Exploring 7β-Amino-6-Nitrocholestens as COVID-19 Antivirals: In silico, Synthesis, Evaluation, and Integration of Artificial Intelligence (AI) in Drug Design: Assessing the Cytotoxicity and Antioxidant Activity of 3β-Acetoxynitrocholestane

Abstract

In light of the ongoing pandemic caused by SARS-CoV-2, effective and clinically translata-ble treatments are desperately needed for COVID-19 and its emerging variants. In this study, some derivatives, including 7β-aminocholestene compounds, and 3β-acetoxy-6-nitrocholesta-4,6-diene were synthesized, in quantitative yields from 7β-bromo-6-nitrocholest-5-enes (1-3) with a small library of amines. The synthesized steroidal products were then thoroughly characterized using a range of physicochemical techniques, including IR, NMR, UV, MS, and elemental analysis. Next, a virtual screening based on structures using docking studies was conducted to investigate the potential of these synthe-sized compounds as therapeutic candidates against SARS-CoV-2. Specifically, we evaluated the compounds' binding energy of the reactants and their products with three SARS-CoV-2 functional proteins: the papain-like protease, 3C-like protease or main protease, and RNA-dependent RNA polymerase. Our results indicate that the 7β-aminocholestene deriva-tives (4-8) display intermediate to excellent binding energy, suggesting that they interact strongly with the receptor's active amino acids and may be promising drug candidates for in-hibiting SARS-CoV-2. Although the starting steroid derivatives; 7β-bromo-6-nitrocholest-5-enes (-3) and one steroid product; 3β-acetoxy-6-nitrocholesta-4,6-diene (9) exhibited strong binding energies with various SARS-CoV-2 receptors, they did not meet the Lipinski Rule and ADMET properties required for drug development. These compounds showed either mutagenic or reproductive/developmental toxicity when assessed using toxicity prediction software. The findings based on structure-based virtual screening, suggest that 7β-aminocholestaines (4–8) may be useful for reducing the susceptibility to SARS-CoV-2 infection. The docking pose of com-pound 4, which has a high score of -7.4 kcal/mol, was subjected to AI-assisted deep learning to generate 60 AI-designed molecules for drug design. Molecular docking of these AI molecules was performed to select optimal candidates for further analysis and visualization. The cytotoxicity and antioxidant effects of 3β-acetoxy-6-nitrocholesta-4,6-diene were tested in vitro, showing marked cytotoxicity and antioxidant activity. To elucidate the molecular basis for these effects, steroidal compound 9 was subjected to molecular docking analysis to identify potential binding interactions. The stability of the top-ranked docking pose was subsequently assessed using molecular dynamics simulations.

Supplementary files

Article information

Article type
Research Article
Submitted
13 Apr 2024
Accepted
22 Sep 2024
First published
26 Sep 2024

RSC Med. Chem., 2024, Accepted Manuscript

Exploring 7β-Amino-6-Nitrocholestens as COVID-19 Antivirals: In silico, Synthesis, Evaluation, and Integration of Artificial Intelligence (AI) in Drug Design: Assessing the Cytotoxicity and Antioxidant Activity of 3β-Acetoxynitrocholestane

S. ., U. ., M. Azam, M. parveen, N.H.A. Kadir, K. Min and M. Alam, RSC Med. Chem., 2024, Accepted Manuscript , DOI: 10.1039/D4MD00257A

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