AGD6 Antibody

What is Gas6 protein and why is it a significant target for antibody development?

Gas6 (growth-arrest-specific gene 6) is a protein involved in cell survival and proliferation across multiple cell types including endothelial cells, vascular smooth-muscle cells (VSMCs), mesangial cells, osteoclasts, and fibroblasts. It functions as a critical platelet amplifier and chemotactic factor for VSMCs .

Studies with Gas6 knockout mice demonstrated that Gas6-depleted platelets no longer respond to low concentrations of most agonists, resulting in protection from both venous and arterial thrombosis challenges . This physiological role makes Gas6 an attractive target for therapeutic antibody development, particularly for conditions involving dysregulated cellular growth or thrombosis.

The development of neutralizing antibodies against Gas6, such as CNTO300, represents a strategic approach to modulating receptor signaling pathways in conditions where Gas6 overactivation contributes to pathological states.

How does the CNTO300 antibody interact with Gas6 protein at the molecular level?

CNTO300 is a neutralizing human monoclonal antibody developed specifically for Gas6. This antibody was generated through immunization of human IgG-expressing transgenic mice with recombinant human Gas6 protein .

The molecular interaction between CNTO300 and Gas6 has several distinctive characteristics:

• CNTO300 partially inhibits Gas6 binding to its receptors in a dose-dependent manner

• The antibody shows comparable binding affinity to both full-length Gas6 and the independently expressed LG1 domain

• No binding to the LG2 domain was detected

• CNTO300 binding to Gas6 is disrupted by EDTA (indicating calcium dependency), yet EDTA has no significant effect on binding to the isolated LG1 domain

Epitope mapping identified a specific Gas6 peptide sequence recognized by CNTO300, located at the LG1 domain distant from both the calcium-binding site and the hydrophobic patch. This finding revealed a previously uncharacterized second receptor-binding site on the LG1 domain, supported by direct binding studies showing Gas6 receptors can bind to independently expressed LG1 domain .

What are the key structural domains involved in Gas6-receptor interactions?

Gas6 contains two C-terminal globular domains (LG1 and LG2) that mediate receptor binding through distinct mechanisms. The traditional understanding of Gas6-receptor interaction focused primarily on the LG2 domain, which contains both a calcium-binding site and a hydrophobic patch previously thought to be the main regions important for receptor binding .

Recent research with CNTO300 has revealed a more complex binding model involving both domains:

This dual-domain interaction model provides crucial insights for therapeutic antibody development, suggesting that targeting the LG1 domain may offer alternative approaches to modulating Gas6 signaling beyond traditional LG2-focused strategies .

What experimental methods are used to assess Gas6 antibody neutralization efficacy?

Researchers employ several complementary approaches to evaluate the neutralizing activity of anti-Gas6 antibodies:

• Solid-phase ELISA competitive binding assays:

  • Receptor proteins (e.g., Axl-Fc) are coated onto plates

  • Recombinant Gas6 is added with titrated antibody concentrations

  • Bound Gas6 is detected using anti-FLAG antibodies (for FLAG-tagged Gas6)

  • Commercial neutralizing polyclonal antibodies serve as positive controls

• BIAcore surface plasmon resonance analysis:

  • Real-time measurement of binding kinetics

  • Assessment of whether antibodies and receptors can simultaneously bind Gas6

  • Determination of competition or co-binding relationships

• Domain-specific binding studies:

  • Comparison of antibody binding to full-length Gas6 versus independently expressed domains

  • Identification of domain-specific neutralization mechanisms

• Calcium dependency analysis:

  • Evaluation of binding in the presence versus absence of calcium using EDTA

  • Determination of structural requirements for antibody-antigen interaction

These methodologies collectively provide a comprehensive assessment of neutralizing antibody function and mechanism of action.

What novel binding sites have been identified for Gas6-receptor interaction and their implications?

Research with the CNTO300 antibody has revealed a previously uncharacterized second binding site for Gas6-receptor interaction located on the LG1 domain. This finding challenges the prior assumption that receptor binding was mediated exclusively through the hydrophobic patch on the LG2 domain .

The key evidence supporting this novel binding site includes:

• Co-interaction of Gas6 with both receptor and CNTO300 antibody (which binds LG1) detected by BIAcore analysis

• Direct binding of Gas6 receptors (Axl-Fc, Dtk-Fc, and Mer-Fc) to independently expressed LG1 domain

• Identification of a specific peptide sequence on LG1 recognized by the neutralizing CNTO300 antibody

This discovery significantly impacts our understanding of Gas6 signaling mechanisms and opens new avenues for therapeutic targeting:

• The dual-domain interaction model suggests that both LG1 and LG2 domains contribute to receptor binding, potentially with different affinities or specificities for different receptor types

• Domain-specific antibodies could potentially achieve selective inhibition of signaling through specific receptors if different Gas6 receptors (Axl, Dtk, Mer) interact differentially with the two domains

• Targeting the newly identified binding site on LG1 might offer more precise modulation of Gas6 signaling compared to approaches targeting the conventional LG2 domain

How does calcium dependency affect Gas6 antibody binding efficacy in experimental settings?

Calcium dependency is a critical factor influencing Gas6-antibody interactions, with differential effects observed between full-length Gas6 and isolated domains. Research with CNTO300 revealed several important aspects of this relationship:

These findings suggest that:

• Calcium induces conformational changes in the full-length Gas6 protein that affect antibody accessibility to certain epitopes

• The isolated LG1 domain may adopt a conformation that preserves antibody binding sites regardless of calcium status

• Allosteric interactions between domains likely influence the calcium dependency of antibody binding

For experimental design, researchers must carefully consider calcium levels when studying full-length Gas6 interactions, while isolated domain studies may be less sensitive to these conditions. This understanding is crucial for optimizing binding assays and interpreting results in physiological contexts where calcium levels may vary.

What are the structural determinants of antibody epitopes on Gas6 and how can they inform therapeutic development?

The identification of the CNTO300 epitope on the LG1 domain of Gas6 provides valuable insights into the structural determinants of effective neutralizing antibodies. This epitope is located distant from both the calcium-binding site and the hydrophobic patch previously thought to be the primary receptor-binding regions .

Several structural features characterize functionally significant epitopes on Gas6:

• Location relative to receptor binding sites: The most effective neutralizing epitopes either directly overlap with receptor binding sites or induce conformational changes affecting these sites

• Domain specificity: Epitopes on the LG1 domain target a distinct receptor interaction site compared to traditional LG2-targeting approaches

• Calcium sensitivity: Some epitopes are accessible only in the calcium-bound conformation of Gas6, while others may be calcium-independent

• Hydrophobic interactions: The hydrophobic patch on LG2 remains important for certain receptor interactions, but additional binding determinants exist

These structural insights inform therapeutic antibody development in several ways:

• Enabling structure-guided design of antibodies targeting specific functional epitopes

• Facilitating the development of antibodies with differential effects on various Gas6 receptors

• Supporting the rational design of antibodies that function under different physiological calcium conditions

• Providing the foundation for antibody engineering approaches to enhance specificity and affinity

How can computational models improve antibody design for optimal Gas6 targeting?

Recent advances in computational modeling have revolutionized antibody design, even in scenarios with limited experimental data. The DyAb model demonstrates how these approaches can significantly enhance antibody affinity and specificity:

Key computational strategies include:

• Combined beneficial mutations: Starting with individual mutations that improve affinity, computational models predict optimal combinations for synergistic effects

• Genetic algorithm approaches: For lead antibody optimization, genetic algorithms can select and mutate sequences to iteratively improve predicted binding affinity

• Edit distance-based sampling: Generating and evaluating combinations of mutations at various edit distances (ED) can efficiently explore sequence space

• Iterative design-build-test cycles: Incorporating experimental results back into training data significantly enhances model performance with each design cycle

These computational approaches have demonstrated remarkable success even with limited initial data. For example, with data from only ~100 variants of an anti-IL-6 lead, the DyAb approach generated sequences that all expressed successfully, bound IL-6, and improved affinity relative to the lead (1.4 nM), with four designs increasing affinity by more than 3-fold .

What techniques are most effective for identifying antibody epitopes on Gas6?

Researchers employ multiple complementary techniques to precisely identify antibody epitopes on Gas6:

• Domain-level binding studies:

  • Expression of isolated LG1 and LG2 domains

  • Comparative binding analysis to full-length versus domain proteins

  • This approach identified the LG1 domain as the binding region for CNTO300

• Calcium dependency analysis:

  • Binding studies in the presence versus absence of calcium (using EDTA)

  • Different calcium dependencies between full-length Gas6 and isolated domains provided insights into conformational aspects of epitope accessibility

• Epitope mapping techniques:

  • Peptide arrays to identify specific sequences recognized by antibodies

  • Mass spectrometry analysis of antibody-antigen complexes

  • Site-directed mutagenesis of potential binding residues

• Co-binding studies:

  • BIAcore analysis to determine if antibody and receptor can simultaneously bind Gas6

  • The observation that Gas6 could interact simultaneously with both receptor and CNTO300 provided key evidence for distinct binding sites

• Competition assays:

  • Dose-dependent inhibition studies with varying antibody concentrations

  • Comparison with characterized antibodies targeting known epitopes

These techniques, used in combination, provide comprehensive characterization of antibody epitopes and their functional significance.

How can BIAcore analysis be optimized for studying Gas6-antibody interactions?

BIAcore surface plasmon resonance (SPR) analysis is a powerful technique for studying protein-protein interactions, including Gas6-antibody binding. Optimal BIAcore protocols for Gas6 studies include:

• Immobilization strategy:

  • For antibody evaluation: Immobilize Gas6 or domains on sensor chip

  • For receptor binding studies: Immobilize receptor-Fc fusion proteins (Axl-Fc, Dtk-Fc, Mer-Fc)

  • Use appropriate concentrations (10 nM for Axl-Fc and Dtk-Fc, 150 nM for Mer-Fc)

• Buffer optimization:

  • Standard HBS buffer with calcium for normal binding studies

  • EDTA-containing buffer for calcium dependency analysis

  • Test calcium concentration gradients to determine optimal conditions

• Co-interaction analysis protocol:

  • Sequential injection: First analyte (antibody) followed by second analyte (receptor)

  • Measure binding response with single versus combined analytes

  • Calculate percent inhibition relative to controls

• Kinetic analysis parameters:

  • Flow rates: 10-30 μL/min for association phase

  • Extended dissociation phase (>10 minutes) for high-affinity interactions

  • Multiple analyte concentrations spanning 0.1-10× KD

• Data normalization and controls:

  • Reference surface subtraction

  • Buffer blank injections

  • Irrelevant protein or antibody controls

These optimized approaches provide precise characterization of binding kinetics, enabling detailed comparisons between different antibody candidates and determining their mechanisms of action in relation to receptor binding.

What expression systems are most effective for producing research-grade Gas6 antibodies?

Various expression systems offer distinct advantages for producing Gas6 antibodies, with selection depending on research requirements:

For the CNTO300 antibody, researchers initially used hybridoma technology with human IgG-expressing transgenic mice, but faced challenges with clone stability. They successfully rescued the antibody gene sequences using molecular cloning approaches .

For evaluating novel antibody designs, mammalian expression systems have demonstrated high success rates, with 85-100% of computationally designed variants successfully expressing and binding their targets .

The choice of expression system should be guided by:

• Research phase (discovery vs. validation)

• Required protein modifications

• Scale of production needed

• Downstream application requirements

How can researchers effectively predict and improve antibody properties with limited experimental data?

Computational approaches demonstrate remarkable effectiveness in predicting and improving antibody properties even with limited data. Key strategies include:

• Machine learning frameworks integration:

  • Models like DyAb combine different protein language models (AntiBERTy, LBSTER)

  • Models trained on small datasets (as few as ~100 variants) can make accurate predictions

  • Pearson correlations of r = 0.84 between predicted and measured affinity improvements demonstrate predictive power

• Staged optimization approach:

  • Begin with individual mutations showing improved properties

  • Generate combinations at increasing edit distances (ED 3-11)

  • Use computational models to prioritize candidates for experimental testing

  • Incorporate new experimental data iteratively

• Data enhancement techniques:

  • Transfer learning from large protein databases

  • Fine-tuning on specific antibody datasets

  • Augmentation of limited experimental data

The effectiveness of these approaches has been demonstrated across multiple antibody targets:

• For anti-EGFR variants, an initial design round produced binders with similar affinities to training set variants (~100 pM) but at a much higher success rate

• A second design round incorporating new data yielded further improved affinity to 66 pM (nearly 50-fold improvement over the original)

• Even with data from only ~100 variants of an anti-IL-6 lead, the approach generated sequences with 100% expression success and affinity improvements exceeding 3-fold

These computational strategies enable efficient exploration of vast sequence spaces and prioritization of promising candidates, dramatically reducing experimental burden while achieving significant improvements in antibody properties.