Calendulaglycoside A showing potential activity against SARS-CoV-2 main protease: Molecular docking, molecular dynamics, and SAR studies

Abstract

Background and aim: The discovery of drugs capable of inhibiting SARS-CoV-2 is a priority for human beings due to the severity of the global health pandemic caused by COVID-19. To this end, natural products can provide therapeutic alternatives that could be employed as an effective safe treatment for COVID-19.

Experimental procedure: Twelve compounds were isolated from the aerial parts of C. officinalis L. and investigated for their inhibitory activities against SARS-CoV-2 M^pro compared to its co-crystallized N3 inhibitor using molecular docking studies. Furthermore, a 100 ns MD simulation was performed for the most active two promising compounds, Calendulaglycoside A (SAP5) and Osteosaponin-I (SAP8).

Results and conclusion: At first, molecular docking studies showed interesting binding scores as compared to the N3 inhibitor. Calendulaglycoside A (SAP5) achieved a superior binding than the co-crystallized inhibitor indicating promising affinity and intrinsic activity towards the M^pro of SARS-CoV-2 as well. Moreover, findings illustrated preferential stability for SAP5 within the M^pro pocket over that of N3 beyond the 40 ns MD simulation course. Structural preferentiality for triterpene-M^pro binding highlights the significant role of 17β-glucosyl and carboxylic 3α-galactosyl I moieties through high electrostatic interactions across the MD simulation trajectories. Furthermore, this study clarified a promising SAR responsible for the antiviral activity against the SARS-CoV-2 M^pro and the design of new drug candidates targeting it as well. The above findings could be promising for fast examining the previously isolated triterpenes both pre-clinically and clinically for the treatment of COVID-19.

Keywords: C. officinalis L.; COVID-19; Computational studies; SAR; Triterpenes.

Graphical abstract

Fig. 1

Time evolution RMSD trajectories of the three investigated ligand-protein complexes over 100 ns all-atom MD simulation. (A) protein RMSD relative to its backbone; (B) ligand backbone RMSD; (C) protein-ligand complex backbone RMSD, as a function of the MD simulation time (ns). Trajectories for SAP5/protein, SAP8/protein, and N3/protein systems are represented in green, blue, and red, respectively.

Fig. 2

Projection of protein atoms in phase space along the first two dominant eigenvectors (eigenvector-1 and eigenvector-2). (A) SAP5/protein; (B) SAP8/protein; (C) N3/protein. The PCA calculations were conducted cross initial and last equilibrated intervals of MD simulation trajectories, having exhibiting differential expected structural stability and convergence.

Fig. 3

Analysis of ΔRMSF trajectories versus residue number of the three investigated ligand-protein complexes over 100 ns all-atom MD simulation. The ΔRMSF values, about protein backbone, were estimated considering independent MD simulation of SARS-CoV-2 main protease apo-state (PDB ID: 6y84) against the holo-states being complexed with either of the three investigated ligands and finally being represented as a function of residue number (residues 1-to-306). Trajectories for SAP5/protein, SAP8/protein, and N3/protein complexes are represented in green, blue, and red, respectively.

Fig. 4

Time-evolution Rg trajectories of the three investigated ligand-protein complexes over 100 ns all-atom MD simulation. (A) protein Rg; (B) ligand Rg; (C) ligand-protein complex Rg, as a function of the MD simulation time (ns). Trajectories for SAP5/protein, SAP8/protein, and N3/protein complexes are represented in green, blue, and red, respectively.

Fig. 5

Time-evolution SASA trajectories of the three investigated ligand-protein complexes over 100 ns all-atom MD simulation. (A) protein SASA; (B) ligand SASA; (C) ligand-protein complex, as a function of the MD simulation time (ns). Trajectories for SAP5/protein, SAP8/protein, and N3/protein complexes are represented in green, blue, and red, respectively.

Fig. 6

Time-evolution hydrogen donner-acceptor distances between the two final promising leads and control inhibitor with crucial protein pocket residues versus 100-ns MD simulation time. (A) N3 control inhibitor; (B) SAP5; (C) SAP8. The vertical and horizontal axes represent the hydrogen donner-acceptor distances (Å) and MD simulation time (ns), respectively.

Fig. 7

Conformation analysis of ligand-protein complex within the binding site of SARS-CoV-2 M^pro at selected frames. (A) SAP5; (B) N3 potent inhibitor control; (C) SAP8. Protein is represented in cartoon 3D representation and colored in green, yellow, or red as corresponding to the extracted frames at 0 ns, 30 ns, and 100 ns, respectively. Ligands (sticks), key binding residues (lines), and hydrogen bonding (dashed lines) are represented in colors corresponding to their respective time frame.

Fig. 8

Time-evolution energy and temperature trajectories of the three investigated systems over 100 ns all-atom MD simulation. (A) potential energy; (B) kinetic energy; (C) total energy; and (D) temperature, as a function of the MD simulation time (ns). Trajectories for SAP5, SAP8, and N3-bound systems are represented in green, blue, and red, respectively.

Fig. 9

Time-evolution MD trajectories of the non-bonded potential energy and its components for the three investigated ligand-protein complexes over 100 ns all-atom MD simulation. (A) Lennard-Jones potential; (B) Coulomb's electrostatic potential; (C) total non-bonded energy, as a function of the MD simulation time (ns). Trajectories for SAP5/protein, SAP8/protein, and N3/protein complexes are represented in green, blue, and red, respectively.

Fig. 10

Binding-free energy/residue decomposition illustrating the protein residue contribution at ligand-protein complex ΔE_binding calculation. (A) SAP5/M^pro residues; (B) N3/M^pro residues.

Fig. 11

Structure-activity relationships of the tested triterpenes isolated from C. officinalis aerial parts.