ProteinIQ for protein design
Design protein sequences with AI
Generate optimized protein sequences and novel binders using LigandMPNN, ProteinMPNN, SolubleMPNN, BoltzGen, and RFdiffusion—state-of-the-art deep learning and diffusion models.
Join 1,200+ researchers using ProteinIQ
01 — Challenges
Challenges we solve
Common obstacles researchers face and how ProteinIQ addresses them.
Design sequences for protein backbone structures
Generate novel protein and peptide binders against any target
Create de novo protein structures with atomic precision
Optimize binding sites with ligand and metal context
02 — Workflow
How it works
A streamlined workflow from input to results.
1
Upload Structure
Provide target backbone or binding target PDB
2
Configure Design
Set residue constraints, chain specifications
3
Generate Sequences
ProteinMPNN or LigandMPNN designs optimized sequences
4
Validate & Order
Check predictions and export for synthesis
03 — Comparison
Traditional methods vs. ProteinIQ
See how we compare to traditional computational approaches.
| Aspect | Traditional | ProteinIQ |
|---|---|---|
| Design approach | Months of directed evolution | AI-guided design in minutes |
| Success rate | Low hit rate from random mutagenesis | High sequence recovery (>50%) |
| Binder design | Phage display campaigns ($100K+) | Generative AI binder design |
| Iteration speed | Weeks per design cycle | Generate hundreds of variants instantly |
04 — Explore more
Related solutions
Discover complementary workflows to enhance your research.