药物在线:使用深度学习的在线平台,用于药物向相互作用,亲和力和结合部位的识别
Xin Zeng1, Guang-Peng Su1, Shu-Juan Li2
1College of Mathematics and Computer Science, Dali University, Dali, 671003, China.
BMC bioinformatics
|April 19, 2024
概括
一个新的综合在线平台,Drug-Online,可以识别药物向相互作用,亲和力和结合点. 该工具通过逐步分析这些关键方面,有助于药物查和设计.
科学领域:
- 计算化学是一种计算化学.
- 生物信息学是一种生物信息学.
- 药物发现 药物发现
背景情况:
- 准确识别药物向相互作用 (DTI),亲和力 (DTA) 和结合位点 (DTS) 对于药物开发和理解向功能至关重要.
- 现有的深度学习平台往往只关注DTI,DTA或DTS的一个方面,缺乏综合方法.
研究的目的:
- 开发一个新的,集成的在线平台,Drug-Online,用于逐步识别药物向相互作用,亲和力和结合部位.
- 为药物查,目标识别和功能分析提供全面的工具.
主要方法:
- 药物在线平台采用三部分方法,从MGraphDTA (GNN和CNN) 开始用于DTI识别.
- 如果检测到相互作用,使用MMDTA (GNN和CNN) 计算药物向亲和力 (DTA).
- 使用pt-lm-gnn方法 (GNN) 识别药物标结合部位 (DTS).
主要成果:
- 该平台以顺序的方式成功集成DTI,DTA和DTS识别.
- 药物在线提供了一个渐进式的分析管道:相互作用,然后是亲和力,最后是结合部位的识别.
结论:
- 药物在线 (Drug-Online) 是一个可靠和自由访问的在线平台,用于整合药物向相互作用,亲和力和结合位点识别.
- 该平台通过其全面的方法促进药物查,目标识别和功能研究.
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