Structure-based Discovery Of Aldehyde Derivatives As SARS-CoV-2 Inhibitors

Abstract

This study aimed to explore the medicinal compounds among aldehyde derivatives from seaweeds as potential SARS-CoV-2 inhibitors through the structure-based drug discovery approach. The absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties of the aldehyde derivatives were analyzed using a machine learning algorithm, and the docking simulation of these aldehyde derivatives to the 3C-like protease was analyzed using a molecular docking protocol based on the CHARMm algorithm. These aldehyde derivatives exhibited good drug-like properties following the Lipinski and Veber rules. Among them, 4-hydroxybenzaldehyde, 3-hydroxybenzaldehyde, 3,4-dihydroxybenzaldehyde, and 5-bromoprotocatechualdehyde were predicted to have good absorption and solubility levels and non-hepatotoxicity in the ADME/Tox prediction. 3-hydroxybenzaldehyde and 3,4-dihydroxybenzaldehyde were predicted to be non-toxic in TOPKAT prediction. In addition, 3,4-dihydroxybenzaldehyde was predicted to exhibit interactions with the 3C-like protease, with binding energies of -71.9725 kcal/mol. The computational analyses indicated that 3,4-dihydroxybenzaldehyde could be regarded as potential a SARS-CoV-2 inhibitor.