tools-only Experiment Types and Workflows
Overview
Adaptyv provides multiple experimental assay types for comprehensive protein characterization. Each experiment type has specific applications, workflows, and data outputs.
Binding Assays
Description
Measure protein-target interactions using biolayer interferometry (BLI), a label-free technique that monitors biomolecular binding in real-time.
Use Cases
- Antibody-antigen binding characterization
- Receptor-ligand interaction analysis
- Protein-protein interaction studies
- Affinity maturation screening
- Epitope binning experiments
Technology: Biolayer Interferometry (BLI)
BLI measures the interference pattern of reflected light from two surfaces:
- Reference layer - Biosensor tip surface
- Biological layer - Accumulated bound molecules
As molecules bind, the optical thickness increases, causing a wavelength shift proportional to binding.
Advantages:
- Label-free detection
- Real-time kinetics
- High-throughput compatible
- Works in crude samples
- Minimal sample consumption
Measured Parameters
Kinetic constants:
- KD - Equilibrium dissociation constant (binding affinity)
- kon - Association rate constant (binding speed)
- koff - Dissociation rate constant (unbinding speed)
Typical ranges:
- Strong binders: KD < 1 nM
- Moderate binders: KD = 1-100 nM
- Weak binders: KD > 100 nM
Workflow
- Sequence submission - Provide protein sequences in FASTA format
- Expression - Proteins expressed in appropriate host system
- Purification - Automated purification protocols
- BLI assay - Real-time binding measurements against specified targets
- Analysis - Kinetic curve fitting and quality assessment
- Results delivery - Binding parameters with confidence metrics
Sample Requirements
- Protein sequence (standard amino acid codes)
- Target specification (from catalog or custom request)
- Buffer conditions (standard or custom)
- Expected concentration range (optional, improves assay design)
Results Format
{
"sequence_id": "antibody_variant_1",
"target": "Human PD-L1",
"measurements": {
"kd": 2.5e-9,
"kd_error": 0.3e-9,
"kon": 1.8e5,
"kon_error": 0.2e5,
"koff": 4.5e-4,
"koff_error": 0.5e-4
},
"quality_metrics": {
"confidence": "high|medium|low",
"r_squared": 0.97,
"chi_squared": 0.02,
"flags": []
},
"raw_data_url": "https://..."
}
Expression Testing
Description
Quantify protein expression levels in various host systems to assess producibility and optimize sequences for manufacturing.
Use Cases
- Screening variants for high expression
- Optimizing codon usage
- Identifying expression bottlenecks
- Selecting candidates for scale-up
- Comparing expression systems
Host Systems
Available expression platforms:
- E. coli - Rapid, cost-effective, prokaryotic system
- Mammalian cells - Native post-translational modifications
- Yeast - Eukaryotic system with simpler growth requirements
- Insect cells - Alternative eukaryotic platform
Measured Parameters
- Total protein yield (mg/L culture)
- Soluble fraction (percentage)
- Purity (after initial purification)
- Expression time course (optional)
Workflow
- Sequence submission - Provide protein sequences
- Construct generation - Cloning into expression vectors
- Expression - Culture in specified host system
- Quantification - Protein measurement via multiple methods
- Analysis - Expression level comparison and ranking
- Results delivery - Yield data and recommendations
Results Format
{
"sequence_id": "variant_1",
"host_system": "E. coli",
"measurements": {
"total_yield_mg_per_l": 25.5,
"soluble_fraction_percent": 78,
"purity_percent": 92
},
"ranking": {
"percentile": 85,
"notes": "High expression, good solubility"
}
}
Thermostability Testing
Description
Measure protein thermal stability to assess structural integrity, predict shelf-life, and identify stabilizing mutations.
Use Cases
- Selecting thermally stable variants
- Formulation development
- Shelf-life prediction
- Stability-driven protein engineering
- Quality control screening
Measurement Techniques
Differential Scanning Fluorimetry (DSF):
- Monitors protein unfolding via fluorescent dye binding
- Determines melting temperature (Tm)
- High-throughput capable
Circular Dichroism (CD):
- Secondary structure analysis
- Thermal unfolding curves
- Reversibility assessment
Measured Parameters
- Tm - Melting temperature (midpoint of unfolding)
- ΔH - Enthalpy of unfolding
- Aggregation temperature (Tagg)
- Reversibility - Refolding after heating
Workflow
- Sequence submission - Provide protein sequences
- Expression and purification - Standard protocols
- Thermostability assay - Temperature gradient analysis
- Data analysis - Curve fitting and parameter extraction
- Results delivery - Stability metrics with ranking
Results Format
{
"sequence_id": "variant_1",
"measurements": {
"tm_celsius": 68.5,
"tm_error": 0.5,
"tagg_celsius": 72.0,
"reversibility_percent": 85
},
"quality_metrics": {
"curve_quality": "excellent",
"cooperativity": "two-state"
}
}
Enzyme Activity Assays
Description
Measure enzymatic function including substrate turnover, catalytic efficiency, and inhibitor sensitivity.
Use Cases
- Screening enzyme variants for improved activity
- Substrate specificity profiling
- Inhibitor testing
- pH and temperature optimization
- Mechanistic studies
Assay Types
Continuous assays:
- Chromogenic substrates
- Fluorogenic substrates
- Real-time monitoring
Endpoint assays:
- HPLC quantification
- Mass spectrometry
- Colorimetric detection
Measured Parameters
Kinetic parameters:
- kcat - Turnover number (catalytic rate constant)
- KM - Michaelis constant (substrate affinity)
- kcat/KM - Catalytic efficiency
- IC50 - Inhibitor concentration for 50% inhibition
Activity metrics:
- Specific activity (units/mg protein)
- Relative activity vs. reference
- Substrate specificity profile
Workflow
- Sequence submission - Provide enzyme sequences
- Expression and purification - Optimized for activity retention
- Activity assay - Substrate turnover measurements
- Kinetic analysis - Michaelis-Menten fitting
- Results delivery - Kinetic parameters and rankings
Results Format
{
"sequence_id": "enzyme_variant_1",
"substrate": "substrate_name",
"measurements": {
"kcat_per_second": 125,
"km_micromolar": 45,
"kcat_km": 2.8,
"specific_activity": 180
},
"quality_metrics": {
"confidence": "high",
"r_squared": 0.99
},
"ranking": {
"relative_activity": 1.8,
"improvement_vs_wildtype": "80%"
}
}
Experiment Design Best Practices
Sequence Submission
- Use clear identifiers - Name sequences descriptively
- Include controls - Submit wild-type or reference sequences
- Batch similar variants - Group related sequences in single submission
- Validate sequences - Check for errors before submission
Sample Size
- Pilot studies - 5-10 sequences to test feasibility
- Library screening - 50-500 sequences for variant exploration
- Focused optimization - 10-50 sequences for fine-tuning
- Large-scale campaigns - 500+ sequences for ML-driven design
Quality Control
Adaptyv includes automated QC steps:
- Expression verification before assay
- Replicate measurements for reliability
- Positive/negative controls in each batch
- Statistical validation of results
Timeline Expectations
Standard turnaround: ~21 days from submission to results
Timeline breakdown:
- Construct generation: 3-5 days
- Expression: 5-7 days
- Purification: 2-3 days
- Assay execution: 3-5 days
- Analysis and QC: 2-3 days
Factors affecting timeline:
- Custom targets (add 1-2 weeks)
- Novel assay development (add 2-4 weeks)
- Large batch sizes (may add 1 week)
Cost Optimization
- Batch submissions - Lower per-sequence cost
- Standard targets - Catalog antigens are faster/cheaper
- Standard conditions - Custom buffers add cost
- Computational pre-filtering - Submit only promising candidates
Combining Experiment Types
For comprehensive protein characterization, combine multiple assays:
Therapeutic antibody development:
- Binding assay → Identify high-affinity binders
- Expression testing → Select manufacturable candidates
- Thermostability → Ensure formulation stability
Enzyme engineering:
- Activity assay → Screen for improved catalysis
- Expression testing → Ensure producibility
- Thermostability → Validate industrial robustness
Sequential vs. Parallel:
- Sequential - Use results from early assays to filter candidates
- Parallel - Run all assays simultaneously for faster results
Data Integration
Results integrate with computational workflows:
- Download raw data via API
- Parse results into standardized format
- Feed into ML models for next-round design
- Track experiments with metadata tags
- Visualize trends across design iterations
Support and Troubleshooting
Common issues:
- Low expression → Consider sequence optimization (see protein_optimization.md)
- Poor binding → Verify target specification and expected range
- Variable results → Check sequence quality and controls
- Incomplete data → Contact support with experiment ID
Getting help:
- Email: support@adaptyvbio.com
- Include experiment ID and specific question
- Provide context (design goals, expected results)
- Response time: <24 hours for active experiments