3 papers
cs.LG2026
APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries
Aryan Pedawi, Jordi Silvestre-Ryan, Bradley Worley +5
Make-on-demand combinatorial synthesis libraries (CSLs) like Enamine REAL have significantly enabled drug discovery efforts. However, their large size presents a challenge for virt…
cs.LG2025
Pearl: A Foundation Model for Placing Every Atom in the Right Location
Genesis Research Team, Alejandro Dobles, Nina Jovic +37
Accurately predicting the three-dimensional structures of protein-ligand complexes remains a fundamental challenge in computational drug discovery that limits the pace and success…
cs.LG2025
BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery
Peter St. John, Dejun Lin, Polina Binder +89
Artificial Intelligence models encoding biology and chemistry are opening new routes to high-throughput and high-quality in-silico drug development. However, their training increas…