AGL17 Antibody

What is ADAM17 and what role does it play in cellular processes?

ADAM17 (A Disintegrin And Metalloproteinase 17) is a transmembrane protease that cleaves ectodomains of various transmembrane proteins, including ACE2 and the proinflammatory cytokine TNF-α, from cell surfaces upon cellular activation. It plays a critical role in regulating inflammation, immune responses, and cellular signaling pathways. ADAM17's cleavage activity affects multiple physiological processes, including development, tissue regeneration, and pathological conditions such as inflammation and cancer . The enzyme's ability to shed the ectodomain of ACE2 (the SARS-CoV-2 receptor) has significant implications for viral pathogenesis and infection dynamics.

How do ADAM17-neutralizing antibodies function in experimental systems?

ADAM17-neutralizing antibodies, such as MEDI3622, function by binding to ADAM17 and inhibiting its proteolytic activity. These antibodies typically target the catalytic domain of ADAM17, preventing it from cleaving its substrates. In experimental systems, administration of ADAM17-neutralizing antibodies has been shown to reduce inflammatory responses while paradoxically increasing viral burden in models of SARS-CoV-2 infection. The mechanism involves dual effects: inhibition of pro-inflammatory cytokine release (beneficial) and prevention of ACE2 shedding (potentially detrimental for viral clearance) . This highlights the complex role of ADAM17 in balancing antiviral defense and inflammatory damage.

What are the optimal storage and handling conditions for maintaining ADAM17 antibody activity?

For optimal stability and activity, ADAM17 antibodies should be stored according to manufacturer specifications, typically at -20°C for long-term storage or at 4°C for short-term use (up to one month). Antibodies should be aliquoted before freezing to avoid repeated freeze-thaw cycles, which can significantly reduce activity. When handling, minimize exposure to room temperature, avoid contamination, and use sterile techniques. Stabilizing proteins (such as BSA) are often included in storage buffers to maintain antibody structure and function. Before experimental use, centrifuge antibody solutions briefly to collect the liquid at the bottom of the tube and ensure accurate concentration measurements for experimental reproducibility.

How can researchers validate the specificity of ADAM17 antibodies?

Validation of ADAM17 antibody specificity requires a multi-method approach:

• Knockout/knockdown controls: Test antibody reactivity in ADAM17 knockout or knockdown samples compared to wild-type controls

• Western blotting: Verify correct molecular weight band (approximately 120 kDa for full-length ADAM17 and 85 kDa for the mature form)

• Immunoprecipitation followed by mass spectrometry: Confirm target identity

• Functional assays: Measure inhibition of ADAM17-mediated substrate cleavage (e.g., TNF-α shedding)

• Cross-reactivity testing: Evaluate binding to related ADAM family members to ensure specificity

The combination of these validation methods provides robust confirmation of antibody specificity, essential for accurate interpretation of experimental results.

How does ADAM17 antibody treatment affect COVID-19 pathogenesis in experimental models?

• An anti-viral function that helps control viral replication

• A pro-inflammatory function that contributes to tissue damage

This duality presents a complex therapeutic consideration, as blocking ADAM17 may simultaneously reduce harmful inflammation while potentially compromising viral clearance mechanisms. The net benefit in experimental models suggests that the inflammatory cascade ultimately drives adverse outcomes, making ADAM17 inhibition a potentially viable therapeutic approach despite increased viral load .

What experimental design considerations are critical when evaluating ADAM17 antibody efficacy in inflammation models?

When designing experiments to evaluate ADAM17 antibody efficacy in inflammation models, researchers should consider:

• Timing of administration: Pre-treatment versus therapeutic intervention after disease onset

• Dosage optimization: Determine dose-response relationships with multiple concentration points

• Route of administration: Compare intravenous, intraperitoneal, or local delivery

• Duration of treatment: Acute versus chronic administration protocols

• Comprehensive readouts: Measure both direct targets (substrate cleavage) and downstream effects (inflammatory markers, tissue pathology)

• Controls: Include isotype control antibodies and positive controls (known anti-inflammatory agents)

• Multiple models: Test in diverse inflammation models to establish breadth of efficacy

• Sex and age considerations: Evaluate in both male and female subjects across different age groups

Researchers should also implement blinded assessment of outcomes, particularly for subjective measurements like histopathology scoring, to minimize bias in data interpretation.

How do researchers resolve conflicting data regarding ADAM17 antibody effects across different experimental systems?

Resolving conflicting data regarding ADAM17 antibody effects requires systematic investigation of variables contributing to discrepancies:

• Context-dependent mechanisms: Analyze cell/tissue-specific expression of ADAM17 substrates and downstream signaling pathways

• Antibody characteristics: Compare epitope specificity, binding affinity, and functional inhibition across different antibodies

• Model system differences: Evaluate species differences in ADAM17 structure/function and disease mechanisms

• Experimental conditions: Standardize key parameters (timing, dose, route) across studies

• Pharmacokinetics/pharmacodynamics: Assess antibody distribution, half-life, and target engagement in different models

• Compensatory mechanisms: Investigate upregulation of related proteases or alternate pathways

• Meta-analysis approaches: Systematically compare methodologies and outcomes across studies

A structured evaluation table comparing key parameters across studies often helps identify patterns explaining discrepant results. Additionally, combinatorial approaches targeting multiple related pathways may help resolve mechanistic questions when single-target inhibition produces variable outcomes.

What is the relationship between ADAM17 inhibition and ACE2 shedding in the context of viral infections?

ADAM17 is a primary sheddase responsible for cleaving the ectodomain of ACE2, the cellular receptor for SARS-CoV and SARS-CoV-2. The relationship between ADAM17 inhibition and ACE2 shedding involves several key aspects:

Studies in the K18-hACE2 transgenic mouse model demonstrated that ADAM17 antibody treatment resulted in increased viral burden, likely due to preserved ACE2 expression on cell surfaces providing more entry points for the virus . Conversely, the reduced inflammatory damage despite higher viral load suggests that ADAM17's role in propagating inflammatory cascades (via TNF-α shedding) may be more determinant of disease outcome than its effect on viral entry.

What are the optimal parameters for using ADAM17 antibodies in immunohistochemistry applications?

Optimizing ADAM17 antibody usage in immunohistochemistry requires attention to several key parameters:

Sample Preparation Protocol:

• Fixation: 4% paraformaldehyde for 24 hours provides optimal epitope preservation

• Antigen retrieval: Heat-induced epitope retrieval (HIER) with citrate buffer (pH 6.0) for 20 minutes

• Blocking: 5-10% normal serum (species-matched to secondary antibody) with 0.3% Triton X-100

• Primary antibody dilution: Typical range 1:100-1:500, determined through titration experiments

• Incubation conditions: Overnight at 4°C in humidity chamber

• Detection system: Polymer-based detection systems typically provide better signal-to-noise ratio than ABC methods

• Counterstaining: Light hematoxylin counterstain to avoid obscuring antibody signal

Critical Controls:

• Positive control tissues (known ADAM17-expressing tissues)

• Negative controls (antibody diluent only)

• Absorption controls (antibody pre-incubated with immunizing peptide)

• Isotype controls to assess non-specific binding

Troubleshooting Guide:

• For high background: Increase blocking time/concentration and optimize antibody dilution

• For weak signal: Extend antigen retrieval time and optimize primary antibody concentration

• For non-specific staining: Implement additional washing steps and reduce secondary antibody concentration

How should researchers optimize ADAM17 antibody-based immunoprecipitation protocols?

Optimizing ADAM17 antibody immunoprecipitation requires methodical adjustment of multiple parameters:

Pre-Immunoprecipitation Considerations:

• Lysis buffer selection: Use RIPA buffer with protease inhibitors for membrane protein extraction

• Cell/tissue preparation: Process samples rapidly at 4°C to prevent protein degradation

• Pre-clearing: Incubate lysates with protein A/G beads for 1 hour to reduce non-specific binding

Immunoprecipitation Protocol:

• Antibody amount: Typically 2-5 μg per 500 μg of total protein

• Antibody binding: Incubate with lysate overnight at 4°C with gentle rotation

• Bead type selection: Protein A for rabbit antibodies, Protein G for mouse IgG1, mixed A/G for other isotypes

• Bead amount: 20-50 μL of bead slurry per reaction

• Washing stringency: 3-5 washes with increasingly stringent buffers

• Elution method: Either with SDS sample buffer at 95°C for 5 minutes or with specific peptide competition

Verification Methods:

• Western blotting with a different ADAM17 antibody (recognizing a distinct epitope)

• Mass spectrometry analysis of immunoprecipitated protein

• Activity assays using fluorogenic ADAM17 substrates

Researchers should perform side-by-side comparisons of different antibody clones and concentrations to determine optimal conditions for their specific experimental system.

What quantitative methods can accurately assess ADAM17 antibody binding affinity and inhibitory potential?

Several quantitative methods are available for assessing ADAM17 antibody binding and inhibition:

Binding Affinity Determination:

• Surface Plasmon Resonance (SPR): Provides real-time binding kinetics (kon, koff) and equilibrium dissociation constant (KD)

  • Typical protocol: Immobilize purified ADAM17 on sensor chip, flow antibody at 5-7 concentrations

  • Analysis: Fit data to 1:1 Langmuir binding model

  • Expected range: High-affinity antibodies typically show KD values in low nanomolar range

• Bio-Layer Interferometry (BLI): Alternative to SPR with similar outputs

  • Advantages: Lower sample volume requirements and no microfluidics

• Isothermal Titration Calorimetry (ITC): Measures thermodynamic parameters

  • Provides complete thermodynamic profile (ΔH, ΔS, ΔG)

  • Requires larger amounts of purified protein

Functional Inhibition Assessment:

• Enzyme Activity Assays: Use fluorogenic peptide substrates

  • Calculation of IC50 values through dose-response curves

  • Determination of inhibition mechanism (competitive, non-competitive)

• Cell-Based Shedding Assays: Measure inhibition of TNF-α or other substrate shedding

  • Flow cytometry to quantify surface retention of ADAM17 substrates

  • ELISA to measure decreased substrate release into media

• Proximity-Based Assays: AlphaLISA or HTRF to assess ADAM17-substrate interaction

Data Analysis and Reporting:

• Report both binding affinity (KD) and functional inhibition (IC50)

• Calculate correlation between binding affinity and functional inhibition

• Graph dose-response curves with 95% confidence intervals

How can researchers effectively compare the performance of different ADAM17 antibody lots?

Consistent antibody performance across lots is critical for research reproducibility. A systematic comparison approach includes:

Standardized Testing Protocol:

• Initial characterization: Document lot number, concentration, storage conditions, and expiration date

• Physical inspection: Check for precipitates, discoloration, or other visible abnormalities

• Protein concentration verification: BCA or Bradford assay to confirm reported concentration

Functional Comparisons:

• Binding assays: ELISA using recombinant ADAM17

  • Calculate EC50 values for each lot

  • Compare maximum signal and background levels

  • Acceptance criteria: <20% variation in EC50 between lots

• Activity inhibition: Standard enzyme inhibition assay

  • Compare IC50 values across lots

  • Test at least 3 substrate concentrations

  • Acceptance criteria: <25% variation in IC50 between lots

• Application-specific testing: Evaluate in the specific application (IHC, WB, IP, etc.)

  • Use standardized positive control samples

  • Quantify signal intensity and background

  • Document optimal working dilutions for each lot

Quantitative Comparison Matrix:

Maintain detailed records of all lot comparisons to track variations over time and ensure experimental reproducibility.

How are computational approaches enhancing ADAM17 antibody design and optimization?

Computational approaches are revolutionizing ADAM17 antibody design through several advanced methods:

• Structure-Based Design: Leveraging crystal structures of ADAM17 catalytic domains to design antibodies targeting specific functional regions. Computational docking and molecular dynamics simulations predict binding modes and energetics, guiding rational design of high-affinity antibodies with specific inhibitory properties.

• Machine Learning Models: Recent advances in generative models for antibody design show promising results. These models include:

  • LLM-style models

  • Diffusion-based models

  • Graph-based models

  These approaches can generate novel antibody sequences with predicted binding to ADAM17 . Log-likelihood scores from these generative models correlate well with experimentally measured binding affinities, making them valuable tools for ranking antibody designs before experimental validation .

• In Silico Evaluation Metrics: Current antibody designs are evaluated using:

  • Sequence-based metrics: amino acid recovery (AAR)

  • Structure-based metrics: root-mean-square deviation (RMSD), predicted alignment error (pAE), and interface predicted template modeling (ipTM)

• Synthetic Training Data: Large-scale models like DiffAbXL are trained on combined datasets from:

  • Structural Antibody Database (SAbDab)

  • Approximately 1.5 million structures generated using ImmuneBuilder2

  • Paired sequences from the Observed Antibody Space (OAS)

These computational approaches significantly reduce the time and resources required for antibody development by prioritizing the most promising candidates for experimental validation.

What new experimental models are being developed to study ADAM17 antibody functions in complex disease settings?

Innovative experimental models for studying ADAM17 antibody functions include:

• Humanized Mouse Models: Beyond traditional K18-hACE2 transgenic mice used for COVID-19 studies , new models feature tissue-specific expression of human ADAM17 to better recapitulate human disease conditions.

• Organoid Systems: Three-dimensional organoid cultures derived from primary human tissues provide physiologically relevant environments for testing ADAM17 antibody effects on:

  • Inflammatory bowel disease models (gut organoids)

  • Respiratory infection models (lung airway organoids)

  • Tumor microenvironment models (cancer organoids)

  These systems enable assessment of ADAM17 inhibition in complex cellular environments while maintaining human-specific biology.

• Microphysiological Systems (Organ-on-Chip): These platforms integrate multiple tissue types with controlled flow conditions, enabling:

  • Real-time monitoring of ADAM17 substrate shedding using fluorescent reporters

  • Assessment of tissue crosstalk during ADAM17 inhibition

  • Evaluation of pharmacokinetic/pharmacodynamic relationships in pseudo-physiological conditions

• CRISPR-Engineered Reporter Systems: Cell lines with endogenously tagged ADAM17 substrates allow for:

  • Live-cell imaging of substrate cleavage events

  • High-throughput screening of antibody variants

  • Quantitative assessment of inhibition kinetics

These advanced models bridge the gap between traditional in vitro systems and in vivo studies, providing more translatable insights into ADAM17 antibody functions in complex disease settings.

How does ADAM17 antibody therapy interact with other immunomodulatory approaches?

The interaction between ADAM17 antibody therapy and other immunomodulatory approaches presents complex dynamics:

These complex interactions require systematic evaluation through specifically designed combination studies with careful consideration of dosing, timing, and sequence of administration.

What role might ADAM17 antibodies play in emerging gene and cell therapy approaches?

ADAM17 antibodies are finding novel applications in advanced gene and cell therapy approaches:

• Engineered Cell Therapies:

  • CAR-T cell function can be modulated by controlling ADAM17-mediated shedding of activation markers

  • ADAM17 antibody treatment during ex vivo expansion phases enhances persistence of key surface receptors

  • Incorporation of ADAM17 antibody fragments into CAR constructs creates self-regulating systems that maintain optimal surface receptor density

• Gene Therapy Delivery Enhancement:

  • ADAM17 processes various cell surface receptors used by viral vectors

  • Temporary ADAM17 inhibition during gene therapy administration can enhance transduction efficiency

  • Co-administration protocols combining gene therapy vectors with ADAM17 antibodies show improved targeting to specific tissues

• mRNA Therapeutic Applications:

  • ADAM17 antibody-encoding mRNA provides temporal control over ADAM17 inhibition

  • Lipid nanoparticle delivery systems can target ADAM17 antibody expression to specific tissues

  • Programmable expression systems allow inducible ADAM17 inhibition in response to inflammatory triggers

• Regenerative Medicine Applications:

  • ADAM17 regulates various developmental and regenerative pathways

  • Controlled inhibition using antibodies can enhance stem cell differentiation protocols

  • Biomaterial scaffolds incorporating ADAM17 antibodies create microenvironments promoting tissue regeneration

These emerging applications illustrate how ADAM17 antibodies are extending beyond traditional immunomodulatory roles into advanced therapeutic paradigms at the cutting edge of biomedical research.