Humanized Framework
CDR Library Design
AI Affinity Scoring
Yeast Expression
ELISA + WB Validation
What Is a VHH Antibody?
VHH antibodies — also known as nanobodies or single-domain antibodies — are the variable domains of camelid heavy-chain-only immunoglobulins. At approximately 15 kDa, they are the smallest naturally occurring antigen-binding fragments, yet retain full binding specificity and affinity comparable to full IgG antibodies.
Their unique structure — a single immunoglobulin fold stabilised by a conserved disulfide bond and an extended, convex CDR3 loop — allows them to penetrate enzyme active sites, receptor pockets and cryptic epitopes that are entirely inaccessible to the flat paratopes of conventional IgG antibodies.
ICDMO's AI screening platform applies deep learning to explore the CDR sequence space of humanised VHH scaffolds at scale, identifying high-affinity binders in one week that would otherwise require months of library screening.
Antibody Format Comparison
Full IgGCannot reach cavity epitopes~150 kDa
FabLimited tissue penetration~50 kDa
scFvAggregation-prone linker~25 kDa
VHHDeep epitope access, stable~15 kDa
Size proportional to molecular weight
Key Characteristics of VHH Antibodies
1
Compact ~15 kDa Size
Smallest fully functional antibody fragment — accesses cryptic epitopes, enzyme active sites and receptor grooves sterically inaccessible to conventional IgG.
2
Thermal & Solvent Stability
Extraordinary resistance to high temperatures, detergents and extreme pH — retains activity under conditions that denature conventional antibodies.
3
Deep Tissue Penetration
Compact structure enables superior tumour penetration, blood-brain barrier crossing, and intracellular delivery for therapeutic applications.
4
Easy Engineering
Single domain simplifies formatting into bispecific, trispecific, CAR-T constructs, VHH-Fc fusions, and nanobody-drug conjugates.
5
Low Immunogenicity
Humanized frameworks with >90% sequence identity to human VH3 germline minimise immunogenic risk for therapeutic programmes.
6
Camelid Origin
Naturally occurring in llama, alpaca and camel IgG heavy-chain-only antibodies — diverse CDR3 loops enable unique binding modes.
AI Screening Platform
AI Workflow
1
CDR Mutagenesis
CDR1/2/3 regions undergo controlled random mutagenesis, generating a virtual library of millions of VHH sequence variants around the humanized framework scaffold.
2
Deep Learning Scoring
Proprietary deep learning models trained on thousands of VHH–antigen co-crystal structures predict binding affinity (ΔG), shape complementarity, and hydrogen-bond networks for every variant.
3
Top Candidate Selection
Ranked candidate list filters for top 200–500 predicted binders, applying additional filters for solubility, aggregation propensity, and expression compatibility in yeast secretion systems.
Model Architecture
Transformer + Graph Neural Network
Training Dataset
>50,000 VHH–antigen structures
Prediction Output
ΔΔG, shape complementarity, H-bonds
Five-Step Service Workflow
1
Humanized Framework Design
Natural VHH sequences are back-grafted onto human VH3 germline frameworks. CDR loops are preserved while all framework residues achieving ≥90% human identity — maintaining function while minimising immunogenicity risk.
2
CDR Random Mutagenesis
CDR1, CDR2 and CDR3 regions undergo controlled random mutagenesis, generating a virtual library spanning millions of sequence variants around each humanized scaffold.
3
AI Deep Learning Screening
Proprietary deep learning algorithms score every variant for predicted antigen-binding affinity, shape complementarity, and structural stability. Top-ranked sequences selected for synthesis.
4
Yeast Secretion Expression
Selected VHH candidates expressed using optimised Pichia pastoris or S. cerevisiae secretion systems. Secreted VHH purified by IMAC and confirmed by SDS-PAGE and SEC-HPLC.
5
ELISA & Western Blot Validation
Purified VHH antibodies validated by direct and competition ELISA (EC50, Kd estimation) and Western blot. Confirmed high-affinity binders delivered with full sequence data and validation report.
Applications
Therapeutic nanobodies against GPCRs, ion channels and enzyme targets
VHH-drug conjugates (NDC) for precise tumour targeting
Agonist / antagonist nanobodies for signalling pathway modulation
Bispecific and trispecific VHH-Fc therapeutic formats
Case Study Results
The following results were achieved across completed VHH AI screening projects. Each programme ran from sequence submission to confirmed validated binder in under two weeks.
Drug Discovery Target95% success
Hit identified in ≤1 week
GPCR Conformational VHH88% success
Active-state selective binder
Tumour Antigen Target92% success
Sub-nM Kd confirmed by SPR
Viral Surface Protein97% success
Neutralising nanobody identified
Platform Track Record
Projects Completed200+
Avg. Time to Hit<1 week
Validated Binders Delivered1,800+
Expression Success Rate99%+
Sub-nM Kd Rate>60%
Service Modules & Turnaround
Get a Custom Quote
Submit your target antigen and receive a project plan and quote within 24 hours.
Contact Us Online ConsultationStandard Deliverables
✓Humanized VHH sequence design report
✓AI-ranked candidate list + affinity scores
✓Purified protein (SDS-PAGE, SEC-HPLC)
✓ELISA binding data (EC50)
✓Western blot confirmation
✓Full project report (PDF)
Why ICDMO?
Proprietary AI trained on 50k+ structures
One-stop: design → expression → validation
99%+ yeast expression success rate
Results in as little as 1 week
24h response guarantee