Welcome to Our Research Group
We are a dynamic research laboratory dedicated to advancing knowledge in computational chemistry, AI-driven drug discovery, and structure-based molecular design. Our research integrates computational chemistry, structure-based modeling, machine learning, and ultra-large-scale virtual screening to identify novel therapeutics and expand accessible chemical space for challenging biological targets
We aim to bridge fundamental computational methodology development with practical applications in medicinal chemistry and translational drug discovery.
Research Focus
- AI-Assisted Drug Discovery: Developing machine learning models and generative AI methods to efficiently explore target-specific chemical space and prioritize promising drug candidates.
- Structure-Based Virtual Screening & Molecular Design: Integrating docking, scoring, and combinatorial screening methods for ultra-large chemical libraries to enable rapid identification of novel bioactive compounds
- Computational Chemistry & Molecular Modeling: Applying molecular dynamics simulations, free energy prediction, and protein–ligand interaction analysis to understand molecular recognition and guide rational drug design.
News & Announcements
- May 2026: Lab website launched
- Recruiting motivated students and postdoctoral researchers interested in computational chemistry and AI-driven drug discovery
- Ongoing projects in virtual screening, generative modeling, and structure-based ligand discovery
Contact: yang.chao@suat-sz.edu.cn
Location: Faculty of Pharmaceutical Sciences, Shenzhen University of Advanced Technology (SUAT)