Synthesis of Dihydrobenzofuro[3,2‐b]chromenes as Potential 3CLpro Inhibitors of SARS‐CoV‐2: A Molecular Docking and Molecular Dynamics Study

Abstract

The recent emergence of pandemic of coronavirus (COVID‐19) caused by SARS‐CoV‐2 has raised significant global health concerns. More importantly, there is no specific therapeutics currently available to combat against this deadly infection. The enzyme 3‐chymotrypsin‐like cysteine protease (3CLpro) is known to be essential for viral life cycle as it controls the coronavirus replication. 3CLpro could be a potential drug target as established before in the case of severe acute respiratory syndrome coronavirus (SARS‐CoV) and Middle East respiratory syndrome coronavirus (MERS‐CoV). In the current study, we wanted to explore the potential of fused flavonoids as 3CLpro inhibitors. Fused flavonoids (5a,10a‐dihydro‐11H‐benzofuro[3,2‐b]chromene) are unexplored for their potential bioactivities due to their low natural occurrences. Their synthetic congeners are also rare due to unavailability of general synthetic methodology. Here we designed a simple strategy to synthesize 5a,10a‐dihydro‐11H‐benzofuro[3,2‐b]chromene skeleton and it's four novel derivatives. Our structural bioinformatics study clearly shows excellent potential of the synthesized compounds in comparison to experimentally validated inhibitor N3. Moreover, in‐silico ADMET study displays excellent druggability and extremely low level of toxicity of the synthesized molecules. Further, for better understanding, the molecular dynamic approach was implemented to study the change in dynamicity after the compounds bind to the protein. A detailed investigation through clustering analysis and distance calculation gave us sound comprehensive data about their molecular interaction. In summary, we anticipate that the currently synthesized molecules could not only be a potential set of inhibitors against 3CLpro but also the insights acquired from the current study would be instrumental in further developing novel natural flavonoid based anti‐COVID therapeutic spectrums.

Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates

“…This is the distance between the rotational axis and the mass center [112]. It is essential and important to know and understand how structural variation affects the compactness of the protein after binding with the ligands when examining the stability and flexibility of the complex structure during simulation [113], and this can be accomplished by analyzing the complex structure's radius of gyration (Rg). Higher Rg values indicate that the protein is less compact and flexible, whereas low values indicate that the protein packing has not changed much (see Figure 12C), thus exemplifying the high degree of compactness and stiffness.…”

“…Similarly, we examined the formation of hydrogen bonds in the complex structure by plotting the number of hydrogen atoms against time. This is necessary for a better understanding of the protein's structural integrity, catalytic region, and protein-ligand interaction in the complex structure [113]. Within the complex structure of the protein, there is a significant change in the hydrogen bond interaction (see Figure 12D).…”

“…SASA is a significant parameter for determining the extent of receptor exposure to surrounding solvent molecules during simulation [111]. SASA with a higher value indicates more hydrophilicity [113]. The SASA complex trajectory values gradually decreased till 400 ns.…”

Computational Exploration of Anti-cancer Potential of Flavonoids against Cyclin-Dependent Kinase 8: An In Silico Molecular Docking and Dynamic Approach

“…The EM of subjected complex systems was done using 5000 steps of the steepest descent algorithm and the protein–ligand complex was neutralized. The simulation was performed in the presence of 0.15 M NaCl . Canonical ( NVT ) and isothermal–isobaric ( NPT ) ensembles after each step of EM were done to equilibrate the simulated systems. − The MD simulation of the protein–ligand complex was performed in different temperature conditions (298, 300, 305, 310, and 320 K), and each time, the temperature was maintained with the help of the Berendsen thermostat approach while the pressure was maintained at 1.0 bar using the Parrinello–Rahman barostat approach to control the entire simulated complex system in each temperature condition. − All the simulations were performed for 100 ns, and the obtained trajectories of MD simulation at different temperature conditions were used further for statistical analysis (RMSD, RMSF, R g , and HBs) .…”

“…The simulation was performed in the presence of 0.15 M NaCl. 79 Canonical ( NVT ) and isothermal–isobaric ( NPT ) ensembles after each step of EM were done to equilibrate the simulated systems. 80 − 82 The MD simulation of the protein–ligand complex was performed in different temperature conditions (298, 300, 305, 310, and 320 K), and each time, the temperature was maintained with the help of the Berendsen thermostat approach while the pressure was maintained at 1.0 bar using the Parrinello–Rahman barostat approach to control the entire simulated complex system in each temperature condition.…”