QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CLpro inhibitors

Abstract

The 3C-like protease (3CLpro), known as the main protease of SARS-COV, plays a vital role in the viral replication cycle and is a critical target for the development of SARS inhibitor. Comparative sequence analysis has shown that the 3CLpro of two coronaviruses, SARS-CoV-2 and SARS-CoV, show high structural similarity, and several common features are shared among the substrates of 3CLpro in different coronaviruses. The goal of this study is the development of validated QSAR models by CORAL software and Monte Carlo optimization to predict the inhibitory activity of 81 isatin and indole-based compounds against SARS CoV 3CLpro. The models were built using a newer objective function optimization of this software, known as the index of ideality correlation (IIC), which provides favorable results. The entire set of molecules was randomly divided into four sets including: active training, passive training, calibration and validation sets. The optimal descriptors were selected from the hybrid model by combining SMILES and hydrogen suppressed graph (HSG) based on the objective function. According to the model interpretation results, eight synthesized compounds were extracted and introduced from the ChEMBL database as good SARS CoV 3CLpro inhibitor. Also, the activity of the introduced molecules further was supported by docking studies using 3CLpro of both SARS-COV-1 and SARS-COV-2. Based on the results of ADMET and OPE study, compounds CHEMBL4458417 and CHEMBL4565907 both containing an indole scaffold with the positive values of drug-likeness and the highest drug-score can be introduced as selected leads.

Models for the No-Observed-Effect Concentration (NOEC) and Maximal Half-Effective Concentration (EC50)

“…The ranges for training sets are 1.07–2.03 (NOEC) and 1.55–1.67 (EC50), while for calibration sets, the ranges are 0.449–0.968 (NOEC) and 0.726–0.631 (EC50). This is due to the influence of the factors IIC and CII on the Monte Carlo optimization method [ 20 , 27 , 30 , 31 ].…”

“…These models are based on the correlation weights of molecular features used to calculate the 2D descriptor in the CORAL software (http://www.insilico.eu/coral/ accessed on 11 June 2024). The Monte Carlo method has been used for many other models [20][21][22][23][24][25][26][27].…”

3D-QSAR, molecular docking and molecular dynamics analysis of pyrazole derivatives as MALT1 inhibitors

“…12 For data visualization, the IC50 of all MALT1 inhibitors has been transformed to PIC50 (pIC50 = −logIC50). 13 In addition, 38 of the 46 compounds were randomly divided into a training set. The remaining molecules were used as a test set (labeled with an “*” sign) to differentiate them.…”

Recent advances in chemometric modelling of inhibitors against SARS-CoV-2

“…Soleymani et al collected 81 isatin and indole-based compounds with good inhibitory activity against SARS-CoV 3CLpro, and the reliable Monte Carlo QSAR models were subsequently built [ 64 ]. The parameters of the best model were R 2 = 0.96 and R test 2 = 0.92.…”

“…There are many structural fragments in the literature that have been shown to positively contribute to the inhibitory activity of compounds [ 64 , 66 , 75 ]. Researchers can design new compounds on the basis of these substructures, and subsequently utilizing these compounds directly for docking and MD.…”