Exploiting the potential of natural polyphenols as antivirals against monkeypox envelope protein F13 using machine learning and all-atoms MD simulations.

The re-emergence of monkeypox (MPX), in the era of COVID-19 pandemic is a new global menace. Regardless of its leniency, there are chances of MPX expediting severe health deterioration. The role of envelope protein, F13 as a critical component for production of extracellular viral particles makes it a crucial drug target. Polyphenols, exhibiting antiviral properties have been acclaimed as an effective alternative to the traditional treatment methods for management of viral diseases. To facilitate the development of potent MPX specific therapeutics, herein, we have employed state-of-the-art machine learning techniques to predict a highly accurate 3-dimensional structure of F13 as well as identify binding hotspots on the protein surface. Additionally, we have effectuated high-throughput virtual screening methodology on 57 potent natural polyphenols having antiviral activities followed by all-atoms molecular dynamics (MD) simulations, to substantiate the mode of interaction of F13 protein and polyphenol complexes. The structure-based virtual screening based on Glide SP, XP and MM/GBSA scores enables the selection of six potent polyphenols having higher binding affinity towards F13. Non-bonded contact analysis, of pre- and post- MD complexes propound the critical role of Glu143, Asp134, Asn345, Ser321 and Tyr320 residues in polyphenol recognition, which is well supported by per-residue decomposition analysis. Close-observation of the structural ensembles from MD suggests that the binding groove of F13 is mostly hydrophobic in nature. Taken together, this structure-based analysis from our study provides a lead on Myricetin, and Demethoxycurcumin, which may act as potent inhibitors of F13. In conclusion, our study provides new insights into the molecular recognition and dynamics of F13-polyphenol bound states, offering new promises for development of antivirals to combat monkeypox. However, further in vitro and in vivo experiments are necessary to validate these results.

Identification of phytocompounds as newer antiviral drugs against COVID-19 through molecular docking and simulation based study.

COVID-19 pandemic has emerged as a global threat with its highly contagious and mutating nature. Several existing antiviral drugs has been worked on, without proper results and meanwhile the virus is mutating rapidly to create more infectious variant. In order to find some alternatives, phytocompounds can be opted as good one. In this study, three hundred phytocompounds were screened virtually against two viral proteins namely main protease and spike protein. Molecular docking and dynamic simulation study was used to find binding affinity, structural stability and flexibility of the complex. Pharmacokinetic properties were studied through ADMET analysis. To understand energy variation of the complex structure free energy landscape analysis was performed. Among three hundred phytocompounds virtual screening, three phytocompounds were selected for detailed molecular interaction analysis. Oleanderolide, Proceragenin A and Balsaminone A, showed strong binding affinity against both the target proteins and reflected conformational stability throughout the MD run. Oleanderolide, proceragenin A and balsaminone A has docking score -9.4 kcal/mol, -8.6 kcal/mol, and -8.1 kcal/mol respectively against main protease and same -8.3 kcal/mol docking score against spike protein. These three phytocompounds has high gastrointestinal absorption capacity. They were unexplored till now for their antiviral activity. Their promising in silico results suggests that they can be promoted in the long run for development of new antiviral drugs.