Tools

Compare antibody sequence plausibility using AbLang2 scores.

Number antibody sequences and label framework and CDR regions using IMGT, Kabat, Chothia, or AHo.

Identify regions of predicted aggregation propensity in a protein structure.

Number antibody variable domains, assign V/J germlines, label FR/CDR regions, and locate sequence liabilities.

Predict short-peptide secondary structure in different solvents.

Humanize antibody sequences and compare their 9-mers with the OASis human antibody repertoire.

Generate biomolecular binder candidates conditioned on a target structure and design constraints.

Design and score protein sequences for a structure or conformational ensemble.

Measure contact molecular surface and shape complementarity across a protein–protein interface.

Compare model-predicted high-concentration viscosity risk for paired antibody heavy and light chains.

Estimate antibody PSR and SEC assay pass probabilities from VH, VL, and HCDR3 sequences.

Design protein sequences and structures around ligands, DNA, or RNA.

Compare a predicted complex with a reference structure using DockQ.

Generate mean-pooled protein embeddings with ESMC 300M or 600M.

Generate protein embeddings, fill masked sequences, and predict structures with ESMFold2.

Compare Fc residues with human IgG references and review candidate edits without changing the Fab.

Design protein binders from binder and target structure templates.

Generate a 40-residue protein backbone with fixed sampling settings.

Optimize protein sequences and structures with molecular and sequence constraints.

Predict HLA-II presentation probabilities and allele-specific 9-mer core scores.

Predict 3D structures of antibodies and nanobodies.

Score protein sequences with the DRB1 population immunogenicity risk model.

Score antibody variable regions and rank framework substitutions using human and mouse 8–12-mer references.

Score predicted binder interfaces using complex structures and matching predicted alignment error.

Find similar antibodies in PLAbDab patent and TheraSAbDab therapeutic references.

Generate peptide Cα conformations in MHC-I complexes.

Predict MHC-I binding affinity, antigen processing, and presentation for peptides and alleles.

Compare two CDR-based polyreactivity scores for nanobody variable domains.

Predict nanobody structures and review residue-level confidence for VHH candidates.

Predict all-atom complexes containing proteins, antibodies, nucleic acids, ligands, and ions.

Predict sequence aggregation propensity and locate candidate aggregation-prone regions.

Generate protein sequences and all-atom structures around a supplied ligand pose.

Design sequences for protein backbones, with optional ligand, nucleic-acid, metal, or cofactor context.

Predict target–binder complex structures and inspect confidence and predicted alignment error.

Design protein binders for up to four targets per run.

Design antibody and nanobody structures against a target antigen.

Generate one unconditional protein backbone of 20–50 residues.

Generate all-atom proteins, binders, and enzyme scaffolds with molecular constraints.

Generate structure-aware protein embeddings and mutation preference scores.

Repair PDB structures and calculate pairwise RMSD across a structure set.

Predict transformed affinity scores for HLA-A*02:01 9-mers, with optional unrefined structures.

Assess antibody developability features and screen CDR tryptophan exposure and electrostatics.