Best-Fit Scenarios
VHH molecules need improved humanness
You need to reduce immunogenicity risk while preserving activity and stability as much as possible
We use cookies to enhance your browsing experience and analyze site traffic. By continuing to use this site, you agree to our cookie policy. Privacy Policy
Leveraging AI-based structure prediction and stepwise back-mutation design evaluate the structural roles of key residues, helping preserve affinity while increasing humanness — yielding a smaller, better-prioritized candidate set, lower experimental cost, and a shorter development timeline.
Validated Results
Why Is This Needed?
"VHH antibodies originate from camelid animals. Their heterologous protein characteristics may trigger the human immune system, producing anti-drug antibodies (ADA), leading to drug efficacy loss or adverse reactions. Humanization is a critical step to reduce immunogenicity risk and advance nanobody drug development."
Key Advantages
Traditional CDR grafting makes it difficult to identify human germline frameworks that are structurally compatible with a VHH, limiting the available framework options.
Grafting often leads to significant activity decline or loss; back-mutations rely on trial and error with uncertain success rates.
Extensive expression, purification, and screening are time-consuming; discovering immunogenicity issues at the clinical stage causes project delays or failure.
Uses advanced AI models to predict 3D structures of VHH sequences, revealing CDR-loop conformations and framework interactions.
Screens human germline frameworks for compatibility with VHH CDRs, then optimizes VHH-specific residues, the DE loop, and other key structural positions.
Progressively optimizes back-mutations around framework-CDR interfaces, Vernier zones, and core structural residues, balancing functional retention with high humanness.
Only a few candidate molecules need testing to find high-performing humanized VHH; all design is completed through the online platform with no offline communication needed.
Validation
Parental_VHH (affinity 16nM, CDR3 15aa). Using the Click.mAb. platform, only 7 recommended sequences yielded multiple molecules outperforming the parent antibody.
Most humanized sequences showed expression levels comparable to the parent antibody, with minor decreases still within acceptable range. CE-SDS analysis showed main peak purity above 90% with low aggregate content, indicating humanization did not significantly affect expression or basic physicochemical properties.
Pipeline
An AI structural-biology system guides each optimization step, reducing trial and error through structure-informed design.
VHH sequence submission → Structure prediction → Intelligent framework matching → Progressive back-mutations → Multidimensional scoring → Sequence recommendation & risk annotation
Report
The excerpts below are from a nanobody humanization report and cover the workflow from VHH sequence analysis to selection of humanizing mutations.
Use Cases
Best suited for improving VHH before downstream development.
VHH is a single-domain structure where FWR2, the DE Loop, long CDR3, and framework hydrophilicity affect solubility, stability, and antigen binding. The platform performs VHH-specific framework screening and site optimization instead of copying mAb CDR grafting.
Structure prediction helps evaluate CDR loop conformation, framework support, and key residue positions. Humanization is therefore not just sequence replacement, but candidate selection around structural stability and functional retention.
The platform progressively evaluates back-mutations around framework-CDR interfaces, Vernier regions, core structural residues, and VHH-specific positions, helping balance high humanness with activity retention more reliably.
Structural analysis and multidimensional scoring narrow the candidate pool before expression, reducing the need to test large, unguided panels. In the case shown here, a small set of recommended VHH sequences yielded multiple candidates with better humanness and affinity.
No extensive expert experience needed — just upload VHH sequences and the system will complete the fully automated design from structure prediction to optimal mutation strategies.