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Cloud 3D-QSAR: a web tool for the development of quantitative structure-activity relationship models in drug discovery.
Wang, Yu-Liang; Wang, Fan; Shi, Xing-Xing; Jia, Chen-Yang; Wu, Feng-Xu; Hao, Ge-Fei; Yang, Guang-Fu.
Afiliação
  • Wang YL; College of Chemistry, Central China Normal University (CCNU).
  • Wang F; College of Chemistry, CCNU.
  • Shi XX; College of Chemistry, CCNU.
  • Jia CY; College of Chemistry, Central China Normal University (CCNU).
  • Wu FX; College of Chemistry, CCNU.
  • Hao GF; Pesticide Design and Bioinformatics in College of Chemistry, CCNU.
  • Yang GF; College of Chemistry of CCNU.
Brief Bioinform ; 22(4)2021 07 20.
Article em En | MEDLINE | ID: mdl-33140820
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.cn9999/ccb/server/cloud3dQSAR/.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Desenho de Fármacos / Internet / Descoberta de Drogas Tipo de estudo: Prognostic_studies Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Desenho de Fármacos / Internet / Descoberta de Drogas Tipo de estudo: Prognostic_studies Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2021 Tipo de documento: Article