Abstract
Capuramycin and a few semisynthetic derivatives have shown potential as anti-tuberculosis antibiotics.To understand their mechanism of action and structureactivity relationships a 3D-QSAR and molecular docking studies were performed. A set of 52 capuramycin derivatives for the training set and 13 for the validation set was used. A highly predictive MFA model was obtained with crossvalidated q2 of 0.398, and non-cross validated partial least-squares (PLS) analysis showed a conventional r2 of 0.976 and r2pred of 0.839. The model has an excellent predictive ability. Combining the 3D-QSAR and molecular docking studies, a number of new capuramycin analogs with predicted improved activities were designed. Biological activity tests of one analog showed useful antibiotic activity against Mycobacterium smegmatis MC2 155 and Mycobacterium tuberculosis H37Rv. Computer-aided molecular docking and 3D-QSAR can improve the design of new capuramycin antimycobacterial antibiotics.
Document Type
Article
Publication Date
12-29-2017
Digital Object Identifier (DOI)
https://doi.org/10.1515/chem-2017-0039
Funding Information
This work was supported by the National Natural Science Foundation of China (Grants No. 81321004 and 81761128016); CAMS Innovation Fund for Medical Sciences (2016-12M-3-012 and 2016-12M-3-022); Beijing Natural Science Foundation (7164279); and Central Public-interest Scientific Institution Basal Research Fund (IMBF201509).
Repository Citation
Jin, Yuanyuan; Fan, Shuai; Lv, Guangxin; Meng, Haoyi; Sun, Zhengyang; Jiang, Wei; Van Lanen, Steven G.; and Yang, Zhaoyong, "Computer-Aided Drug Design of Capuramycin Analogues as Anti-Tuberculosis Antibiotics by 3D-QSAR and Molecular Docking" (2017). Pharmaceutical Sciences Faculty Publications. 96.
https://uknowledge.uky.edu/ps_facpub/96
Notes/Citation Information
Published in Open Chemistry, v. 15, issue 1, p. 299–307.
© 2017 Yuanyuan Jin et al.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0