At OpenBind, we’re working to generate large-scale, open experimental datasets of protein-ligand structures and binding measurements to support the development and evaluation of computational methods for drug discovery. One thing I’m particularly excited about is using these data not just for retrospective benchmarking, but for prospective, blind evaluation.
So, I’m very pleased that we’re launching the first OpenBind blind challenge on 14 October 2026, in partnership with OpenADMET and the ASAP Discovery Consortium. The interim submission deadline is 11 November, with final submissions due by 16 December 2026 at 23:59 UTC.
The challenge asks participants to predict protein-ligand complexes of 400 compounds bound to Zika virus NS2B-NS3 protease, ranging from small fragments to larger, lead-like molecules.
A key challenge will be using the structural information that already exists to accurately predict the binding modes of new, unseen ligands. There are already a number of publicly available structures of Zika NS2B-NS3 protease in the PDB that participants can use.
We’re also setting a high bar for success. While many protein-ligand benchmarks use an RMSD threshold of 2 Å, we’re tightening this to 1.5 Å, along with additional checks on interaction accuracy (lDDT-PLI > 0.8) and physical validity (PoseBusters validity checks). I’m particularly excited to see how docking, cofolding, and other approaches compare!
If you work on protein-ligand structure prediction, I’d strongly encourage you to join the challenge. You can find all the details, including how to register and join the challenge Discord, in the OpenBind announcement.