Computational evaluation of Withania somnifera phytocompounds targeting SARS-CoV-2 ORF9b Protein: Insights from molecular docking, ADMET and MD simulations

利用分子对接、ADMET和MD模拟方法对南非醉茄植物化合物靶向SARS-CoV-2 ORF9b蛋白进行计算评价:

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Abstract

The COVID-19 pandemic, caused by SARS-CoV-2, has emerged as a global health crisis, leading to widespread morbidity and mortality, causing significant disruption to daily life and socio-economic activities worldwide. The outbreak created an urgent need for novel therapeutics and vaccines. However, several of these pharmaceutical interventions have exhibited adverse effects with prolonged usage, emphasizing the need for alternative or complementary therapeutic approaches. Withania somnifera (known as Ashwagandha) has gained attention due to its long history of use in traditional medicine and its reported antiviral, immunomodulatory, and anti-inflammatory properties. This study investigates the binding affinities and molecular interactions of particularly three bioactive compounds in detail - Ashwagandhanolide, Sitoindoside IX and Withanolide D - using molecular docking techniques. The analysis revealed binding affinities of -9.5 kcal/mol, -8.8 kcal/mol and -8.9 kcal/mol, respectively. Detailed interaction profiles identified ADMET profiling pharmacophore modeling, van der Waals forces, hydrogen bonding, and hydrophobic interactions as key contributors to drug-likeness and stability of these compounds. These findings provide insights into the compounds' potential pharmacological applications and establish a foundation for experimental validation in the future.

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