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Updated: Sep 19, 2025

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提高综合共识策略的可靠性,以促进基于对接的选活动,使用公开可用的对接程序

Valeria Scardino^1,2,3, M Justina Galarce^1,4, M Emilia Mignone^1,4

¹Computational Drug Design and Biomedical Informatics Laboratory, Instituto de Investigaciones en Medicina Traslacional (IIMT), Universidad Austral-CONICET, Pilar, Buenos Aires, Argentina.

Molecular informatics

|June 19, 2025

概括

共识对接通过结合多个程序来增强药物发现. 这种综合方法提高了虚拟选性能,使其可靠用于使用自由软件的高吞吐量活动.

科学领域:

计算化学和化学信息学
药物的发现和开发.
生物信息学和计算生物学

背景情况:

分子对接对于药物发现至关重要,但其性能因蛋白质点和软件而异.
共识对接,集成多个对接程序,提高高通量选 (HTS) 的可靠性.
现有的共识方法往往侧重于构成或排名,需要采用综合方法.

研究的目的:

开发和评估分子对接的综合姿势和排名共识方法.
使用公开可用的软件提高高通量对接 (HTD) 的性能.
评估组合方法在识别潜在候选药物的有效性.

主要方法:

使用了五个公开可用的对接程序:rDock,DOCK 6,Auto Dock 4,PLANTS 和 Vina.
开发了一种综合方法,结合了姿势共识和指数共识排名 (ECR).
通过使用50个不同的蛋白质标和与属性匹配的连接体/诱库进行了对方法的基准测试.

主要成果:

增强的姿势/排名共识方法显著超过了个人对接程序和标准ECR.
在HTD活动中评估了六个目标的约110万个分子,平均ECR改进率达到约40%.
与单个程序对接相比,在识别活性化合物方面表现出卓越的性能.

结论:

综合的位置/排名共识方法为HTD提供了强大而可靠的增强.
这种方法可以在未来的HTD活动中使用自由可用的对接程序来自信地应用.
这项研究证实共识对接是一种强大的策略,可以提高药物发现中的虚拟查效率.

关键词:

达成共识的对接指数级共识排名指数级共识排名高通量对接的对接方式基于结构的虚拟选.

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