QSAR and Molecular Docking Studies of Oxadiazole-Ligated Pyrrole Derivatives as Enoyl-ACP (CoA) Reductase Inhibitors

Abstract

A quantitative structure-activity relationship model was developed on a series of compounds containing oxadiazole-ligated pyrrole pharmacophore to identify key structural fragments required for anti-tubercular activity. Two-dimensional (2D) and three-dimensional (3D) QSAR studies were performed using multiple linear regression (MLR) analysis and k-nearest neighbour molecular field analysis (kNN-MFA), respectively. The developed QSAR models were found to be statistically significant with respect to training, cross-validation, and external validation. New chemical entities (NCEs) were designed based on the results of the 2D- and 3D-QSAR. NCEs were subjected to Lipinski’s screen to ensure the drug-like pharmacokinetic profile of the designed compounds in order to improve their bioavailability. Also, the binding ability of the NCEs with enoyl-ACP (CoA) reductase was assessed by docking.

3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity

“…Many models were generated, but the best model satisfied all of the following parameters:The number of compounds should be 3–6 times the number of molecular descriptors used in the proposed model [7]. R 2 , square of regression (>0.7) [8]. q 2 , cross-validated r 2 (>0.5) [8].SEE, standard error of estimate (smaller is better) [8]. F -test, F -test for statistical significance of the model (higher is better, for the same set of descriptors and chemicals) [8].…”

Predictive Modeling of the Human Hepatoma (Huh-7D12) Cancer Line of a Series of bis- (5-arylidene-rhodanine-3-yl) Diamine

“…RML and RMNL were generated using the XLSTAT software version 2016 [29] to predict the anticancer activity IC 50 . The equations of the different models were evaluated by the coefficient of determination (R 2 ) which measures the adequacy of the model and the predictive power of the QSAR model; the Root Mean Square Error (RMSE) which must be less than 10% of the range of the target property value [30]; the Fischer test (F) Test F, for the statistical significance of the model (higher is high, the better is the same set of descriptors and chemicals) [31] and the cross correlation coefficient (Q 2 CV ) which allows for evaluate the predictive power associated with a QSAR model ( > 0,6 for a satisfactory model while for an excellent model > 0,9 ) [32]. These different statistical parameters are given by the following expressions:…”

Enoyl Acyl Carrier Protein Reductase Inhibitors: An Emerging Target

“…The correctness of the rationale behind these dry lab studies can be further validated by carrying out the synthesis and antitubercular activity of the designed NCEs. (20) …”