AI-Driven Computational Modeling for Structural Biology and Protein Engineering

Dr. Xing Liu is a Postdoctoral Researcher in the College of Engineering at Northeastern University. Liu’s research lies at the intersection of artificial intelligence, computational structural biology, and biomolecular engineering, with a particular focus on developing machine-learning methods for understanding and engineering proteins and molecular interactions.

Current research includes AI-based modeling of antibody–antigen interactions, protein–protein interfaces, flexible molecular docking, and protein and enzyme engineering. Liu develops deep-learning approaches that integrate protein sequence, structural information, molecular representations, and graph-based modeling to improve the prediction of biomolecular structure, function, interactions, and stability. A major emphasis of this work is the development of interpretable and structure-aware AI methods that can provide biologically meaningful predictions and support experimental design. Liu’s broader research interests include protein language models, geometric deep learning, molecular dynamics, multimodal biological modeling, and AI-guided biomolecular design.

The overall goal of this research is to bridge advances in artificial intelligence with practical challenges in structural biology and protein engineering, enabling more efficient computational screening, mechanistic understanding, and rational design of biomolecular systems.