TIGP (BIO)—Exploring Protein Conformations and Ligand Binding Using Molecular Dynamics and Machine Learning

Abstract

Molecular dynamics (MD) simulations are widely used to investigate the structural dynamics of biomolecules. However, efficiently sampling relevant conformational states and ligand binding poses remains challenging due to the large conformational space of proteins. In this seminar, I will briefly introduce the basic concept of MD simulations and discuss computational strategies to improve sampling efficiency. I will present our work on protein conformational sampling and protein–ligand docking, including Tree-Search MD for exploring protein conformational changes and Concentrated Ligand Docking (ColDock) for predicting protein–ligand binding structures.These studies illustrate how molecular simulations combined with machine learning–inspired strategies can help explore biologically relevant conformations and ligand binding modes.
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