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

Authors :
Wang, Yu-Liang
Wang, Fan
Shi, Xing-Xing
Jia, Chen-Yang
Wu, Feng-Xu
Hao, Ge-Fei
Yang, Guang-Fu
Source :
Briefings in Bioinformatics. Jul2021, Vol. 22 Issue 4, p1-8. 8p.
Publication Year :
2021

Abstract

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 R 2 = 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/. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14675463
Volume :
22
Issue :
4
Database :
Academic Search Index
Journal :
Briefings in Bioinformatics
Publication Type :
Academic Journal
Accession number :
152575468
Full Text :
https://doi.org/10.1093/bib/bbaa276