Best-Fit Scenarios
VHH molecules need improved humanness
You need to reduce immunogenicity risk while preserving activity and stability as much as possible
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Leveraging AI high-precision structure prediction and stepwise back-mutation design, comprehensively evaluating key residues at the structural level, maximizing affinity retention while improving humanization — more precise sequences, lower experimental costs, and shorter development cycles.
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 strategy makes it difficult to find the most structurally compatible Germline for VHH in human libraries; candidate framework scope is limited.
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 structure prediction models to generate high-precision 3D structures for VHH sequences, enabling intuitive understanding of CDR loop conformations and framework support relationships.
Intelligently screens suitable candidate frameworks from human Germline for VHH CDR, with focused optimization of VHH-specific residues, DE Loop, and key structural sites.
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 parental.
Most humanized sequences showed expression levels comparable to the parental, 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
Based on the core principle of "precise design, minimize trial and error", leveraging an AI structural biology expert system for closed-loop optimization.
VHH sequence submission → Structure prediction → Intelligent framework matching → Progressive back-mutations → Multi-dimensional scoring → Sequence recommendation & risk annotation
Report
Below are excerpts from the nanobody humanization service delivery report, showing the complete workflow from VHH sequence analysis to humanization mutation strategies.
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.
The advantage is reducing candidate space through structure and multi-dimensional scoring before expression, avoiding large blind panels. In the page case, only a small number of VHH sequences were recommended, yet multiple candidates showed improved humanness and affinity performance.
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.