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Exploiting the potential of natural polyphenols as antivirals against monkeypox envelope protein F13 using machine learning and all-atoms MD simulations.
Rout, Madhusmita; Mishra, Sarbani; Dey, Suchanda; Singh, Mahender Kumar; Dehury, Budheswar; Pati, Sanghamitra.
  • Rout M; Bioinformatics Division, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India.
  • Mishra S; Bioinformatics Division, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India.
  • Dey S; Biomics and Biodiversity Lab, Siksha 'O' Anusandhan (deemed to be) University, Kalinga Nagar, Ghatikia, Bhubaneswar, 751003, Odisha, India.
  • Singh MK; Data Science Laboratory, National Brain Research Centre, Gurgaon, Haryana, 122052, India.
  • Dehury B; Bioinformatics Division, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India. Electronic address: budheswar.dehury@gmail.com.
  • Pati S; Bioinformatics Division, ICMR-Regional Medical Research Centre, Nalco Square, Chandrasekharpur, Bhubaneswar, 751023, Odisha, India. Electronic address: drsanghamitra12@gmail.com.
Comput Biol Med ; 162: 107116, 2023 Aug.
Artículo en Inglés | MEDLINE | ID: covidwho-20230879
ABSTRACT
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.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Mpox / COVID-19 Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: Comput Biol Med Año: 2023 Tipo del documento: Artículo País de afiliación: J.compbiomed.2023.107116

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Mpox / COVID-19 Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: Comput Biol Med Año: 2023 Tipo del documento: Artículo País de afiliación: J.compbiomed.2023.107116