All Competitors

Molecular ensemble foundation model for cyclic peptides, pooling per-conformer EGNN embeddings to predict membrane permeability from 3D structure.

Antigen-specific antibody design model that conditions an ESM3 backbone on epitope geometry, then aligns CDR generation with calibrated DPO.

De novo small molecule design for protein pockets, steering a discrete flow-matching generator with gradients from a frozen Boltz-2 affinity model.

Antibody CDR design model post-trained by on-policy distillation, cutting RAbD CDR-H3 backbone RMSD from 2.37 Å to 1.95 Å.

Protein language model for post-translational modifications, predicting PTM sites, types, and crosstalk across 40 modification classes.

Protein-ligand binding affinity prediction from sequence and SMILES, without MSAs. Coarse-grained cofolding runs over 10x faster than Boltz-2.

Protein conformational ensemble generator and coarse-grained force field in one normalizing flow. Samples faster than diffusion-based baselines.

B-cell receptor DNA language model pretrained on antibody heavy-chain nucleotide sequences, with embeddings that outperform protein language models.

Protein language model pretrained on structural domain segments, encoding fold and contact signals for remote-homology detection from sequence alone.

Protein function captioning model fusing sequence, Foldseek structure tokens, and text through a BLIP-2 Q-Former for open-ended free-text annotation.

Mixed-modality metagenomic language model using bidirectional Mamba blocks to embed proteins within 20K tokens of coding and non-coding DNA.

All-atom foundation model for macrocyclic peptide structure prediction, permeability estimation, and de novo design across non-canonical chemistries.

Variable-length generative protein design across structure, sequence, motif scaffolding, and peptide co-design via a generalized Poisson flow.

Generative language model that designs drug-like SMILES conditioned on disease ontology and a target protein sequence for de novo drug discovery.

All-atom foundation model for immune-receptor design that predicts structures and co-designs CDR sequences for antibodies, nanobodies, and TCRs.

Protease inhibitor prediction for small secreted proteins lacking an inhibitor domain, pairing protein language models with structure filtering.

Open-source all-atom co-folding foundation model for protein-ligand, protein-protein, and antibody-antigen complex prediction in drug discovery.

T-cell receptor-MHC restriction prediction from amino acid sequence, mapping TCRs to their restricting HLA allele at 0.97 held-out AUC.

Structure-based drug design language model fusing protein structural and evolutionary encoders with SAFE fragment tokens for hit-to-lead generation.

Heterograph foundation model for metabolic engineering, fusing protein, chemistry, and text embeddings over a 6.9M-node biological knowledge graph.

Atomic protein model building from cryo-EM density maps, resolving conformational heterogeneity through atom-centric sampling and diffusion.

Diffusion model for 3D small-molecule design against protein-protein interaction sites, guided by the natural binding peptide or protein partner.

Text-guided localization model that grounds natural-language functional descriptions to specific residue regions of a protein sequence.