优先考虑用于击中扩张的化合物,减少时间和人类偏差.
- EVP有效地分析了SAR数据,揭示了矢量相关性.
结论:
- 开发的矢量模式提供了一个有价值的,客观的工具,用于管理和分析药物发现中的化学多样性.
- EVP方法简化了化合物选择和优先级,提高了效率并减轻了偏差.
- 提供的Jupyter笔记本可方便采用和适应EVP分析,用于各种药物化学任务.
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