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Cloud 3D-QSAR: a web tool for the development of quantitative structure–activity relationship models in drug discovery

数量结构-活动关系 Web服务器 计算机科学 服务器 云计算 药物发现 云服务器 数据库 数据挖掘 机器学习 化学 互联网 万维网 操作系统 生物化学
作者
Yuliang Wang,Fan Wang,Xing-Xing Shi,Chen-Yang Jia,Feng-Xu Wu,Ge-Fei Hao,Guang-Fu Yang
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:22 (4) 被引量:27
标识
DOI:10.1093/bib/bbaa276
摘要

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure-Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/.

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