Cover image of the article: 3D QSAR Studies of 1,3,4-oxadiazole derivatives as antimycobacterial agents

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3D QSAR Studies of 1,3,4-oxadiazole derivatives as antimycobacterial agents

Authors

Krishna Kant Jha1,*, Abdul Samad2, Yatendra Kumar3, Mohd Shaharyar4, RatanLal Khosa5, Jainendra Jain6, Sandeep Bansal5
1Department of Pharmaceutical Technology, MIET, Meerut. (U.P.) India
2D.J. College of Pharmacy Modinagar, Ghaziabad, (U.P.) India
3I.T.S. Paramedical College, Muradnagar, Ghaziabad, (U.P.) India
4Faculty of Pharmacy, Jamia Hamdard, New Delhi, India
5B.I.T Meerut, (U.P.) India
6Department of Pharmaceutical Technology, MIET, Meerut, (U.P.) India
*Corresponding Author: Department of Pharmaceutical Technology, MIET, Meerut. (U.P.) India. Email:samadsiddiqister@gmail.com

Iranian Journal of Pharmaceutical Research:Vol. 8, issue 3; 163-167
Published online:Nov 20, 2010
Article type:Research Article
Received:May 01, 2008
Accepted:Oct 01, 2008
How to Cite:Jha KK, Samad A, Kumar Y, Shaharyar M, Khosa R, et al. 3D QSAR Studies of 1,3,4-oxadiazole derivatives as antimycobacterial agents. Iran J Pharm Res. 2022;8(3):e128633. doi: https://doi.org/10.22037/ijpr.2010.806

Abstract

Recently several 1,3,4-oxadiazole derivatives were identified as potentially active antimycobacterial agents. Various 5-aryl-2-thio-1,3,4-oxadiazoles have been reported having good antimycobacterial activity against Mycobacterium tuberculosis H37Rv (ATCC 27294). In this paper we report 3D QSAR studies for the 41 molecules of 1,3,4-oxadiazoles by using k-Nearest Neighbor Molecular Field Analysis (kNN-MFA) combined with various selection procedures. Using kNN-MFA approach 52 3D-QSAR models were generated; one of these models was selected on the basis of q2 and pred_r2 values. The selected model had shown good internal and external predictivity for the training set of 33 molecules and test set of 8 molecules with validation (q2) and cross validation (pred_r2) values of 0.5022 and 0.2898, respectively.

This model can be used for preliminary screening of large diversified compound libraries. The model has shown that presence of sulphur is must for activity, however the larger bulky substituents reduce the activity. The presence of halogen and other non-halogen groups have also contributed to the activity.

Hence the future schemes with smaller groups on sulphur and electronegative groups in the molecule would result in potentially active molecules.

Highlights

Copyright

© 2022, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

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