HomeServicesCompound & Biological Library DesignAntibody Library Design (Synthetic / Semi-Synthetic)
Ref N3
Computational Service
Confidence Reported
Scoped After Feasibility Review
Service Overview
A display library succeeds or fails on its design. Diversity placed where it cannot contribute is wasted, frameworks that fold and express poorly lose a large share of the library before selection starts, and unconstrained randomisation introduces stop codons, glycosylation motifs and chemical liabilities that propagate into every downstream hit. We design synthetic and semi-synthetic antibody libraries with diversity positioned structurally, codon schemes chosen deliberately, and the theoretical diversity checked against what your construction process can actually realise.
Key Features & Advantages
Diversity Positioned Structurally
Randomised positions are chosen from paratope structural analysis and from natural repertoire statistics, so diversity lands where it can influence binding.
Repertoire-Informed Amino Acid Usage
Position-specific amino acid distributions follow observed antibody repertoires rather than uniform randomisation, which improves both folding and the proportion of functional clones.
Liabilities Excluded At The Codon Level
Codon schemes are designed to avoid stop codons, unpaired cysteines, glycosylation sequons and known chemical liability motifs before the library is built.
Realisable Diversity Assessed
Theoretical diversity is compared with the transformation efficiency you can achieve, so the design matches the library you will actually obtain.
Where This Service Is Used
1Designing a synthetic naive library for phage or yeast display
2Building a semi-synthetic library on a validated framework scaffold
3Designing affinity maturation libraries focused on a specific lead
4Creating epitope-biased libraries when the target surface is known
5Designing VHH or single-domain libraries with format-appropriate diversity
Methods and Techniques Applied
1Framework selection based on expression, stability, display compatibility and germline usage
2Paratope structural analysis to identify positions that contribute to binding
3Natural repertoire analysis for position-specific length and amino acid distributions
4Codon scheme design using degenerate codons or trinucleotide mixtures as appropriate
5In silico library generation with diversity, liability and folding quality assessment
6Epitope biasing through structure-guided diversity placement where the target site is known
What We Need From You
1The display platform and its practical diversity ceiling
2Framework preferences, or existing scaffolds your group has validated
3Target information if the library is to be biased toward a known epitope
4Construction method available: degenerate oligonucleotides, trinucleotide synthesis or gene synthesis
What You Receive
1Complete library design with position-by-position diversity specification
2Codon schemes and oligonucleotide designs ready for synthesis
3Theoretical diversity calculation with liability and quality assessment
4In silico library sample with predicted folding and developability statistics
5Construction notes and recommended quality control checkpoints
What We Compute and Report
1Theoretical diversity and realisable diversity at your construction efficiency
2Position-by-position amino acid distribution compared against natural repertoire statistics
3Predicted proportion of in-frame, liability-free, foldable clones
4Codon scheme composition with stop codon and liability motif frequencies
5In silico library sample with developability statistics across simulated members
Questions We Are Asked Before Scoping
How large should the library be?
▸Naive libraries generally need very high diversity to yield good binders directly; focused maturation libraries work well at far smaller sizes. The practical ceiling is usually your transformation efficiency, not the design.
Does library design guarantee binders?
▸No. It improves the fraction of functional, developable clones and positions diversity where it can matter. Selection outcomes still depend on the antigen, the panning strategy and the construction quality.
Do you build the library?
▸No. We deliver the design and oligonucleotide specifications; construction and selection are performed by your team or a partner, and we help interpret the sequencing results.
Interpretation and Limitations
Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.
Is This the Right Service for You?
Choose this when
A synthetic or semi-synthetic display library is being built in house
Diversity should be placed where it can influence binding rather than spread evenly
A maturation library is needed around a confirmed lead
Consider another service when
Specific variants should be made instead of a library
CDR Affinity Maturation The library is peptide rather than antibody
Peptide Library Design What Goes Wrong, and How We Handle It
These are the failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.
Theoretical diversity quoted while transformation efficiency limits reality
Realisable diversity at your construction efficiency is computed alongside the theoretical figure.
Randomisation introducing stop codons and liability motifs
Codon schemes are designed to avoid stops, unpaired cysteines and glycosylation sequons before construction.
Uniform randomisation producing poorly folding clones
Position-specific amino acid distributions follow observed repertoires, which raises the functional fraction substantially.
A Worked Example
Designing diversity that survives construction
The situation
A previous in-house library had high theoretical diversity and a low fraction of functional clones.
What the work involved
The paratope was analysed structurally, repertoire statistics were used for position-specific composition, codon schemes were redesigned, and an in silico sample was generated and screened for folding and liabilities.
What came back
Predicted functional fraction improved substantially in the in silico sample, with stop-codon frequency eliminated by the codon scheme and realisable diversity stated against the team’s measured transformation efficiency.
Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.
Service Workflow
1
Scientific Consultation
We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.
2
Feasibility Review
We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.
3
Technical Proposal
Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.
4
Computation and QC
The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.
5
Report and Follow-Up
You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.
Service Process
1
Online Consultation
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2
Solution Matching
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3
Service Contract
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4
Project Execution
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5
Data Delivery
Specifications & Turnaround
Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.
Get a Custom Quote
Our scientific team responds within 24 hours with a detailed technical proposal and pricing tailored to your project.
Contact Us Online ConsultationStandard Deliverables
✓Sequence-verified final product
✓Full QC documentation
✓Certificate of Analysis (CoA)
✓Electronic data files
✓Project completion report
Why ICDMO?
Computational CDMO Focus
Reproducible, Versioned Pipelines
Confidence & Limitations Reported
Experiment-Aware Recommendations
Response Within One Business Day