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CODD-Pred:用于有效识别小分子的目标和生物活性预测的Web服务器

Xiaodan Yin^1,2, Xiaorui Wang^1,2, Yuquan Li³

¹Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Macao, 999078, China.

Journal of chemical information and modeling

|October 11, 2023

概括

CODD-Pred是一个新的网络服务器,可以预测药物点和小分子生物活性. 它使用先进的框架来提高癌症等疾病的药物发现效率和准确性.

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:

目标识别和生物活性预测对于药物发现至关重要.
现有的方法需要提高准确性和效率.

研究的目的:

介绍CODD-Pred,这是一个用于预测药物点和小分子生物活性的Web服务器.
为快速评估和优化候选药物提供一个工具.

主要方法:

开发了一种双分子图形感知 (DMGP) 框架,用于使用646,498个小分子和640个人类目标进行目标预测.
创建了一个多模型自我验证活动预测 (MSAP) 框架,用于对56个与疾病相关的目标进行小分子的生物活性量化.
使用来自GOSTAR数据库的精选数据集.

主要成果:

在目标预测方面,DMGP框架实现了超过80%的前五名准确度,超过了现有的服务器.
在MSAP框架中,小分子接体的生物活性得到了准确的量化.
CODD-Pred为全面的药物设计预测提供了一种双重方法.

结论:

CODD-Pred作为一个有价值的,免费可访问的工具,加速药物发现.
开发的框架增强了对药物标和生物活性的预测.
该资源有助于研究人员评估和优化潜在的治疗方法.

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