Acacetin shows potency against SARS-CoV-2 spike protein

In a recent Journal of the Indian Chemical Society study, researchers use molecular docking to screen 12 phytocompounds and evaluate their binding affinity with main proteases and mutants of the receptor-binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein.

Study: Evaluation of binding performance of bioactive compounds against main protease and mutant model spike receptor-binding domain of SARS-CoV-2: Docking, ADMET properties and molecular dynamics simulation study. Image Credit: Juan Gaertner /

About the study

In the present study, researchers derived 424 compounds from a herbal extract of several plants including Zingiber officinale, Syzygiumaromaticum, Ocimum tenuiflorum, Citrus limon, and Curcumin, within the retention time of 22 minutes. The researchers subsequently identified these compounds using the National Institute of Standards and Technology (NIST) database.

Gas chromatography-mass spectrometry (GC/MS) analysis revealed the presence of 12 antiviral phytochemicals among these 424 bioactive compounds. The 12 identified antiviral phytochemicals included thebaine, acacetin, indomethacin, crinamine acetate, (S)-1-Piperideine-6-carboxylate, levamisole, melatonin, nicotinic acid, curcumin, methotrimeprazine, omeprazole, and methaqualone.

The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, as well as the physicochemical properties, such as partition coefficient (logP), hydrogen bond donors/acceptor, solubility coefficient (logS), number of rotatable bonds, and polar surface area (PSA), were evaluated for each phytochemical.

Additionally, the researchers examined the molecular interactions of the identified compounds, specifically hydrophobic and electrostatic interactions, as well as hydrogen bonding during molecular docking studies.

Furthermore, the dynamic properties of the 6LU7-acacetin, 6Y2E-acacetin, and S RBD-acacetin systems were assessed by molecular dynamics (MD) simulations. Gmx rms module was also used to compute the root mean square deviation (RMSD) of the backbone atoms for these systems.

Any changes in the average movement of the position of an atom at a given temperature and pressure in relation to the overall protein structure or its flexible region(s) were also determined by Root Mean Square Fluctuation (RMSF). Solvent-accessible surface area (SASA) computations were also used to calculate the extent of conformational changes and expansion of the protein volume that occurred during the interaction between the complexes and solvents.

Both gmxcovar and gmxanaeig modules were used to study the dynamic behavior of the 6LU7- acacetin, 6Y2E-acacetin, and spike RBD-acacetin, whereas the motions of these chemicals were assessed by principal component analysis (PCA). Additionally, the researchers verified the flexible aspect using covariance matrix diagonalization.

Study findings

Except for (S)-1-Piperideine-6-carboxylate and nicotinic acid, all other compounds had a log P-value greater than one. Likewise, log S values were within -4.5 to -1 for all the compounds except (S)-1-Piperideine-6-carboxylate, and PSA for all studied compounds was less than 140 Å2.

Low fluctuations and low RMSD values indicate a system's stability. The RMSD fluctuation analysis revealed that the MD trajectories for the entire studied protein-ligand complexes were generally stable and within acceptable ranges during the 100 nanoseconds (ns) simulation period.

RMSD values for the 6Y2E-acacetin system decreased over time as compared to the 6LU7-acacetin system during a 100 ns simulation cycle. The average RMSD values for the 6Y2E-acacetin, 6LU7- acacetin, and S RBD-acacetin systems were 0.15, 0.21, and 0.17 nm, respectively.

The authors also observed fluctuations in the LEU50, ASN72, PRO96, TYR 154, GLY170, ALA 193, ARG 222, and MET 274 residues for both the 6LU7-acacetin and 6Y2E-acacetin systems. Additional fluctuations were observed in the S RBD-acacetin system in residues GLY446, SER477, GLY482, THR500, and LEU518. Higher RMSF values in the double mutant of the S RBD-acacetin complex implied more flexibility throughout the MD simulation, whereas a lower RMSF value indicated the stability of the 6Y2E-acacetin simulated system.

The gmx hbond module predicted 215.77, 216.49, and 117.28 average hydrogen bond numbers for 6LU7-acacetin, 6Y2E-acacetin, and spike RBD-acacetin systems, respectively. This finding suggests that acacetin was bound with 6LU7 and 6Y2E more effectively and tightly than the S RBD protein. Moreover, the observed higher average hydrogen bond number of 6Y2E proteins with acacetin was attributed to a lower RMSF value.

A higher value of the radius of gyration (Rg) indicates lower compactness of the ligand-protein complex. These initially were 2.2 nm for the 6LU7- acacetin system and attained a value of 2.1nm at 100 ns, averaging 2.21nm.

Similar fluctuating patterns were reported for the S RBD-acacetin system, where the Rg value was 1.9 nm at 94 ns, and the average Rg value was 1.86 nm. Further, the researchers observed a consistent Rg value of 2.18 nm throughout the 100 ns simulation time, leading to a more stable binding of 6Y2E with acacetin for the 6Y2E-acacetin system.

The SASA value for the 6LU7-acacetin system varied between 167 to 169 nm2, and the average SASA values for 6Y2E-acacetin and the S RBD-acacetin systems were 168.33 and 109.03 nm2, respectively. A higher SASA value for 6Y2E-acacetin indicated that 6Y2E was more expandable to bind with acacetin in comparison with 6LU7-acacetin and the S RBD-acacetin.

SASA values for 6LU7- acacetin, 6Y2E-acacetin, and S RBD-acacetin were 12.29, 6.27, and 10.33 nm2, respectively. A lower value of covariance matrix indicates less dynamic structural conformation and was observed for 6Y2E-acacetin at 6.27 nm2. This revealed that 6Y2E-acacetin was much-less dynamic in structural conformation than both 6LU7- acacetin and S RBD-acacetin.

The size and shape of the minimum energy region of the free energy landscape indicate a complex's stability. The S RBD-acacetin complex had several minima, indicating its stability, whereas the 6LU7-acacetin and 6Y2E-acacetin complexes achieved only single energy minima.


Molecular docking analysis showed that SARS-CoV-2 protease residues including LEU50, ASN72, PRO96, TYR154, GLY170, ALA193, ARG222, and MET274 play a crucial role in the binding of examined protein complexes with ligands. Notably, interactions also occurred between residues GLY446, SER477, GLY482, THR500, LEU518, as well as the mutant RBD of the S protein.

To conclude, the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) results and 100 ns MD simulations suggest that acacetin is a potent inhibitor of main proteases and mutants of RBD of SARS-CoV-2 S protein.

Journal reference:
  • Moharana, M., Das, A., Narayan Sahu, S. N., et al. (2022). Evaluation of binding performance of bioactive compounds against main protease and mutant model spike receptor-binding domain of SARS-CoV-2: Docking, ADMET properties and molecular dynamics simulation study. Journal of the Indian Chemical Society. doi:10.1016/j.jics.2022.100417.

Posted in: Drug Discovery & Pharmaceuticals | Medical Science News | Medical Research News | Disease/Infection News | Pharmaceutical News

Tags: binding affinity, Chemicals, Chromatography, Compound, Coronavirus, Coronavirus Disease COVID-19, Curcumin, Drug Discovery, Gas Chromatography, Indomethacin, Ligand, Mass Spectrometry, Melatonin, Metabolism, Phytochemical, Protein, Receptor, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Spectrometry, Spike Protein, Syndrome

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Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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