超大虚拟查:药物设计的定义,最近的进展和挑战
Gabriel Corrêa Veríssimo1,2, Rafaela Salgado Ferreira3, Vinícius Gonçalves Maltarollo1
1Departamento de Produtos Farmacêuticos, Faculdade de Farmácia, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, 31270-901, Brazil.
Molecular informatics
|December 5, 2024
概括
超大虚拟选 (ULVS) 利用人工智能和先进计算来分析庞大的复合库. 这种计算方法通过从数十亿个分子中识别潜在的候选药物来加速药物发现.
科学领域:
- 计算化学是一种计算化学.
- 药物发现 药物发现
- 生物信息学是一种生物信息学.
背景情况:
- 虚拟选 (VS) 对于药物设计中的分子排名至关重要.
- 人工智能和计算能力的进步使得超过10^9分子的库可以选.
研究的目的:
- 审查数十亿级图书馆的超大虚拟选 (ULVS) 方法.
- 在规模上展示各种VS方法的软件,应用程序和结果.
主要方法:
- 粗暴的力量对接对接.
- 基于反应的对接.
- 机器学习 (ML) 用于VS
- 类似性/药物类型搜索
主要成果:
- 证明了数十亿级化合物选的可行性.
- 展示了识别杀伤候选人的潜力.
- 突出了新生物活性化合物的结构多样性的增加.
结论:
- ULVS代表了药物发现的范式转变.
- 能够有效地识别潜在的治疗剂.
- 扩大了在早期药物设计中探索的化学空间的范围.
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