All Competitors

Polarizable machine-learning interatomic potential extending MACE with long-range electrostatics, trained on 100M OMol25 DFT calculations.

Diffusion model that generates continuous-time, all-atom biomolecular trajectories, reproducing conformational kinetics far more cheaply than MD.

Full-atom SE(3)-equivariant diffusion model that inpaints binding interfaces to design proteins that bind DNA, RNA, and small molecules.

Structure-based drug design model that unifies de novo generation, docking, conformer generation, and pharmacophore conditioning via flow matching.

Protein-ligand interaction predictor that types seven contact classes between residues and ligand functional groups from sequence and SMILES alone.

Protein binder design model post-trained from a multimodal protein language model to bind proteins, peptides, small molecules, and nucleic acids.

Structure-based drug discovery transformer that handles protein-ligand docking and pocket-aware 3D molecule design in one pretrained model.

Protein-ligand binding affinity prediction that fine-tunes ESM-2 and ChemBERTa-2 into a shared space where cosine similarity is the predicted pKd.