Protein engineering workflows
Design proteins fromsequence to folded structure.
Move from sequence or structure to folding, stability, variant scoring, binder design, and downstream validation without losing the files, tables, and confidence signals behind each result.
Result generated with RFdiffusion3
Capabilities
Protein design models
AlphaFold2
AlphaFold2 via ColabFold for high-accuracy protein structure prediction. Uses MMSeqs2 API for MSA generation with no local databases required. Supports monomer and multimer prediction.
Boltz-2
Boltz-2 is a biomolecular foundation model for structure and binding affinity prediction. Supports proteins, ligands, DNA, and RNA in multi-component complexes. Automatically scales GPU resources for large complexes. Predicts binding affinity with near-FEP accuracy at 1000x faster speed.
Chai-1
Chai-1 is a multi-modal foundation model for molecular structure prediction. Predicts 3D structures for proteins, ligands, DNA, RNA, and multi-component complexes with high accuracy.
ProteinMPNN
Design protein sequences for given backbone structures using deep learning. Fast and accurate inverse folding with state-of-the-art sequence recovery (52.4%).
RFdiffusion3
All-atom generative diffusion model for protein design with complex constraints. Design binders, enzymes, and symmetric protein assemblies.
ThermoMPNN
Predict protein thermostability changes (ΔΔG) for point mutations using a graph neural network. Enables computational saturation mutagenesis screening to identify stabilizing mutations.
Read to research?
Free
Per user/month, billed annually
For trying ProteinIQ
- 1,200 credits/year
- Daily lightweight analysis
- Core sequence and format tools
Lite
Per user/month, billed annually
For regular individual research
- 6,000 credits/year
- No daily job limit
- API, assistant, and workflows
Plus
Per user/month, billed annually
For high-throughput workflows
- 24,000 credits/year
- More concurrent jobs
- Batch workflow runs
Pro
Per user/month, billed annually
For commercial research
- 96,000 credits/year
- Commercial license
- Highest self-serve limits
Questions & answers
ProteinIQ supports protein engineering workflows for folding, structure prediction, protein design, variant scoring, stability review, solubility analysis, binder design, structure validation, and downstream candidate comparison. The platform keeps the upstream files, scores, confidence values, and logs available for review.
ProteinIQ protein tools can accept FASTA sequences, PDB or CIF structures, protein complexes, mutation lists, reference models, and design constraints depending on the upstream method. Each workflow preserves the relationship between the input sequence or structure and the outputs it generates.
Yes. ProteinIQ can run protein design tools that generate or redesign sequences from structural context, then route candidates into folding, stability, solubility, and validation checks. The generated variants are computational candidates for review and testing, not automatically validated proteins.
Yes. ProteinIQ can run protein structure prediction and folding tools when the sequence or structure inputs match the upstream model requirements. Outputs can include PDB or CIF files, confidence metrics, model artifacts, and logs so predicted structures can be inspected and exported.
Yes. ProteinIQ can connect protein candidates to stability, solubility, aggregation, mutation, and sequence-property tools depending on the workflow. These computational scores help prioritize variants, and ProteinIQ keeps the score tables tied to the sequence or structure being evaluated.
Yes. ProteinIQ can support binder design and protein interaction workflows when the required target structures, scaffold inputs, or design constraints are available. The platform helps keep designed sequences, predicted structures, confidence values, and downstream validation outputs together for review.
No. ProteinIQ helps prioritize protein engineering candidates computationally. Expression, binding, stability, activity, specificity, and functional assays remain essential before treating a designed or modified protein as experimentally validated.
Yes. ProteinIQ exports candidate evidence such as FASTA files, generated sequences, PDB or CIF structures, score tables, validation reports, confidence metrics, logs, and upstream result artifacts depending on the tool. This makes it easier to review or share the evidence outside ProteinIQ.
Start in ProteinIQ with a protein sequence, structure, or candidate variant set, then choose a workflow template or an individual tool for design, folding, stability, or validation. A small first run helps confirm formatting and output expectations before scaling to larger protein design campaigns.