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. 2024 Aug;53(5-6):277-298.
doi: 10.1007/s00249-024-01713-z. Epub 2024 Jun 21.

Computational discovery of dual potential inhibitors of SARS-CoV-2 spike/ACE2 and Mpro: 3D-pharmacophore, docking-based virtual screening, quantum mechanics and molecular dynamics

Boris D Bekono  1   2 , Pascal Amoa Onguéné  3   4 , Conrad V Simoben  3   5 , Luc C O Owono  6   7 , Fidele Ntie-Kang  8   9   10
Affiliations

Computational discovery of dual potential inhibitors of SARS-CoV-2 spike/ACE2 and Mpro: 3D-pharmacophore, docking-based virtual screening, quantum mechanics and molecular dynamics

Boris D Bekono et al. Eur Biophys J. 2024 Aug.

Abstract

To find drugs against COVID-19, caused by the SARS-CoV-2, promising targets include the fusion of the viral spike with the human angiotensin-converting enzyme 2 (ACE2) as well as the main protease (Mpro). These proteins are responsible for viral entry and replication, respectively. We combined several state-of-the-art computational methods, including, protein-ligand interaction fingerprint, 3D-pharmacophores, molecular-docking, MM-GBSA, DFT, and MD simulations to explore two databases: ChEMBL and NANPDB to identify molecules that could both block spike/ACE2 fusion and inhibit Mpro. A total of 1,690,649 compounds from the two databases were screened using the pharmacophore model obtained from PLIF analysis. Five recent complexes of Mpro co-crystallized with different ligands were used to generate the pharmacophore model, allowing 4,829 compounds that passed this prefilter. These were then submitted to molecular docking against Mpro. The 5% top-ranked docking hits from docking result having scores < -8.32 kcal mol-1 were selected and then docked against spike/ACE2. Only four compounds: ChEMBL244958, ChEMBL266531, ChEMBL3680003, and 1-methoxy-3-indolymethyl glucosinolate (4) displayed binding energies < - 8.21 kcal mol-1 (for the native ligand) were considered as putative dual-target inhibitors. Furthermore, predictive ADMET, MM-GBSA and DFT/6-311G(d,p) were performed on these compounds and compared with those of well-known antivirals. DFT calculations showed that ChEMBL244958 and compound 4 had significant predicted reactivity values. Molecular dynamics simulations of the docked complexes were run for 100 ns and used to validate the stability docked poses and to confirm that these hits are putative dual binders of the spike/ACE2 and the Mpro.

Keywords: 3D-pharmacophore; ACE2; Mpro; Quantum mechanics; SARS-CoV-2; Virtual screening.

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References

    1. Becke AD (1988) Density-functional exchange-energy approximation with correct asymptotic behavior. Phys Rev A 38(6):3098–3100. https://doi.org/10.1103/physreva.38.3098 - DOI
    1. Bekono BD, Esmel AE, Dali B, Ntie-Kang F, Keita M, Owono LCO, Megnassan E (2021a) Computer-aided design of peptidomimetic inhibitors of falcipain-3: QSAR and pharmacophore models. Sci Pharm 89(4):44. https://doi.org/10.3390/scipharm89040044 - DOI
    1. Bekono BD, Sona AN, Eni DB, Owono LCO, Megnassan E, Ntie-Kang F (2021b) Molecular mechanics approaches for rational drug design: forcefields and solvation models. Physical Sciences Reviews 8(3):457–477. https://doi.org/10.1515/psr-2019-0128 - DOI
    1. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The Protein Data Bank. Nucleic Acids Res 28(1):235–242. https://doi.org/10.1093/nar/28.1.235 - DOI - PubMed - PMC
    1. Brooke GN, Filippo P (2020) Structural and functional modelling of SARS-CoV-2 entry in animal models. Sci Rep 10(1):15917. https://doi.org/10.1038/s41598-020-72528-z - DOI - PubMed - PMC

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