Synthesis of 1,2,4-oxadiazole derivatives: anticancer and 3D QSAR studies

2020 ◽  
Vol 151 (3) ◽  
pp. 385-395 ◽  
Author(s):  
Ankur Vaidya ◽  
Shweta Jain ◽  
Br Prashantha Kumar ◽  
Shashank K. Singh ◽  
Sushil Kumar Kashaw ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Neda Shakour ◽  
Farzin Hadizadeh ◽  
Prashant Kesharwani ◽  
Amirhossein Sahebkar

Sortase A (SrtA) is an enzyme that catalyzes the attachment of proteins to the cell wall of Gram-positive bacterial membrane, preventing the spread of pathogenic bacterial strains. Here, one class of oxadiazole compounds was distinguished as an efficient inhibitor of SrtA via the “S. aureus Sortase A” substrate-based virtual screening. The current study on 3D-QSAR was done by utilizing preparation of the structure in the Schrödinger software suite and an assessment of 120 derivatives with the crystal structure of 1,2,4-oxadiazole which was extracted from the PDB data bank. The docking operation of the best compound in terms of pMIC ( pMIC = 2.77 ) was done to determine the drug likeliness and binding form of 1,2,4-oxadiazole derivatives as antibiotics in the active site. Using the kNN-MFA way, seven models of 3D-QSAR were created and amongst them, and one model was selected as the best. The chosen model based on q 2 (pred_ r 2 ) and R 2 values related to the sixth factor of PLS illustrates better and more acceptable external and internal predictions. Values of crossvalidation (pred_ r 2 ), validation ( q 2 ), and F were observed 0.5479, 0.6319, and 179.0, respectively, for a test group including 24 molecules and the training group including 96 molecules. The external reliability outcomes showed that the acceptable and the selective 3D-QSAR model had a high predictive potential ( R 2 = 0.9235 ) which was confirmed by the Y -randomization test. Besides, the model applicability domain was described successfully to validate the estimation of the model.


2012 ◽  
Vol 29 (5) ◽  
pp. 438-443
Author(s):  
Hai-bin LUO ◽  
Guo-wen CHEN ◽  
Yong-xian SHAO ◽  
Zhe LI ◽  
Ming LIU ◽  
...  

2017 ◽  
Vol 14 (7) ◽  
Author(s):  
Chunqi Hu ◽  
Liang Hong ◽  
Jun Li ◽  
Wenting Du
Keyword(s):  
3D Qsar ◽  

2018 ◽  
Vol 15 (7) ◽  
pp. 721-732
Author(s):  
Liqiang Meng ◽  
Liqian Sun ◽  
Chaoqun Yan ◽  
Dongxiao Cui ◽  
Jingrun Chen ◽  
...  

2019 ◽  
Vol 16 (8) ◽  
pp. 868-881
Author(s):  
Yueping Wang ◽  
Jie Chang ◽  
Jiangyuan Wang ◽  
Peng Zhong ◽  
Yufang Zhang ◽  
...  

Background: S-dihydro-alkyloxy-benzyl-oxopyrimidines (S-DABOs) as non-nucleoside reverse transcriptase inhibitors have received considerable attention during the last decade due to their high potency against HIV-1. Methods: In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) of a series of 38 S-DABO analogues developed in our lab was studied using Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The Docking/MMFF94s computational protocol based on the co-crystallized complex (PDB ID: 1RT2) was used to determine the most probable binding mode and to obtain reliable conformations for molecular alignment. Statistically significant CoMFA (q2=0.766 and r2=0.949) and CoMSIA (q2=0.827 and r2=0.974) models were generated using the training set of 30 compounds on the basis of hybrid docking-based and ligand-based alignment. Results: The predictive ability of CoMFA and CoMSIA models was further validated using a test set of eight compounds with predictive r2 pred values of 0.843 and 0.723, respectively. Conclusion: The information obtained from the 3D contour maps can be used in designing new SDABO derivatives with improved HIV-1 inhibitory activity.


2014 ◽  
Vol 10 (7) ◽  
pp. 711-723 ◽  
Author(s):  
P. Chaitanya ◽  
G. Reddy ◽  
G. Varun ◽  
L.M. Srikanth ◽  
V.V.S.R. Prasad ◽  
...  

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