M. Bronstein

PLINDER: The protein-ligand interactions dataset and evaluation resource

PLINDER provides a large, annotated PLI dataset with diverse annotations and improved evaluation splits to better assess computational methods for drug design.

Targeting protein-ligand neosurfaces using a generalizable deep learning approach

This paper designs proteins that target neosurfaces from protein-ligand complexes using a deep learning approach, validated experimentally against three drug-bound protein complexes.

A 3D Clinical Face Phenotype Space of Genetic Syndromes using a Triplet-Based Singular Geometric Autoencoder

This paper develops a triplet-based geometric autoencoder to create a clinical face phenotypic space for syndrome diagnosis, showing it can classify syndromes, generalize to new ones, and preserve genetic disease relationships.

De novo design of site-specific protein interactions with learned surface fingerprints

This paper designs novel protein interactions using geometric deep learning to generate surface fingerprints, achieving nanomolar affinity for four targets through computational and experimental methods.

Human nasal and lung tissues infected ex vivo with SARS-CoV-2 provide insights into differential tissue-specific and virus-specific innate immune responses in the upper and lower respiratory tract

This study compares SARS-CoV-2 and influenza virus infection in human nasal and lung tissues, revealing distinct innate immune responses in the upper and lower respiratory tract.