Hilbert Yuen In Lam

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 shows that protein language models can achieve screening performance similar to structure-based methods without requiring 3D protein structures.

The paper challenges the classical cisternal progression model by showing that intra-Golgi transport velocity varies and Golgi residence times differ for different cargos, suggesting a stable compartment model.

The paper introduces a generalist model for drug design that predicts multiple properties simultaneously, achieving faster virtual screening and drug development with explainability.

This study identifies FDA-approved drugs that may repurpose to treat monkeypox by predicting their binding to viral proteins critical for replication.