Suppr超能文献

云 3D-QSAR:用于药物发现中定量构效关系模型开发的网络工具。

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

机构信息

College of Chemistry, Central China Normal University (CCNU).

College of Chemistry, CCNU.

出版信息

Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa276.

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 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/.

摘要

有效药物发现有助于治疗许多疾病,但受到高成本和长周期的限制。定量构效关系 (QSAR) 方法被引入来虚拟评估大量化合物的活性,从而减少化学合成和实验测定所需的时间和劳动成本。因此,这种方法提高了药物发现的效率。为了满足研究人员利用这项技术的需求,近年来开发了许多与 QSAR 相关的网络服务器,如 Web-4D-QSAR 和 DPubChem。然而,上述服务器都不能完成完整的 QSAR 建模和提供活性预测功能。我们通过集成分子结构生成、对齐、分子相互作用场 (MIF) 计算和结果分析功能来引入 Cloud 3D-QSAR,提供一站式解决方案。我们严格验证了这个服务器,在 834 个测试分子中,活性预测的相关系数为 R2=0.934。敏感性、特异性和准确性分别为 86.9%、94.5%和 91.5%,AUC=0.981,AUCPR=0.971。Cloud 3D-QSAR 服务器可以促进药物发现中良好 QSAR 模型的发展。我们的服务器是免费的,现在可以在 http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/ 上使用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验