Background

Label-free interaction analysis is of great importance for scientists to study interactions between biomolecules. Scientists from Creative Biolabs are competent for performing antibody affinity and kinetics measurement with the most advanced Biacore, ProteOn, Octet systems, etc. These systems are mainly based on the optical phenomena technologies - surface plasmon resonance (SPR) and bio-layer interference (BLI), which enable a direct detection and measurement of molecular interactions in a real-time monitoring manner.

SPR is an extremely sensitive method for the detection of molecular interactions by tracking the change of signal via sensor chips. SPR signal is defined as refractive index changes, which refers the response unit (RU) is approximately equivalent to a surface concentration of protein at 1pg/mm2. Plotting the SPR signal over time during the interaction between two molecules results in a sensorgram, which could be visualized in real time (Figure 1). General binding response includes three phases: association, equilibrium and dissociation; fitting these sensorgram data with a mathematic model allows scientists to calculate the association (Ka) and dissociation (Kd) rate constants and ultimately determine the binding affinity (KD). Different from isothermal calorimetry (ITC) that measures antibody binding affinity based on equilibrium point, SPR could obtain full kinetic parameters to evaluate all the effects of association and dissociation as well as antibody affinity.

Figure 1. SPR imaging process

In antibody affinity measurement, the antibodies to be analyzed are first captured by high-affinity anti-IgG antibody immobilized on the sensor chip surface. Then a series of concentrations of antigens are sequentially injected across the surface. Based on the sensorgram curve, people can rank the antibodies according to the kinetic parameters and select monoclonal antibodies with the best characters of your preference. Compared to the discovery of tight-binding antibodies, the identification of specific region (epitope) is more promising in drug discovery since the binding affinity could be matured via standard protein engineering approaches. Thus, based on the bivalent analyte model, which refers to two binding responses, we are capable of providing scouting assay to identify antibodies binding to two distinct antigen epitopes. Firstly, a generic anti-antibody (such as rabbit anti-mouse immunoglobulins) is covalently attached to the chip surface, and then the first antibody is captured by the generic antibody previously attached. After the blocking of unsaturated sites, the injected antigen will be bonded by the first antibody with the formation of Ab-Ag complex. Followed by the administration of a second monoclonal antibody which is applied to evaluate the binding affinity, a unique sensorgram curve will be observed if the second antibody binds to a distinct separate epitope. (Figure 2)

Figure 2. Major steps in epitope mapping. ① First antibody capture. ② Block unsaturated site. ③ interact with antigen. ④ Introduce with the second antibody ⑤ Rinse and regeneration

Antibody Affinity Measurement Services

Creative Biolabs can provide custom antibody affinity measurement, and also any molecular interactions (molecular mass not less than 100) can be determined in a real time manner without labeling. All the data analysis will be performed and documented. Please feel free to contact us for a detailed quote.

Learn more about Antibody Affinity Measurement:

• Cell Line Affinity Measurement
• Affinity Measurement Services for Specific Antibodies
• Membrane Proteins Affinity Measurement
• Affinity Measurement Services for Bivalent Antigens
• Affinity Measurement Services for Dimers/Polymers
• Affinity Measurement Services for Small Molecules
• Affinity Measurement Services for Cell Lysates
• Affinity Measurement Services for Various Ligands and Analytes
• Biacore System
• ProteOn System
• Octet system

Published Data

• Affinity Measurement of an Optimized BDNF Monoclonal Antibody

Fig. 3 Demonstration of affinity improvement of B30 over parental R3bH01. (Edwina Stack, 2020)

Brain-derived neurotrophic factor (BDNF) has been shown to act on chronic pain, so a high-affinity, peripherally restricted anti-BDNF monoclonal antibody can be designed to regulate pain. Here, the scientists chose the chicken as an alternative immune host for initial antibody production. R3bH01 is an anti-BDNF antibody that specifically blocks the interaction of TrkB receptors. Through complementary determination region transplantation, the affinity of chicken-derived R3bH01 was optimized, and B30 was identified. The affinity measured in vitro was transformed into pharmacological activity in vivo, and the efficacy of B30 in the peripheral nerve injury model was 30 times higher than that of parent R3bH01. Further studies have shown that peripheral BDNF plays a role in maintaining the plasticity of sensory neurons after nerve injury, and B30 reverses the overexcitation of neurons related to thermal and mechanical stimulation in a dose-dependent manner. In short, the role of BDNF in chronic pain can be effectively inhibited by high affinity neutralizing antibodies.

FAQ

1. What is antibody affinity and why is it important to measure it?

   Antibody affinity refers to the strength of the binding interaction between an antibody and its specific antigen. Measuring antibody affinity is crucial because it provides insight into the effectiveness of an antibody in recognizing and binding to its target. High affinity is often associated with increased efficacy in various applications, including therapeutic interventions, diagnostic tools, and research experiments. By assessing affinity, researchers can select or engineer antibodies that are most effective for their specific needs.

2. How is antibody affinity measured?

   Antibody affinity can be measured using several techniques, each suitable for different contexts and requirements. Common methods include:

   • Surface Plasmon Resonance (SPR): This technique measures the real-time binding kinetics between an antibody and antigen, providing a direct measurement of affinity and kinetic rates.
   • Enzyme-linked Immunosorbent Assay (ELISA): By competing an antibody with varying concentrations of antigen, ELISA can indirectly measure affinity based on the equilibrium constant derived from the binding curves.
   • Biocore Technology: Similar to SPR, this method uses optical sensors to detect the interaction between antibody and antigen, allowing for precise kinetic analysis.
3. What factors can influence the measurement of antibody affinity?
   • Antigen properties: The physical characteristics of the antigen, such as its size, conformation, and purity, can affect binding interactions.
   • Assay conditions: Variations in pH, temperature, and ionic strength of the buffer used during the measurement can alter antibody-antigen interactions.
   • Antibody valency: Multivalent antibodies, which have multiple binding sites, can exhibit apparent higher affinity due to avidity effects, complicating the interpretation of true monovalent affinity.
4. Can antibody affinity be improved? If so, how?

   Antibody affinity can be enhanced through various engineering techniques. Common approaches include:

   • Mutagenesis: Introducing mutations in the antibody's variable regions can lead to changes in the binding site that improve interaction with the antigen.
   • Phage display: This technique allows for the screening of vast libraries of antibody variants to identify those with higher affinity.
   • Affinity maturation in vivo or in vitro: Mimicking the natural immune process, antibodies can be evolved in controlled environments to enhance their affinity.
5. What is the difference between affinity and avidity in antibody interactions?

   Affinity refers to the strength of the binding between a single antigen-binding site on an antibody and a single epitope on an antigen. In contrast, avidity describes the overall strength of binding between a multivalent antibody and a multivalent antigen, incorporating all the interactions from the multiple binding sites. Avidity is influenced not only by the affinity of individual antibody-antigen interactions but also by the valency of both the antibody and the antigen, as well as the spatial arrangement of the binding sites. This makes avidity a more comprehensive measure of the functional binding strength in multivalent interactions, which is particularly relevant in assessing the effectiveness of polyvalent antibodies in biological systems.

6. What role does antibody affinity measurement play in vaccine development?

   In vaccine development, measuring antibody affinity is critical for determining the potency and potential efficacy of vaccine-induced immune responses. High-affinity antibodies are generally more effective at neutralizing pathogens and preventing infection. During the vaccine development process, affinity measurements can guide the selection of antigen designs, adjuvants, and delivery methods that induce a robust and high-affinity antibody response. Additionally, monitoring changes in antibody affinity over time can help in assessing the need for booster vaccinations and the long-term effectiveness of the vaccine.

7. How does temperature affect antibody affinity measurements?

   Typically, higher temperatures increase the rate of molecular interactions but might decrease binding affinity by destabilizing the antibody-antigen complex. Conversely, lower temperatures generally stabilize these complexes, potentially leading to an apparent increase in affinity. Accurate affinity measurements, therefore, require conducting experiments at a consistent and physiologically relevant temperature to ensure that the results are representative of biological conditions.

8. Are there computational methods available for predicting antibody affinity?

   These computational methods often involve molecular modeling and simulations to predict how mutations or modifications to an antibody's structure could affect its binding to an antigen. Computational approaches can be highly beneficial in the early stages of antibody design and optimization, providing insights that help reduce the need for extensive empirical testing. Tools such as molecular docking, dynamics simulations, and machine learning models are commonly used to predict binding sites, optimize antibody-antigen interactions, and estimate binding energies, thereby helping to predict affinity changes due to structural alterations. These predictions can then guide more targeted experiments in the laboratory.

Resources

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All listed services and products are For Research Use Only. Do Not use in any diagnostic or therapeutic applications.