CovalentInDB 2.0:一个更新的综合数据库,用于基于结构和基于连接体的共价抑制剂的设计和选
Hongyan Du1, Xujun Zhang1, Zhenxing Wu1
1College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, Zhejiang, China.
Nucleic acids research
|October 23, 2024
概括
CovalentInDB 2.0 通过扩展的数据库,人工智能驱动的氨酸分析和广泛的虚拟查库,增强了针对性共价抑制剂的发现. 该资源有助于研究人员优化共价药物设计并加速治疗开发.
科学领域:
- 药用化学 医学化学
- 计算机化药物发现技术
- 生物信息学是一种生物信息学.
背景情况:
- 向共价抑制剂 (TCI) 提供强大的药物发现策略,因为强大的目标参与.
- 开发TCI是复杂的,需要优化共价弹头,非共价相互作用,并访问各种化合物库.
研究的目的:
- 介绍CovalentInDB 2.0,一个更新的在线数据库,以促进共价药物发现.
- 为分析共价相互作用和分析潜在药物标提供全面的资源.
主要方法:
- 数据库扩展了8303种抑制剂,368种标和3445种共晶结构.
- 基于人工智能的144,864个人类氨酸结合能力的分析.
- 整合了最大的共价虚拟选库 (2,030,192个化合物) 和天然产品库 (105,901个分子).
主要成果:
- 在共晶结构中对非共价相互作用的详细分析.
- 在人类蛋白质组中识别可使用药物的囊蛋白.
- 通过结构相似性和药物相似性预测,提高了选图书馆的效用.
结论:
- 协同InDB 2.0 作为一个有价值的,自由可访问的资源,用于推进协同药物发现.
- 该数据库支持有效的选,合理的设计和对共价抑制剂的持续数据贡献.
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