Sebastian Pujalte Ojeda

OmniBind predicts small-molecule promiscuity across the human proteome using a neural network, enabling faster early-stage drug screening with improved specificity over affinity alone.

Metadiffusion introduces a meta-energy biasing layer to diffusion models to generate diverse biomolecular conformations without retraining, matching molecular dynamics simulations.

This paper introduces Ligand-Transformer, a deep learning framework for predicting protein-ligand interactions, and demonstrates its application in identifying inhibitors for specific targets and studying disordered proteins.