All Competitors

Protein dynamics model predicting per-residue probability of microsecond-millisecond conformational exchange from sequence or structure.

Protein conformational motion prediction from a single structure, using an SE(3)-equivariant GNN trained on ensembles mined from the PDB.

Predicts EC, GO, InterPro, Gene3D, keyword and cofactor terms from sequence, emitting database identifiers rather than free-text function guesses.

Cyclic peptide binder design by Monte Carlo tree search over sequence space, scored by predicted confidence of the peptide-target complex fold.

Binding affinity scoring for protein-ligand and lipid-protein pairs without a docked pose, used to rank the protein corona on candidate liposomes.

Cryo-EM density-map-to-atomic-structure modeling that fuses protein language model embeddings with density voxels, then refines with AlphaFold3.

Zero-shot pathogenicity scoring for in-frame insertions and deletions from protein language model likelihoods over residues both alleles share.

Protein conformational ensemble generator that samples heavy-atom structures in a latent space, with a variant conditioned on temperature.

Enzyme turnover number (kcat) prediction from sequence and substrate SMILES, scaling to genome-wide kinetic parameters for metabolic modeling.

Residue-level carbohydrate binding-site identification on protein structures, using equivariant graph convolutions over ESM2 per-residue embeddings.

Whole-protein carbohydrate-binding classification from structure, for proteome-scale screening with graph convolutions over ESM2 embeddings.

Protein inverse folding ensemble that fuses five pretrained sequence designers through a self-attention encoder, reaching 63.1% recovery on CATH4.2.

All-atom generative foundation model for biomolecular structure, unifying protein-ligand docking, structure-based drug design, and peptide design.

Protein sequence-structure encoder biasing attention with relative residue-frame transforms, for inverse folding and peptide binding prediction.

Matryoshka sparse autoencoders scaled to ESM2-3B, exposing the features that drive protein structure prediction and steering ESMFold outputs.

Protein language model that tokenizes sequence, backbone structure, and text into one vocabulary for function prediction, design, and fold editing.

Protein segmentation that locates folded domain, sub-domain, and disordered region boundaries from frozen ProtT5 embeddings without any training step.

Structure-based drug design framework that scores interaction-aware fragments against protein subpockets, then diffuses a 3D scaffold to link them.

Protein complex structure prediction system combining AlphaFold2 and AlphaFold3 with stoichiometry prediction, MSA engineering, and model ranking.

Protein-protein interaction language model that embeds whole sets of interacting chains through cross-chain attention, not one sequence at a time.

Protein-protein binding interface prediction from conformational ensembles, resolving interfaces in flexible and intrinsically disordered regions.

Generative foundation model that co-generates sequence and 3D coordinates for proteins, small molecules, and crystals under functional objectives.

Neurotoxicity prediction for short peptides and full-length neurotoxins, with separate ESM-2 models matched to each sequence length regime.