Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis

Abstract

The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro. A comprehensive analysis of compounds from the ChemDiv and PubChem databases was performed. The physicochemical properties, pharmacokinetics, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiles were evaluated to determine drug similarity and safety. Compound 4896 - 4038 proved to be the most promising candidate. It exhibited a favorable balance between molecular weight (491.06) and lipophilicity (logP 3.957), high intestinal absorption (92.119%), and broad tissue distribution (VDss of 0.529), indicating good oral bioavailability and therapeutic potential. Molecular docking studies showed that 4896 - 4038 has a strong binding affinity to the active site of Mpro and forms key interactions, such as hydrogen bonds, carbon-hydrogen bonds, pi-sulfur, and multiple van der Waals and pi-pi stacked bonds. The binding energy was comparable to that of the reference drug X77, indicating potential efficacy. Molecular dynamics simulations over 300 ns confirmed the stability of the Mpro/4896 - 4038 complex of protein-ligand. Free energy landscape mapping and MM/PBSA calculations further substantiated the favorable binding and stability of the complex. Importantly, 4896 - 4038 exhibited a comparatively favorable safety profile. In summary, compound 4896 - 4038 shows significant potential as a potent SARS-CoV-2 Mpro inhibitor, combining potent inhibitory activity with favorable pharmacokinetic and safety profiles. These results support the further development of 4896 - 4038 as a promising therapeutic agent in the fight against COVID-19 that warrants experimental validation and clinical investigation.

Keywords: 3CLpro; COVID-19; Molecular Docking; Molecular dynamics, ADMET; Mpro; SARS-CoV-2.

Fig. 1

- Physicochemical (left) and ADMET (right) properties for each compound. Blue denotes values that fit within acceptable ranges, with red falling short of them. For the CYP enzymes family, blue denotes interaction and red denotes non-interaction as a substrate and/or inhibitor.

Fig. 2

- Results of each ligand’s geometry optimization and their respective binding energy as seen in Table 2.

Fig. 3

- Protein-ligand complexes after molecular docking. (A) Docked pose of ligand X77 in Mpro and its respective intermolecular binding forces. (B) Docked pose of ligand 4896 − 4038 in Mpro and its respective intermolecular binding forces.

Fig. 4A

displays the time-dependent RMSD values of the C-alpha atoms in relation to the complex structure, which were computed during MD simulations. It can be observed that in the first 150 ns of the simulation, the Mpro/X77 complex is more stable than the Mpro/4869 − 4038 complex. The Mpro/4869 − 4038 complex shows an increased RMSD value (up to 0.5 nm) between 150–200 ns, while the Mpro/X77 complex shows a slight decrease in the RMSD value (from 0.3 to 0.2 nm). However, both complexes stabilize similarly around 0.25 nm after 200 ns simulations, which is a very low value for RMSD analysis. These results indicate that the simulation time was able to obtain stable protein-ligand complexes.

Fig. 5

- Free energy landscape (FEL) and principal component analysis (PCA) of the protein-ligand complex. The figure shows the FEL obtained from the molecular dynamics (MD) simulation of the protein-ligand complex. The PCA was used to reduce the dimensionality of the data, with principal components PC1 and PC2 representing the directions of the largest conformational variations. The blue areas represent stable conformations with lower free energy, while the red areas show less stable conformations with higher energy.

Fig. 6

- Free binding energy from the MM/PBSA calculation from the last 500 frames (50 ns) of each simulation. The black line represents the energy of the Mpro/X77 complex and the red line corresponds to Mpro/4896 − 4038.

Fig. 7

- Per residue decomposition energy analysis showing the amino acids that contribute most to binding affinity with ligands X77 and 4896 − 4038.