Protein structure prediction
Model monomers, multimers, protein-ligand complexes, nucleic-acid assemblies, and modified biomolecules with modern folding and co-folding methods.
Trusted by researchers at leading biotech, pharmaceutical, academic, and materials organizations
Sequence to structural hypothesis
Represent every relevant chain, ligand, nucleotide, ion, or modification, then interpret confidence at the residue, domain, and interface levels.
Define chains, stoichiometry, ligands, nucleic acids, modifications, and any experimentally justified restraints before prediction.
Compare modern co-folding, diffusion, and protein-language-model approaches where uncertainty or system complexity warrants it.
Inspect local confidence, aligned error, interfaces, clashes, and agreement across models before using a structure downstream.
Designed around the research
Available now
Model the relevant molecular context and interpret local and interface confidence rather than treating one global score as validation.
Predict proteins and mixed biomolecular complexes.
Run AlphaFold3-style co-folding workflows.
Model all-atom biomolecular systems.
Predict all-atom structures and complexes.
Generate fast protein and complex predictions.
Evaluate predicted structure plausibility.
From the Neurosnap blog
Co-folding guide
Learn how to represent proteins, nucleic acids, ligands, ions, and modifications in one prediction.
Read articleStructure guide
Review input construction, model confidence, and practical interpretation for mixed biomolecular systems.
Read articleSecurity & privacy
Submitted data and generated results remain confidential, with ownership retained by your team.
Only you and authorized colleagues can access submitted data and results.
Your results and intellectual property remain yours. No royalties or equity.
Platform controls help protect sensitive computational research.
Onboarding and integration support help organizations scale confidently.
Model the right system
Predict complete molecular systems, inspect uncertainty, and carry trustworthy structures into design, docking, or simulation.
