All Competitors

Protein melting temperature prediction from sequence, pairing frozen ESM2 embeddings with growth-temperature and thermophilicity features.

Refines AlphaFold2 predictions against cryo-EM, cryo-ET, and X-ray data by optimizing coevolutionary embeddings rather than atomic coordinates.

Flow matching model for de novo 3D peptide design that converges peptide position before conformation, mirroring the physical order of docking.

Protein-ligand affinity foundation model that embeds pockets and ligands in one space, unifying virtual screening with hit-to-lead optimization.

Broad-spectrum antiviral screening framework pairing a pretrained molecular encoder with ESM-2 embeddings for phenotype- and target-based prediction.

De novo protein backbone generator built on rectified quaternion flow matching, reaching 0.972 designability with far fewer sampling steps.

Protein language models evotuned on influenza A hemagglutinin, with a pLM entropy metric scoring per-site conservation from a single input sequence.

Protein conformational ensemble generator conditioned on backbone geometry alone, sampling MD-like dynamics without MSAs or a folding model.

Antibody-aware B-cell epitope prediction from a graph convolutional network over frozen antibody and antigen protein language model embeddings.

Fixed-backbone protein sequence design that co-generates amino acid identity and sidechain conformation, with 49.7% sequence recovery on CATH 4.2.

Protein function annotation that reshapes language model embeddings with a neural-collapse loss so rare EC, Pfam, and GO classes stay separable.

MSA-free structure prediction for TCR-peptide-MHC complexes, pairing a protein-protein-interaction language model with a flexible docking module.

Enzyme kcat and KM prediction from sequence and substrate SMILES, binned by order of magnitude so catalytic-site mutations shift the prediction.

Disordered protein ensemble prediction from sequence, generating hundreds of conformers in seconds via latent diffusion over distance maps.

Antibody chain pairing model that scores whether a heavy and a light chain are cognate partners, fine-tuned from an antibody-specific language model.

De novo protein sequence design conditioned on target vibrational dynamics, pairing a diffusion designer with a predictor that ranks candidates.

Antibody affinity maturation framework that steers flow-matching structure generation with a binding predictor, then mutates CDRs by inverse folding.

N-linked glycosylation site prediction stacking SVM, XGBoost, and KNN classifiers over ProtT5, ESM-2, and ProteinBERT sequence embeddings.

Absolute protein folding stability prediction that estimates ΔG by jointly modeling the folded and unfolded ensembles as residue-pair distograms.

Neural ODE model of protein network dynamics, pretrained on 38 million perturbed protein measurements for drug efficacy and synergy prediction.

Unified science foundation model treating molecules, proteins, RNA, DNA, and materials as one sequence language, in 1B, 8B, and 46.7B sizes.

Antibody and TCR CDR sequence design by structure retrieval, matching query loops against solved CDR structures rather than generating residues.

Multi-omics foundation model that folds DNA, RNA, and protein into one codon-level nucleotide representation following the central dogma.