Identifying and Evaluating Flavonoids as Potential Inhibitors of SARS-CoV-2 Main Protease (Mpro/3CL) Through Docking and Molecular Dynamics

Identification of Potential SARS-CoV-2 Main Protease (MPro) Inhibitors Through Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Simulation Approaches

The findings suggest that Lig-1, followed by Lig-3, may serve as promising computational lead compounds targeting SARS-CoV-2 MPro, representing promising candidates for further experimental validation.

Natural Metabolites from Clinacanthus nutans as Promising SARS-CoV-2 Main Protease Inhibitors: Insights from Molecular Docking and Dynamics Simulations

Structure-based drug design against SARS-CoV-2 main protease (Mpro) was enabled by the availability of its crystal structure (PDB ID: 6LU7). In this study, metabolites from Clinacanthus nutans were computationally evaluated as potential Mpro inhibitors using validated molecular docking and molecular dynamics (MD) approaches. Native ligand re-docking produced an RMSD of 1.329 Å, confirming the reliability of the docking setup. Among the tested compounds, vitexin demonstrated a favorable binding affinity in docking analysis, indicating its potential for interaction within the active site of Mpro. However, further evaluation using 100 ns MD simulations and MM/PBSA free energy calculations revealed that, although the vitexin–Mpro complex remained relatively stable, the native ligand exhibited superior thermodynamic stability and binding free energy. Overall, vitexin shows promising binding characteristics as a natural compound targeting Mpro, but it does not surpass the native ligand in terms of overall binding stability. These findings suggest that vitexin may serve as a potential lead compound, warranting further optimization and experimental validation.

In Silico Identification of Potent SARS-CoV-2 RdRp Inhibitors: DFT and Molecular Docking Analysis of Acylated Glucopyranoside Derivatives

The results demonstrate the promise of modified MDG derivatives as lead compounds and justify further in vitro and in vivo studies to validate their antiviral activity against SARS-CoV-2.

Integrated Computational Study Prioritizes Drug-like Para-Flavonoids as Candidate SARS-CoV-2 Mpro Inhibitors

Emerging SARS-CoV-2 variants highlight the need for orally active, low-toxicity antivirals. We designed seven para-substituted flavonoid hybrids (M1–M7) against the main protease (Mpro). In silico ADME filtering revealed zero Lipinski, Veber, or Ghose violations, a SwissADME bioavailability score of 0.55, and selected favorable predicted absorption and transporter endpoints relative to lopinavir, without implying measured pharmacokinetic superiority. ProTox-III indicated that amino and nitro substitution increased predicted genotoxicity liabilities, whereas cyano and methoxy substitution reduced selected endocrine-related signals. AutoDock Vina docking to Mpro (PDB 9C8Q; redocking RMSD 0.316 Å) ranked the nitro analogue M6 first among the designed compounds (−8.1 kcal mol−1), with contacts involving His41 and neighboring active-site residues. During the 100 ns GROMACS simulations, the protein backbone remained stable, whereas M6 adopted a late reoriented pose that was retained in the active-site region and supported by late-window per-residue energetic contributions. DFT calculations at the B3LYP/6-311G(d,p) level identified the narrowest HOMO-LUMO gap (3.44 eV) and highest electrophilicity (ω = 6.2 eV) for M6. Overall, M6 is prioritized as a computational lead requiring Mpro inhibition, antiviral, and cytotoxicity validation.

IN SILICON EVALUATION OF ARTEMISININ DERIVATIVES AS POTENTIAL INHIBITORS OF SARS-COV-2 MAIN PROTEASE

Four artemisinin-derived compounds namely, artesunate, artemether, artemisinin and dihydroartemisinin were evaluated as potential Mpro binders using molecular docking and post docking interaction analysis and among the tested ligands, artesunate showed the most favorable predicted binding affinity with docking score.

Identification of potential SARS-CoV-2 Mpro inhibitors from a Thai natural product database via interaction fingerprint-based virtual screening