Protein representation learning plays a crucial role in understanding the structure and
function of proteins, which are essential biomolecules involved in various biological …

The effects of ligand binding on protein structures and their in vivo functions carry numerous
implications for modern biomedical research and biotechnology development efforts such as …

Drug discovery pipelines nowadays rely on machine learning models to explore and
evaluate large chemical spaces. While including 3D structural information is considered …

Geometric graph is a special kind of graph with geometric features, which is vital to model
many scientific problems. Unlike generic graphs, geometric graphs often exhibit physical …

In recent years, there has been a surge in the development of 3D structure-based pre-
trained protein models, representing a significant advancement over pre-trained protein …

Accurate prediction of protein-ligand binding structures, a task known as molecular docking
is crucial for drug design but remains challenging. While deep learning has shown promise …

Drug-target interaction (DTI) prediction is a critical component of the drug discovery process.
In the drug development engineering field, predicting novel drug-target interactions is …