The nsp16 protein forms a heterodimer with a co-factor nsp10 and triggers 2′-O-methyltransferase activity which catalyzes the conversion of S-adenosyl methionine into S-adenosyl homocysteine. The free methyl group is transferred to the 2′-O position on ribose sugar at the 5′ end of mRNA to form the cap-1 structure which is essential for replication of the virus and evading the innate immunity of the host. In this study, we identify a potential lead natural bioactive compound against nsp16 protein by systematic cheminformatic analysis of more than 144k natural compounds. Virtual screening, molecular docking interactions, ADMET profiling, molecular dynamics (MD) simulations, molecular mechanics-generalized born surface area (MM-GBSA), free energy analysis and density functional theory analysis were used to discover the potential lead compound. Our investigation revealed that ZINC8952607 has the greatest binding affinity and best pharmacokinetic parameters due to presence of carbazol and BLAHone (biaryl moiety). Further, time-dependent MD simulation analysis substantiates the stability and rigidness of nsp16 protein even after interaction with the lead compound.
Techniques: Cheminformatics-assisted
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The nsp14 protein of SARS-CoV-2 is a key target for antiviral drug development as it controls replication of virus and evasion of host immune system. In this study, a consensus of cheminformatics approaches involving virtual screening, molecular docking, ADMET profiling, molecular dynamics simulations, free-energy landscape, MM-GBSA, DFT and 2D-QSAR analysis is employed to discover the inhibitor of nsp14 protein. Our investigation reveals four natural bioactive compounds, i. e. ZINC2132169, ZINC8791872, ZINC8952607 and ZINC6624334 that possess enhanced binding affinity towards nsp14 protein with no predicted toxicity. Molecular docking, MD simulations and MM-GBSA analysis established that all hit compounds strongly bind at the same pocket through hydrophobic interactions and hydrogen bonding. DFT analysis revealed greater reactivity of hit compounds and their stable complex formation with nsp14 protein, while the 2D-QSAR (R2=0.92) predicted their pIC50 value in the range of 5.30–6.71 nM. These findings imply that hit compounds would be potent drug candidates in controlling the SARS-CoV-2 by inhibiting nsp14 protein.
Techniques: Cheminformatics and QSAR-assisted
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Various viral proteins have been identified as potential drug targets, however, to date, no specific therapeutic cure is available against the SARS-CoV-2. To address this issue, the present work reports a systematic cheminformatic approach to identify the potent andrographolide derivatives that can target methyltransferases of SARS-CoV-2, i.e. nsp14 and nsp16 which are crucial for the replication of the virus and host immune evasion. A consensus of cheminformatics methodologies including virtual screening, molecular docking, ADMET profiling, molecular dynamics simulations, free-energy landscape analysis, molecular mechanics generalized born surface area (MM-GBSA), and density functional theory (DFT) was utilized. Our study reveals two new andrographolide derivatives (PubChem CID: 2734589 and 138968421) as natural bioactive molecules that can form stable complexes with both proteins via hydrophobic interactions, hydrogen bonds and electrostatic interactions. The toxicity analysis predicts class four toxicity for both compounds with LD50 value in the range of 500–700 mg/kg. MD simulation reveals the stable formation of the complex for both the compounds and their average trajectory values were found to be lower than the control inhibitor and protein alone. MMGBSA analysis corroborates the MD simulation result and showed the lowest energy for the compounds 2734589 and 138968421. The DFT and MEP analysis also predicts the better reactivity and stability of both the hit compounds. Overall, both andrographolide derivatives exhibit good potential as potent inhibitors for both nsp14 and nsp16 proteins, however, in-vitro and in vivo assessment would be required to prove their efficacy and safety in clinical settings.
Techniques: Cheminformatics-assisted
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