AlphaFold2 and open-source alternatives have commoditized single-chain prediction. But a raw model is not a decision-ready structure. We answer the real question: Is this model reliable for docking, MD, or drug design? Our protein modeling service focuses on model quality assessment, refinement of hard targets (GPCRs, membrane proteins, loops, non-natural modifications), and integration into structure-based discovery workflows — so you don't waste cycles on a misleading fold.
We benchmark your model against expected geometry, PAE/pLDDT confidence, and known experimental constraints. You get a clear fit-for-purpose verdict.
Missing loops, clashes, or wrong rotamers? We rebuild and refine using MODELLER, Rosetta, or MD-based relaxation to produce a physically realistic model.
We specialize in receptors, channels, and transporters — targets where AlphaFold3 still struggles with conformational states and ligand-ready pockets.
We incorporate crosslinking, HDX, or mutagenesis data to steer modeling and validate the final ensemble.
We deliver models with protonation states, missing hydrogens, and force-field-consistent geometry — ready for your simulation pipeline.
When multiple models exist, we compare and rank them using consensus metrics and downstream test cases.
We run state-of-the-art predictors, then rigorously assess model quality with orthogonal metrics.
When templates exist but are remote, we use MODELLER, SWISS-MODEL, and threading to build reliable models.
We relax models in explicit solvent to remove clashes and capture conformational flexibility for downstream use.
We discuss your downstream goal — docking, MD, epitope mapping, or publication — and define what “good enough” means for your target.
We run AlphaFold2 or homology modeling based on target difficulty, then assess initial model quality.
PAE, pLDDT, MolProbity, Ramachandran, and active-site geometry checks. We identify unreliable regions.
Loop rebuilding, side-chain repacking, and MD-based relaxation for hard targets (GPCRs, membrane proteins, antibodies).
We cross-check with mutagenesis, crosslinking, or HDX data. When no data exists, we use ensemble consistency and energy metrics.
Final models with validation metrics, confidence maps, and recommendations for downstream use (docking, MD, or experimental design).
We prepare the structure for docking or MD — protonation, force field parameters, and binding-site analysis.
| Challenge | Computational approach | Key deliverables | Wet-lab validation (optional) |
|---|---|---|---|
| Is my AlphaFold model good enough for docking? | PAE/pLDDT audit + active-site geometry + docking test | Fit-for-purpose report, confidence map | SPR / ITC (binding validation) |
| GPCR or membrane protein with low homology | Homology modeling + MD refinement + ensemble generation | Refined model, conformational ensemble | HDX / crosslinking |
| Missing loops or non-natural residues | Loop modeling, Rosetta design, MD relaxation | Repaired structure, energy scores | Circular dichroism |
| Need a structure for publication | Multi-method validation + experimental cross-check | Publication-ready figures, methods | Mutagenesis validation |
We are not a prediction shop. We are a structure intelligence partner that helps you decide when a model is reliable, when it needs refinement, and how to use it for downstream discovery.
Yes — and for many easy targets, that's sufficient. But raw predictions often have unreliable loops, wrong side-chain rotamers, or poor active-site geometry. If you need the structure for docking, MD, or publication, validation and refinement are essential. We provide that layer.
We use orthogonal metrics: PAE/pLDDT confidence, MolProbity stereochemistry, Ramachandran analysis, active-site geometry, and ensemble consistency from MD. When experimental data exists (mutagenesis, crosslinking), we incorporate it as restraints.
GPCRs, membrane proteins, targets with missing loops, non-natural modifications, and low-homology sequences. AlphaFold3 has improved but still struggles with conformational states, ligand-ready pockets, and multi-domain assemblies.
Yes. We deliver structures with correct protonation, missing hydrogens added, and force-field-consistent geometry — ready for AMBER, GROMACS, or docking pipelines. We also offer downstream integration.
A standard model audit and refinement takes 1–2 weeks. Hard targets with extensive loop rebuilding or MD refinement may take 3–4 weeks. Please contact us with your target details.
Share your sequence and downstream goal. We'll tell you if your current model is good enough — and if not, we'll refine it until it is.
Submit Project DetailsSubmit your project details below, and our team will respond within 24 hours.
Talk to our technical team about your project!
I Want To Talk
