|
This project aims to advance in silico drug discovery using state-of-the-art artificial intelligence (AI) models. The work involves four key components. First, we will develop an accurate and scalable docking model to describe protein–drug binding. Second, an autoregressive model capable of generating molecular structures with 3D atomic precision will be integrated with the docking model. Third, large-scale training will be carried out using publicly available protein–drug docking data and refined with experimental results. Finally, potential drug candidates will be generated and evaluated through high-throughput virtual screening (HTVS). This project is conducted in collaboration with experimental groups, who will synthesize and test the most promising compounds in vivo. Through this work, students will gain hands-on experience in a complete AI-driven drug discovery workflow and develop practical skills in AI and machine learning (ML).
|
Sign in
to view more information about this project.
