In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition

Abstract

The COVID-19 pandemic emerged in 2019, bringing with it the need for greater stores of effective antiviral drugs. This paper deals with the conformation-independent, QSAR model, developed by employing the Monte Carlo optimization method, as well as molecular graphs and the SMILES notation-based descriptors for the purpose of modeling the SARS-CoV-3CLpro enzyme inhibition. The main purpose was developing a reproducible model involving easy interpretation, utilized for a quick prediction of the inhibitory activity of SAR-CoV-3CLpro. The following statistical parameters were present in the best-developed QSAR model: (training set) R 2 = 0.9314, Q 2 = 0.9271; (test set) R 2 = 0.9243, Q 2 = 0.8986. Molecular fragments, defined as SMILES notation descriptors, that have a positive and negative impact on 3CLpro inhibition were identified on the basis of the results obtained for structural indicators, and were applied to the computer-aided design of five new compounds with (4-methoxyphenyl)[2-(methylsulfanyl)-6,7-dihydro-1H-[1,4]dioxino[2,3-f]benzimidazol-1-yl]methanone as a template molecule. Molecular docking studies were used to examine the potential inhibition effect of designed molecules on SARS-CoV-3CLpro enzyme inhibition and obtained results have high correlation with the QSAR modeling results. In addition, the interactions between the designed molecules and amino acids from the 3CLpro active site were determined, and the energies they yield were calculated. Supplementary Information The online version contains supplementary material available at 10.1007/s11696-022-02170-8.

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

“…Ničkčović et al also extracted 84 heterocyclic molecules in the Binding database with the definitive inhibitory activity (IC 50 ) against 3CLpro of SARS-CoV to construct the Monte Carlo-based QSAR model [ 66 ]. It should be noted that the SMILES notation and molecular graph-based descriptors were used for model development.…”

“…Similarly, molecular docking was also used by Ničkčović et al to validate the inhibitory activity of the five newly designed molecules (from QSAR-aided design, see Table S3 ) on the 3CLpro of SARS-CoV. The results showed that the new molecule with the highest predictive activity in the QSAR also possessed the best docking score [ 66 ].…”

“…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.…”

“…According to “Veber Rules”, a molecule is considered acceptable if it satisfies the following conditions: having 10 or fewer rotatable bonds, a polar surface area equal to or less than 140 Å2, and 12 or fewer hydrogen donors and acceptors. In the research conducted by Ničkčović et al, all five newly designed molecules ( Table S3 ) were found to comply with both the "Lipinski five rules" and “Veber Rules” [ 66 ]. This indicates that these molecules possess desirable drug-like properties and are likely to exhibit satisfactory oral bioavailability.…”

In Silico Therapeutic Study: The Next Frontier in the Fight against SARS-CoV-2 and Its Variants

“…This method involves the mathematical modeling of the relationship between physicochemical properties or molecular descriptors of compounds and their biological activities. Studies have been carried out using QSAR methods to develop phosphorus-based drugs, which have good inhibitory activity against SARS-CoV-2 proteins and their non-synonymous variants [66][67][68]. A QSAR study based on the simplified molecular-input line-entry system (SMILES) strings of 32 bicycloproline derivatives has also been applied in the discovery of COVID-19 therapeutics, with the strings applied in calculating 0D, 1D, and 2D molecular descriptors [69].…”