Eco-Technological Evaluation of Natural Phytochemicals Potential Drug Molecules Against Main Protease: A Machine Learning Algorithm

天然植物化学潜在药物分子对抗主要蛋白酶的生态技术评价:一种机器学习算法

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Abstract

Introduction: The global viral pandemic has rapidly spread, leading to many individuals experiencing the infection. Coronaviruses (CoVs) are among many viral families that infect different types of mammals. They can spread to humans and cause gastrointestinal, neurological, and respiratory problems. The present investigation has discovered flavonoid compounds as promising molecular agents with potential antiviral activity against virus proteins, specifically main protease (Mpro). Methodology: A comprehensive in silico screening of natural compounds derived from medicinal plants was performed in the present study. It included parameter assessments such as drug-likeness, pharmacokinetics, molecular docking, toxicity evaluations, bioavailability assessments, and molecular target exploration. In this systematic approach, the primary objective was to identify potential lead compounds. These phytochemicals were investigated as drug candidates to provide a detailed understanding of their molecular properties. Results: The Mpro binding energy values were -10.637, -12.752, -7.813, -15.732, -6.449, -5.578, -8.037, and -8.52 kcal/mol for isoquercetin, narirutin, myricetin, hesperidin, silibinin, baicalein, taxifolin, and petunidin. Molecular simulations were conducted on two flavonoid compounds - hesperidin and narirutin - stable over 100 nanoseconds in the Coronavirus protein. Conclusions: The computational study we conducted is promising, but to validate the action of these compounds, further experimental studies are needed, with a critical component of the research being the conduct of in vitro and in vivo experiments.

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