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Research Article

Bioprospecting of Meliaceae family phytomolecules for the treatment of monkeypox virus infection: a QSAR modeling and MD simulation approach

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Received 10 Jul 2023, Accepted 01 Dec 2023, Published online: 04 Jan 2024
 

Abstract

Recent monkeypox virus (MPXV) infections show the risk of MPXV transmission that persists today and the significance of surveillance and quick response methods to stop the virus’s spread. Currently, the monkeypox virus infection is not specifically treated. In this study, QSAR models were designed using known inhibitors of cysteine proteinase from the vaccinia virus, where the Random Forest model and Ridge model had showed the best correlation between predicted and observed EC50. These models were used to screen Maliaceae family phytochemicals against MPXV cysteine proteinase. The compound, IMPHY010637 was detected in top 5 from both the QSAR screening models and showed best docked score (-8.6 kcal/mol) and thus selected for further investigation. Further, the IMPHY010637 showed interaction with the catalytic residue His241 of the protein as reported in earlier studies. The ADMET analysis of the compound showed the acceptable drug-like properties of IMPHY010637. However, these properties could be improved after experimental validation of protein-ligand binding. Both docked complex and poses created in 100 ns MD simulation of the protein-ligand complex showed the presence of multiple hydrogen bonds. RMSD and conformation analysis showed stable binding of IMPHY010637 with the cysteine proteinase of MPXV at its active site. Compared to the known inhibitor, IMPHY010637 showed better binding with the protein as observed by the PCA and MM/GBSA analysis. This study concluded IMPHY010637 as a potential inhibitor for the cysteine proteinase of MPXV using computational methods that could be tested in in-vitro experiments.

Communicated by Ramaswamy H. Sarma

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study is supported via funding from Prince Sattam bin Abdulaziz University project number (PSAU/2023/R/1445).

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