ApexSuite
Led by our core foundational model APEX, our specialized suite of AI engines is revolutionizing antibiotic discovery and biological computation.
Models
APEX
Antimicrobial prediction
Our activity predictor reads whole proteomes and finds the encrypted peptides that act as antibiotics.
ApexImmuno
Anti-inflammatory prediction
Generates peptides scored for both antimicrobial potency and immune modulation.
ApexFold
Secondary structure prediction
Predicts how a peptide folds in the environment it will actually meet, water, membrane or organic solvent, and scores how much its structure shifts between them.
ApexCPP
Cell penetration prediction
Predicts cell-penetrating activity across biological membranes to guide intracellular peptide delivery.
ApexHemo
Hemolysis prediction
Evaluates hemolytic activity against red blood cells to screen for non-toxic peptide candidates.
ApexTox
Cytolysis prediction
Predicts mammalian cytotoxicity and cytolytic activity to prioritize safe therapeutic sequences.
Applications
ApexGPT
Sequence generation from a target profile
A generative language model that writes new peptides from a target profile.
ApexGO
Template-guided optimization
Optimizes a known peptide instead of starting over, searching a generative latent space under a similarity constraint.
ApexOracle
Antibiotics for pathogens never seen
Pairs a molecular diffusion model with genome and literature profiles of each strain, predicting activity and generating new molecules for pathogens it has never seen.
ApexDuo
Dual-function peptide design
Designs peptides that enter mammalian cells and kill the bacteria hiding inside them.
Amphion
Reward-guided peptide design
Fine-tunes a 6.4-billion-parameter protein language model with reinforcement learning against predicted MIC.
AMPSpace
Design for druggability
Makes druggability a design goal, one loop generates, recognizes and ranks peptides for potency, safety, stability and structure at once.
Key-Cutting Machine
Sequences cut to fit a fold
Cuts sequences to fit a target backbone, optimizing shape, energy and residue properties with no retraining.
Other Models
panCleave
Protease cleavage site prediction
Trained on MEROPS, it predicts where proteases cut a sequence.
OmegAMP
Conditional diffusion, three ways to design
Designs peptides de novo, as analogs of a known lead, or around a required motif.
Termini
Terminal modifications chemistry by design
Designs antimicrobial and safe peptides together with their terminal chemistry, N-terminal acetylation and C-terminal amidation.
Collaborate with the APEX AI ecosystem
Interested in deploying our APEX suite to your institution's pathogen research or benchmarking clinical screening pipelines?