共价对接软件格局:药物设计中的特征和应用
Natesh Singh1, Philippe Vayer2, Bruno O Villoutreix2
1Evotec SE, Molecular Architects, Integrated Drug Discovery, Campus Curie, 195 Rte d'Espagne, 31100 Toulouse, France.
Briefings in bioinformatics
|December 31, 2025
概括
共价小分子干提供增强的药物效力,但构成设计挑战. 包括人工智能在内的新计算工具正在改进这些强大的候选药物的理性设计和虚拟查.
科学领域:
- 药用化学 医学化学
- 计算机化药物发现技术
- 化学生物学 化学生物学
背景情况:
- 性小分子配体在药物发现中越来越重要,用于长时间的向参与和调节以前无法调节的蛋白质.
- 对共价联体的理性设计和虚拟选 (VS) 在计算上具有挑战性,原因是模拟共价键形成能量学的困难.
- 传统的对接工具通常需要先进的量子力学 (QM) 计算来进行准确的预测,这凸显了对改进的计算方法的需求.
研究的目的:
- 审查共价抑制的基本原理和机制.
- 提供对共价联体设计和VS的计算工具的全面概述.
- 讨论人工智能和机器学习 (ML) 在推进共价药物发现方面的作用.
主要方法:
- 对计算工具的审查,包括共价对接,弹头放置算法和药模拟.
- 对AI/ML工具进行讨论,以优先考虑共价联结体候选物.
- 包括案例研究,精选的数据库和评估核性残留物反应性的工具.
主要成果:
- 对于共价联体发现的计算环境正在迅速发展,新的开源,商业和基于网络的平台正在迅速发展.
- 人工智能和机器学习工具越来越多地协助优先考虑候选分子.
- 现有的计算工具可以实现理性设计,假设改进和扩展可用性.
结论:
- 尽管面临挑战,但计算工具的进步显著影响了对共价联体的早期药物发现和化学生物学.
- 目前的共价对接和人工智能驱动的方法促进了药物发现的理性设计和创新.
- 需要进一步的进展,但现有的工具已经扩大了可用药物目标的边界.
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