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Built for scientific use cases

270+ published methods, running on GPUs with no setup. Every example is a real run you can open.

  1. Folding

    Predict protein structures and complexes with ligands, nucleic acids, and other proteins, with per-residue confidence for every model.

    • Boltz-2, Chai-1, and ESMFold
    • pLDDT, PAE, and ipTM for every model
    • Binding affinity for protein-ligand complexes
    Boltz-2 result for KRAS G12C and U4U, showing the predicted complex and five ranked predictions
  2. Docking

    Place small molecules in a binding site and rank the poses, from classical scoring to AI docking and protein-protein docking.

    • AutoDock Vina, Smina, and DiffDock-PP
    • Dock many ligands against one target
    • Validate poses with PoseBusters
    AutoDock Vina batch result for three inhibitors in c-Abl, showing poses from every ligand
  3. Protein design

    Design binders, antibodies, and new sequences for a target, then check each design with structure prediction.

    • BindCraft, RFdiffusion, and mBER
    • Binders, VHHs, and de novo backbones
    • ipTM and pLDDT on every design
    mBER result showing the relaxed PD-L1 and VHH complex with its confidence metrics
  4. Alignment

    Align sequences and structures, search databases for homologs, and build phylogenetic trees.

    • Clustal Omega and US-align
    • Homolog search with MMseqs2 and Foldseek
    • Phylogenetic trees with IQ-TREE
    Clustal Omega result showing the beta-globin alignment in the MSA viewer
  5. Validation

    Check structures and poses for geometry problems, clashes, and outliers before you rely on them.

    • MolProbity for experimental and predicted structures
    • PoseBusters for docked and co-folded poses
    MolProbity result showing the validation metrics table for ubiquitin 1UBQ

Used in published research

Peer-reviewed studies that ran their analysis on ProteinIQ.

Also mentioned by BiopharmaTrend, ParaSurf on GitHub, and HTGAA. Share your experience.

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