🧪 Biomolecule–Synthetic Material Interactions

We simulate DNA/material interfaces using MD and extract meaningful collective variables using statistical learning. This uncovers how recognition and binding occur at the molecular level.

🔬 Protein–Small Molecule Binding & Conformational Dynamics

High-dimensional time-series from MD is reduced to low-dimensional reaction coordinates, helping us map conformational transitions critical to protein function.

🧠 Sequence-Based Property Prediction Using Language Models

We treat protein/ligand sequences like language and use transformer-based models to predict properties such as binding affinity without relying on 3D structure.

🧩 Dynamics-Informed Residue-Level Insights

We analyze residue-level dynamics to classify conformational switching events as stable or unstable—advancing our understanding of function and disorder in proteins.