Exploring the potential of Hispaglabridin B as an mTOR modulator: A molecular dynamics approach from Glycyrrhiza glabra

Abstract

In recent years, in silico methods have emerged as powerful tools for accelerating and enhancing biological and chemical research through computational simulations. This study explores the application of in silico approaches to identify potential lead compounds from Glycyrrhiza glabra for the treatment of glioblastoma multiforme (GBM). By utilizing advanced computational techniques such as molecular docking, molecular dynamics (MD) simulations, and machine learning models, we aimed to predict the binding affinity and orientation of promising candidates. Notably, high-affinity compounds like HISPAGLABRIDIN B (IMPHY001500) were identified, and novel insights into molecular interactions were validated through MD simulations using GROMACS. This research highlights the effectiveness of in silico techniques in accelerating the drug discovery pipeline and uncovering novel molecular targets like mTOR. The insights from this study lay the groundwork for future research and experimental validation, opening the door to more efficient and targeted strategies for identifying therapeutic lead molecules against glioblastoma.