The authors thank Noah Ditto and Adam Miles for technical assistance on the IBIS MX96.

<ol>
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D., Levine, H. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+therapeutic+monoclonal+antibody+market.">The therapeutic monoclonal antibody market.</a> mAbs. 7 (1), 9-14 (2014).</li><li>Rich, R. L., Myszka, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Higher-throughput,+label-free,+real-time+molecular+interaction+analysis.">Higher-throughput, label-free, real-time molecular interaction analysis.</a> Anal Biochem. 361 (1), 1-6 (2007).</li><li>Keighley, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+need+for+high+throughput+kinetics+early+in+the+drug+discovery+process.">The need for high throughput kinetics early in the drug discovery process.</a> Drug Disc World. 12 (3), 39-45 (2011).</li><li>Lad, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+kinetic+screening+of+hybridomas+to+identify+high-affinity+antibodies+using+bio-layer+interferometry.">High-throughput kinetic screening of hybridomas to identify high-affinity antibodies using bio-layer interferometry.</a> J Biomol Screen. 20 (4), 498-507 (2015).</li><li>Bravman, T., Bronner, V., Nahshol, O., Schreiber, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ProteOn+XPR36TM+Array+System-High+Throughput+Kinetic+Binding+Analysis+of+Biomolecular+Interactions.">The ProteOn XPR36TM Array System-High Throughput Kinetic Binding Analysis of Biomolecular Interactions.</a> Cell Mol Bioeng. 1 (4), 216-228 (2008).</li><li>Eddings, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+continuous-flow+print+head+for+micro-array+deposition.">Improved continuous-flow print head for micro-array deposition.</a> Anal Biochem. 382 (1), 55-59 (2008).</li><li>Abdiche, Y., Malashock, D., Pinkerton, A., Pons, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determining+kinetics+and+affinities+of+protein+interactions+using+a+parallel+real-time+label-free+biosensor+the+Octet.">Determining kinetics and affinities of protein interactions using a parallel real-time label-free biosensor the Octet.</a> Anal Biochem. 377 (2), 209-217 (2008).</li><li>Abdiche, Y. N., Lindquist, K. C., Pinkerton, A., Pons, J., Rajpal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expanding+the+ProteOn+XPR36+biosensor+into+a+36-ligand+array+expedites+protein+interaction+analysis.">Expanding the ProteOn XPR36 biosensor into a 36-ligand array expedites protein interaction analysis.</a> Anal Biochem. 411 (1), 139-151 (2011).</li><li>Rich, R. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+global+benchmark+study+using+affinity-based+biosensors.">A global benchmark study using affinity-based biosensors.</a> Anal Biochem. 386 (2), 194-216 (2009).</li><li>Yang, D., Singh, A., Wu, H., Kroe-Barrett, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+biosensor+platforms+in+the+evaluation+of+high+affinity+antibody-antigen+binding+kinetics.">Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics.</a> Anal Biochem. 508, 78-96 (2016).</li><li>Yang, D., Singh, A., Wu, H., Kroe-Barrett, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dataset+of+the+binding+kinetic+rate+constants+of+anti-PCSK9+antibodies+obtained+using+the+Biacore+T100+ProteOn+XPR36,+Octet+RED384,+and+IBIS+MX96+biosensor+platforms.">Dataset of the binding kinetic rate constants of anti-PCSK9 antibodies obtained using the Biacore T100 ProteOn XPR36, Octet RED384, and IBIS MX96 biosensor platforms.</a> Data in Brief. 8, 1173-1183 (2016).</li><li>Bouvier, E. S. P., Koza, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+size-exclusion+separations+of+proteins+and+polymers+by+UHPLC.">Advances in size-exclusion separations of proteins and polymers by UHPLC.</a> Trends Anal Chem. 63, 85-94 (2014).</li></ol>

Publication fees for this video-article were paid by&#160;Boehringer Ingelheim Pharmaceuticals.

Our head-to-head comparison study shows that each biosensor platform has its own strengths and weaknesses. Even though the binding profiles of the antibodies are similar by visual comparison (Figures 3 - 6), and the rank order of the acquired kinetic rate constants are highly consistent across the instruments (Figure 7), our results show that SPR-based instruments with continuous flow fluidics) are better at resolving high-affinity interactions with slow dissociation rates. Upward drift during the dissociation phase is observed in datasets (e.g., mAb 2, mAb 5, and mAb 9; Figure 5) generated by the BLI fluidics-free instrument. This finding can be attributed in large part to sample evaporation over time in the microplate, which is a primary limitation of the system. With this inherent limitation, the experimental time is also restricted to less than 12 h; the experiments were therefore programmed with shorter times (500 s association and 30 min dissociation) compared to those of the other platforms (10 min association and 45 min dissociation). However, shortening the experimental time did not appear to mitigate the impact of evaporation on data quality/consistency, as the rate constants generated by the BLI-based instrument show less linearity as a result of fluctuations in some of the off-rates (Figure 8C). In addition to sample evaporation, differences in the capture reagents used may have also contributed to the differences in the results obtained. While protein A/G was used in all three fluidics-based SPR platforms, AHC sensors were used in the non-fluidics BLI platform. Since protein A/G is likely to have a weaker affinity for the mAbs than does the AHC, an antibody-based biosensor surface, the off-rates of the mAb-antigen complex from the protein A/G surfaces may artificially appear faster than those obtained from the AHC surface. This possibility is supported by the experimental data showing that the off-rate values generated by the BLI platform were consistently lower than those obtained from the other instruments (Figure 7, red line). Nevertheless, the BLI platform has different advantages over the other platforms. For example, it is highly flexible with regard to sensor choice and assay configuration due to the various pre-coated sensors for immediate use. In our experiments, use of the AHC sensors eliminated the need for ligand immobilization steps, reducing the preparation time. Furthermore, the BLI platform requires much less maintenance compared to the other fluidics SPR platforms, which feature complicated tubing and value switch configurations. This feature is an advantage for experiments involving crude samples that can cause clogging and contamination issues.
As the demand for the efficient, rapid, and accurate identification of therapeutic candidates increases, the need for biosensor throughput is also rising. Among the four biosensor platforms, the throughput from the biosensor capable of 96-ligand array printing is the highest, followed by the biosensor coupled to a crisscrossing 36-ligand format and the BLI-based biosensor with 16-channel simultaneous readout, which ultimately increase the number of interactions measured in a single binding cycle to 96, 36 and 16, respectively. These throughput capabilities are significantly higher than that of the traditional SPR platform, which is limited by having only four flow cells connected by a single serial flow. Since our experiments involved a relatively small sample set of 10 mAbs evaluated at multiple surface densities with long dissociation times, the instrumental throughputs played a moderate role in determining the efficiency of the experiments. There were no significant differences in the experimental times of the three high-throughput platforms, and in all cases the experiments were completed in one day. On the other hand, the traditional serial flow SPR experiments required 3 days to complete, despite the walk-away automation of data acquisition after setup. In other studies that involve a large number of samples (i.e. in the hundreds or thousands), for off-rate ranking/kinetic screening or epitope binning purposes, the throughput becomes a critical factor.
Although the throughput in the IBIS MX96 is orders of magnitude higher than that of the other biosensors and is therefore an optimal choice for these purposes, it has a few shortcomings. In particular, the array printing by the CFM shows large surface inconsistencies (Figure 1) and reduced data reproducibility (Figure 8D and 8E). For accurate kinetic measurements, the amount of ligand on the biosensor surface is a critical parameter that needs to be controlled to ensure that the binding responses are not disturbed by secondary factors such as mass transfer or steric hindrance. For the Biacore T100 and ProteOn XPR36, the optimal RL levels were determined based on the standard calculation of set Rmax values as described in the research article17. On the other hand, for the Octet RED384 and IBIS MX96 platforms, the mAb capture levels were attained empirically using a series of 2-fold serially diluted antibodies at constant times. The lack of knowledge or control of the capture step resulted in a high-density surface and high binding response signals (Figure 2) that may have compromised the accuracy of the kinetic rate constants. Furthermore, the separation of the printer from the SPR detector also presents a challenge when conducting multiple binding cycle measurements involving regenerations. The only way to perform the multi-cycle kinetics setup was through direct amine coupling of the mAbs, as opposed to capture through the mAb Fc by the immobilized protein A/G surface in the other three biosensor platforms. As a result, an additional regeneration scouting experiment was required to determine the optimal regeneration conditions. The outcome of this setup was linked to a ~90% lower observed surface activity compared to the Fc capture method (Figure 9), in addition to a longer experimental time. To execute the Fc capture method, an alternative single-cycle kinetic approach was adopted. This approach involves the sequential injection of analyte at increasing concentrations without regeneration between each injection (Figure 2). This highly convenient, but less commonly applied approach not only shortened the experimental time and reduced reagent consumption, but also produced kinetic rate constants highly similar to those from the other biosensors (Figure 7). Therefore, applying this single-cycle kinetics approach overcomes the inherent configuration limitation of the instrument and presents an opportunity for obtaining high-resolution kinetic rate constants in a high-throughput manner.
Despite the throughput being a major limitation in the Biacore T100, our results collectively show that it generated the most consistent data with the highest quality. This was followed by the ProteOn XPR36, which has ~ 10-fold higher throughput. Their ability to generate high-quality data becomes an advantage when characterizing high-affinity antibody-antigen interactions that can be technically challenging when the instruments&#39; detection limits are reached. While the systematic limitations in instrumentation of the Octet RED384 hinder the accurate measurement of dissociation rate constants (i.e., falling short of the sensitivity to resolve sufficient signal decay for slow off-rates), both the Biacore T100 and ProteOn XPR36 can provide sensitive and reliable detection for differentiation.

The acquisition of reliable kinetic parameters for characterizing antibody-antigen interactions is an essential component of the drug discovery and development process1. Optical Surface Plasmon Resonance (SPR) biosensors, the "gold standard" for real-time detection of these interactions, have been used for approximately two decades to enable early selection of criteria-meeting therapeutic antibody candidates2,3. In addition to providing an affinity ranking of antibody candidates by the rapid binding screening of crude supernatants4, and rigorous kinetic constant determinations of purified preparations5, biosensors can further differentiate the functional activity of lead candidates via epitope binning studies6,7. 
To meet the growing demand of antibody-based products for various therapeutic indications8, a wide variety of innovative biosensor instruments have been developed in recent years that increase the efficiency of candidate identification and characterization9,10. These instruments differ in microfluidic channel configuration design and/or in the optical principles involved in detecting biomolecular interactions. Specifically, the Octet RED38411, ProteOn XPR3612, and IBIS MX967 have expanded the number of interactions measured in a single binding cycle to 16, 36, and 96 respectively, representing significant throughput improvements over the traditional Biacore platform. Although these various biosensor platforms all provide essential kinetic data for characterizing antibody-antigen interactions, they differ in experimental setup and operational procedures due to variations in instrumental configurations. For example, in the IBIS MX96's SPR imaging array platform, the multiplex ligand immobilization step is performed in an off-line mode in an external printing device separate from the detector7,13; in contrast, the other three biosensor platforms utilize an "all-in-one" setup, where the addition of component onto the sensor surface, whether it is the activation reagent, ligand, or analyte, is recorded in real time and through pre-programmed commands in sequential order. In the Octet RED384, a unique feature of this BioLayer Interferometry (BLI)-based platform is the availability of pre-coated optical fiber biosensors for immediate "dip-and-read" use14, eliminating the need for ligand surface preparation and initiation/conditioning steps, which are often required for the sensor chips in SPR-based platforms. This instrument's fluidic-free design also simplifies the mechanics and avoids clogging and contamination concerns when dealing with crude samples. With the novel 6 x 6 crisscrossing fluidic design in the ProteOn XPR36, a "one-shot" kinetics approach can be implemented by switching the flow channels between horizontal and vertical directions to create 36 interaction spots15. Instead of assessing binding kinetics one ligand or analyte concentration at a time, as is done in the traditional serial flow Biacore T100 platform, this approach offers the ability to monitor up to 36 different interactions simultaneously in a single binding cycle. 
Despite their differences, these four biosensor platforms are all widely used by many laboratories worldwide. For new users with little hands-on biosensor experience, deciding which instrument to use can be a challenging task given the differences in instrumental design. To determine the most appropriate instrument for their research purposes, factors such as data quality, performance consistency, throughput, ease of operation, and material consumption need to be considered collectively. While several benchmark studies have explored the variability of kinetic rate constants obtained from multiple laboratories and biosensors5,16, a recently published head-to-head comparison study further addresses the systematic factors that influence data reliability from the instrumental performance point of view17,18. The protocols supplied in this video focus on the experimental setup and procedures in detail, and are accompanied by the research article entitled, "Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics"17. These protocols are intended not only to help new biosensor users implement these instruments for their research purposes, but also to provide additional insights for current biosensor users regarding technical challenges and considerations in experimental designs for evaluating high-affinity antibody-antigen interactions.

<table><tbody><tr><td>Biacore T100 System</td><td>GE Healthcare</td><td>28975001</td><td>The T100 system has been upgraded to T200</td></tr><tr><td>CM5 Sensor Chip&amp;nbsp;</td><td>GE Healthcare</td><td>BR100012</td><td></td></tr><tr><td>BIAevaluation&amp;nbsp;</td><td>GE Healthcare</td><td></td><td>Version 4.1</td></tr><tr><td>Biacore T100 Control Software</td><td>GE Healthcare</td><td></td><td>The T100 control software has been upgraded to T200</td></tr><tr><td>Amine Coupling Kit</td><td>GE Healthcare</td><td>BR100050&amp;nbsp;</td><td>It contains: 750 mg 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC), 115 mg N-hydroxysuccinimide (NHS), 10.5 mL 1.0 M ethanolamine-HCl pH 8.5&amp;nbsp;</td></tr><tr><td>HBS-EP+ Buffer 10&amp;times;</td><td>GE Healthcare</td><td>BR100669</td><td>Concentrated stock solution&amp;nbsp;</td></tr><tr><td>Plastic Vials, o.d. 7 mm</td><td>GE Healthcare</td><td>BR100212&amp;nbsp;</td><td></td></tr><tr><td>Rubber Caps, type 3</td><td>GE Healthcare</td><td>BR100502</td><td></td></tr><tr><td>Plastic Vials and Caps, o.d. 11 mm</td><td>GE Healthcare</td><td>BR100214&amp;nbsp;</td><td></td></tr><tr><td>ProteOn XPR36 Protein Interaction Array System</td><td>Bio-Rad</td><td>1760100</td><td></td></tr><tr><td>ProteOn Manager Software&amp;nbsp;</td><td>Bio-Rad</td><td>1760200</td><td>Version 3.1.0.6</td></tr><tr><td>GLM Sensor Chip</td><td>Bio-Rad</td><td>1765012</td><td></td></tr><tr><td>Amine Coupling Kit</td><td>Bio-Rad</td><td>1762410</td><td>It includes EDAC (EDC), sulfo-NHS, ethanolamine HCl&amp;nbsp;</td></tr><tr><td>Regeneration and Conditioning Kit and Buffers</td><td>Bio-Rad</td><td>1762210</td><td>It includes 1 each glycine buffer (pH 1.5, 2.0, 2.5, 3.0), and NaOH, SDS, HCl, phosphoric acid, NaCl; 50 mL each solution&amp;nbsp;</td></tr><tr><td>2 L PBS/Tween/EDTA buffer</td><td>Bio-Rad</td><td>1762730</td><td>It includes hosphate buffered saline (PBS), pH 7.4, 0.005% Tween 20, 3 mM EDTA&amp;nbsp;</td></tr><tr><td>Octet RED384 System</td><td>Fort&amp;eacute;Bio</td><td></td><td></td></tr><tr><td>Data Analysis Software</td><td>Fort&amp;eacute;Bio</td><td></td><td>Version 9.0.0.4</td></tr><tr><td>Dip and Read Anti-hIgG Fc Capture (AHC) Biosensors</td><td>Fort&amp;eacute;Bio</td><td>18-5060</td><td>One tray of 96 biosensors&amp;nbsp;</td></tr><tr><td>384-Well Tilted-Bottom Plate&amp;nbsp;</td><td>Fort&amp;eacute;Bio</td><td>18-5080</td><td></td></tr><tr><td>Biosensor Dispenser</td><td>Fort&amp;eacute;Bio</td><td>18-5016</td><td></td></tr><tr><td>Kinetics Buffer 10x</td><td>Fort&amp;eacute;Bio</td><td>18-1092</td><td>10x concentration. Contains ProClin 300.&amp;nbsp;</td></tr><tr><td>IBIS MX96 SPRi System</td><td>Wasatch Microfluidics</td><td></td><td></td></tr><tr><td>Microfluidics Continuous Flow Microspotter (CFM) Printer</td><td>Wasatch Microfluidics</td><td></td><td>Version 2.0</td></tr><tr><td>SensEye COOH-G chip</td><td>Wasatch Microfluidics</td><td></td><td>1-09-04-004</td></tr><tr><td>Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.19.3.17</td></tr><tr><td>SPRint Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.15.2.1</td></tr><tr><td>Scrubber 2</td><td>BioLogic Software</td><td></td><td>Version 2</td></tr><tr><td>Pierce Recombinant Protein A/G</td><td>ThermoFisher Scientific</td><td>21186</td><td></td></tr></tbody></table>

determination of high-affinity antibody-antigen binding kinetics using four biosensor platforms

Label-free optical biosensors are powerful tools in drug discovery for the characterization of biomolecular interactions. In this study, we describe the use of four routinely used biosensor platforms in our laboratory to evaluate the binding affinity and kinetics of ten high-affinity monoclonal antibodies (mAbs) against human proprotein convertase subtilisin kexin type 9 (PCSK9). While both Biacore T100 and ProteOn XPR36 are derived from the well-established Surface Plasmon Resonance (SPR) technology, the former has four flow cells connected by serial flow configuration, whereas the latter presents 36 reaction spots in parallel through an improvised 6 x 6 crisscross microfluidic channel configuration. The IBIS MX96 also operates based on the SPR sensor technology, with an additional imaging feature that provides detection in spatial orientation. This detection technique coupled with the Continuous Flow Microspotter (CFM) expands the throughput significantly by enabling multiplex array printing and detection of 96 reaction sports simultaneously. In contrast, the Octet RED384 is based on the BioLayer Interferometry (BLI) optical principle, with fiber-optic probes acting as the biosensor to detect interference pattern changes upon binding interactions at the tip surface. Unlike the SPR-based platforms, the BLI system does not rely on continuous flow fluidics; instead, the sensor tips collect readings while they are immersed in analyte solutions of a 384-well microplate during orbital agitation.
Each of these biosensor platforms has its own advantages and disadvantages. To provide a direct comparison of these instruments&#39; ability to provide quality kinetic data, the described protocols illustrate experiments that use the same assay format and the same high-quality reagents to characterize antibody-antigen kinetics that fit the simple 1:1 molecular interaction model.

Figure 1 shows the antibody array image from the CFM and the spotted mAb levels by the two immobilization methods, and Figure 2 shows the corresponding binding sensorgrams generated in the MX96 from the multi-cycle kinetic and the single-cycle kinetic measurements on these mAb arrays. The real-time binding and kinetically fitted curves from multiple antibody-coated surfaces generated in the four biosensor platforms are shown in Figures 3 - 6. Figure 7 shows the comparison of the final kinetic rates and equilibrium binding constants obtained from the global analysis of these binding curves. The individual association (ka), dissociation (kd), and equilibrium (KD) binding constants are presented in Table 1. To demonstrate the variability of datasets generated within the same instrument, Figure 8 shows plots of ka, kd, and KD at different mAb surface densities, and Figure 9 further compares the calculated binding activities of the mAb surfaces across the biosensor platforms.
<img alt="Figure 1" src="/files/ftp_upload/55659/55659fig1.jpg" /> 
Figure 1. Multiplex Ligand Arrays of Amine-coupled (A) and Fc-captured (B) Antibody Surfaces from CFM Printing in the IBIS MX96. Images of the printed arrays are shown in the left panels, where the grey areas enclosed by red squares indicate the presence of antibody. The darker interspots located between the active antibody spots are used for reference subtraction. Each column contains an antibody printed at the titration concentrations identified below and to the left of the image. The amounts of the printed antibodies quantified by calculating the difference in bulk shifts between the active and reference locations are shown in the right panels. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/55659/55659fig2.jpg" /> 
Figure 2. Comparison of Real-time Binding Sensorgrams from Multi-cycle (A) and Single-cycle (B) Kinetic Experiments in the IBIS MX96. The sequential injections of human PCSK9 at increasing concentrations across the 10 x 8 antibody arrays are noted above each corresponding sensorgram segment. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/55659/55659fig3.jpg" /> 
Figure 3. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the Biacore T100. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid smooth black lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/55659/55659fig4.jpg" /> 
Figure 4. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the ProteOn XPR36. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid smooth black lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/55659/55659fig5.jpg" /> 
Figure 5. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the Octet RED384. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid red lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/55659/55659fig6.jpg" /> 
Figure 6. Binding Sensorgrams of the Amine-coupled (A) and Fc-captured (B) Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the IBIS MX96. The binding profiles are organized as 10 x 8 panels that follow the array plate map in Figure 1. The black lines represent the recorded binding response signals at different human PCSK9 concentrations, and the overlaid red lines represent the fitted curves. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/55659/55659fig7.jpg" /> 
Figure 7. Comparison of the Association ka (A), Dissociation kd (B), and Equilibrium KD (C) Binding Constants Generated by the Four Biosensor Platforms. The kinetic parameters are derived from global analysis of the binding curves in Figures 3 - 6. The instruments are represented as follows: Biacore T100 (blue), ProteOn XPR36 (green), Octet RED384 (red), IBIS MX96, amine-coupled (purple), and IBIS MX96, Fc-captured (orange). <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" src="/files/ftp_upload/55659/55659fig8.jpg" /> 
Figure 8. Comparison of the Consistency of Kinetic Rate Constants Over Multiple Antibody Surface Densities in the Biacore T100 (A), ProteOn XPR36 (B), Octet RED384 (C), IBIS MX96, amine-coupled (D), and IBIS MX96, Fc-captured (E). The kinetic parameters ka (top sub-panels), kd (middle sub-panels), and KD (bottom sub-panels) are derived from group analysis at individual antibody surface density. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" src="/files/ftp_upload/55659/55659fig9.jpg" /> 
Figure 9. Binding Activities of the Antibody Surfaces and Their Standard Deviations (error bars) in the Four Biosensor Platforms. The values are calculated using equations described in the research articles17. <a href="https://cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55659/55659fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2"></td>
			<td>ka</td>
			<td>kd</td>
			<td>KD</td>
		</tr>
		<tr>
			<td>(M-1s-1)</td>
			<td>(s-1)</td>
			<td>(nM)</td>
		</tr>
		<tr>
			<td>mAb 1</td>
			<td>11.7 (7.8) x 105</td>
			<td>4.89 (4.18) x 10-5</td>
			<td>0.052 (0.05)</td>
		</tr>
		<tr>
			<td>mAb 2</td>
			<td>1.53 (0.28) x 105</td>
			<td>1.30 (1.54) x 10-5</td>
			<td>0.092 (0.12)</td>
		</tr>
		<tr>
			<td>mAb 3</td>
			<td>11.4 (8.3) x 105</td>
			<td>27.6 (11.0) x 10-5</td>
			<td>0.333 (0.20)</td>
		</tr>
		<tr>
			<td>mAb 4</td>
			<td>3.61 (1.6) x 105</td>
			<td>20.1 (12.3) x 10-5</td>
			<td>0.659 (0.54)</td>
		</tr>
		<tr>
			<td>mAb 5</td>
			<td>0.59 (0.21) x 105</td>
			<td>3.46 (2.50) x 10-5</td>
			<td>0.663 (0.46)</td>
		</tr>
		<tr>
			<td>mAb 6</td>
			<td>1.19 (0.78) x 105</td>
			<td>7.21 (3.83) x 10-5</td>
			<td>0.894 (0.64)</td>
		</tr>
		<tr>
			<td>mAb 7</td>
			<td>1.29 (0.53) x 105</td>
			<td>16.4 (5.63) x 10-5</td>
			<td>1.57 (1.02)</td>
		</tr>
		<tr>
			<td>mAb 8</td>
			<td>4.02 (2.23) x 105</td>
			<td>22.8 (10.7) x 10-5</td>
			<td>0.768 (0.68)</td>
		</tr>
		<tr>
			<td>mAb 9</td>
			<td>4.20 (2.13) x 105</td>
			<td>6.67 (4.3) x 10-5</td>
			<td>0.197 (0.16)</td>
		</tr>
		<tr>
			<td>mAb 10</td>
			<td>1.20 (0.49) x 105</td>
			<td>12.5 (7.64) x 10-5</td>
			<td>1.27 (0.80)</td>
		</tr>
	</tbody>
</table>
Table 1: Kinetic Rates and Equilibrium Binding Constants of 10 mAbs Obtained by Global Fitting of Binding Curves from Four Biosensor Instruments to the 1:1 Interaction Model.

Watch this Scientific Journal Video about Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms at JoVE.com

Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

We describe here protocols for the measurement of antibody-antigen binding affinity and kinetics using four commonly used biosensor platforms.

Label-free optical biosensors are powerful tools in drug discovery for the characterization of biomolecular interactions. In this study, we describe the ...

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Nanyang Technological University

Research

JoVE Journal

Biochemistry

20.6K Views.  Boehringer Ingelheim Pharmaceuticals, Inc.. We describe here protocols for the measurement of antibody-antigen binding affinity and kinetics using four commonly used biosensor platforms.

Video: Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

Bio-layer Interferometry for Measuring Kinetics of Protein-protein Interactions and Allosteric Ligand Effects

We describe the use of Bio-layer Interferometry to study inhibitory interactions of subunit &#949;&#160;with the catalytic complex of Escherichia coli&#160;ATP synthase. Bacterial F-type ATP synthase is the target of a new, FDA-approved antibiotic to combat drug-resistant tuberculosis. Understanding bacteria-specific auto-inhibition of ATP synthase by the C-terminal domain of subunit &#949;&#160;could provide a new means to target the enzyme for discovery of antibacterial drugs. The C-terminal domain of &#949;&#160;undergoes a dramatic conformational change when the enzyme transitions between the active and inactive states, and catalytic-site ligands can influence which of &#949;&#39;s conformations is predominant. The assay measures kinetics of &#949;&#39;s binding/dissociation with the catalytic complex, and indirectly measures the shift of enzyme-bound &#949;&#160;to and from the apparently nondissociable inhibitory conformation. The Bio-layer Interferometry signal is not overly sensitive to solution composition, so it can also be used to monitor allosteric effects of catalytic-site ligands on &#949;&#39;s conformational changes.

The protocols here describe kinetic assays of protein-protein interactions with Bio-layer Interferometry. F-type ATP synthase, which is involved in cellular energy metabolism, can be inhibited by its &#949; subunit in bacteria. We have adapted Bio-layer Interferometry to study interactions of the catalytic complex with &#949;&#8217;s inhibitory C-terminal domain.

We describe the use of Bio-layer Interferometry to study inhibitory interactions of subunit &#949;&#160;with the catalytic complex of Escherichia ...

Chemistry

An ELISA Based Binding and Competition Method to Rapidly Determine Ligand-receptor Interactions

A comprehensive understanding of signaling pathways requires detailed knowledge regarding ligand-receptor interaction. This article describes two fast and reliable point-by-point protocols of enzyme-linked immunosorbent assays (ELISAs) for the investigation of ligand-receptor interactions: the direct ligand-receptor interaction assay (LRA) and the competition LRA. As a case study, the ELISA based analysis of the interaction between different lambda interferons (IFNLs) and the alpha subunit of their receptor (IL28RA) is presented: the direct LRA is used for the determination of dissociation constants (KD values) between receptor and IFN ligands, and the competition LRA for the determination of the inhibitory capacity of an oligopeptide, which was designed to compete with the IFNLs at their receptor binding site. Analytical steps to estimate KD and half maximal inhibitory concentration (IC50) values are described. Finally, the discussion highlights advantages and disadvantages of the presented method and how the results enable a better molecular understanding of ligand-receptor interactions.

The presented protocols describe two enzyme-linked immunosorbent assay (ELISA) based techniques for the rapid investigation of ligand-receptor interactions: The first assay allows the determination of dissociation constant between ligand and receptor. The second assay enables a rapid screening of blocking peptides for ligand-receptor interactions.

A comprehensive understanding of signaling pathways requires detailed knowledge regarding ligand-receptor interaction. This article describes two fast and ...

Characterization of Glycoproteins with the Immunoglobulin Fold by X-Ray Crystallography and Biophysical Techniques

Glycoproteins on the surface of cells play critical roles in cellular function, including signalling, adhesion and transport. On leukocytes, several of these glycoproteins possess immunoglobulin (Ig) folds and are central to immune recognition and regulation. Here, we present a platform for the design, expression and biophysical characterization of the extracellular domain of human B cell receptor CD22. We propose that these approaches are broadly applicable to the characterization of mammalian glycoprotein ectodomains containing Ig domains. Two suspension human embryonic kidney (HEK) cell lines, HEK293F and HEK293S, are used to express glycoproteins harbouring complex and high-mannose glycans, respectively. These recombinant glycoproteins with different glycoforms allow investigating the effect of glycan size and composition on ligand binding. We discuss protocols for studying the kinetics and thermodynamics of glycoprotein binding to biologically relevant ligands and therapeutic antibody candidates. Recombinant glycoproteins produced in HEK293S cells are amenable to crystallization due to glycan homogeneity, reduced flexibility and susceptibility to endoglycosidase H treatment. We present methods for soaking glycoprotein crystals with heavy atoms and small molecules for phase determination and analysis of ligand binding, respectively. The experimental protocols discussed here hold promise for the characterization of mammalian glycoproteins to give insight into their function and investigate the mechanism of action of therapeutics.

We present approaches for the biophysical and structural characterization of glycoproteins with the immunoglobulin fold by biolayer interferometry, isothermal titration calorimetry, and X-ray crystallography.

Glycoproteins on the surface of cells play critical roles in cellular function, including signalling, adhesion and transport. On leukocytes, several of ...

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the dissection and manipulation of biological pathways. Currently, only a limited number of chemically induced dimerization (CID) systems exist and engineering new ones with desired sensitivity and selectivity for specific small-molecule ligands remains a challenge in the field of protein engineering. We here describe a high throughput screening method, combinatorial binders-enabled selection of CID (COMBINES-CID), for the de novo engineering of CID systems applicable to a large variety of ligands. This method uses the two-step selection of a phage-displayed combinatorial nanobody library to obtain 1) &#34;anchor binders&#34; that first bind to a ligand of interest and then 2) &#34;dimerization binders&#34; that only bind to anchor binder-ligand complexes. To select anchor binders, a combinatorial library of over 109 complementarity-determining region (CDR)-randomized nanobodies is screened with a biotinylated ligand and hits are validated with the unlabeled ligand by bio-layer interferometry (BLI). To obtain dimerization binders, the nanobody library is screened with anchor binder-ligand complexes as targets for positive screening and the unbound anchor binders for negative screening. COMBINES-CID is broadly applicable to select CID binders with other immunoglobulin, non-immunoglobulin, or computationally designed scaffolds to create biosensors for in vitro and in vivo detection of drugs, metabolites, signaling molecules, etc.

Creating chemically induced protein dimerization systems with desired affinity and specificity for any given small molecule ligand would have many biological sensing and actuation applications. Here, we describe an efficient, generalizable method for de novo engineering of chemically induced dimerization systems via the stepwise selection of a phage-displayed combinatorial single-domain antibody library.

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the ...

Rapid Determination of Antibody-Antigen Affinity by Mass Photometry

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this protocol, we describe the implementation of a new single-molecule technique, mass photometry (MP), for this purpose. MP is a label- and immobilization-free technique that detects and quantifies molecular masses and populations of antibodies and antigen-antibody complexes on a single-molecule level. MP analyzes the antigen-antibody sample within minutes, allowing for the precise determination of the binding affinity and simultaneously providing information on the stoichiometry and the oligomeric state of the proteins. This is a simple and straightforward technique that requires only picomole quantities of protein and no expensive consumables. The same procedure can be used to study protein-protein binding for proteins with a molecular mass larger than 50 kDa. For multivalent protein interactions, the affinities of multiple binding sites can be obtained in a single measurement. However, the single-molecule mode of measurement and the lack of labeling imposes some experimental limitations. This method gives the best results when applied to measurements of sub-micromolar interaction affinities, antigens with a molecular mass of 20 kDa or larger, and relatively pure protein samples. We also describe the procedure for performing the required fitting and calculation steps using basic data analysis software.

We describe a single-molecule approach to antigen-antibody affinity measurements using mass photometry (MP). The MP-based protocol is fast, accurate, uses a very small amount of material, and does not require protein modification.

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this ...

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Biomolecular interactions play versatile roles in numerous cellular processes&#160;by regulating and coordinating functionally relevant biological events. Biomolecules such as proteins, carbohydrates, vitamins, fatty acids, nucleic acids, and enzymes are fundamental building blocks of living beings; they assemble into complex networks in biosystems to synchronize a myriad of life events. Proteins typically utilize complex interactome networks to carry out their functions; hence it is mandatory to evaluate such interactions to unravel their importance in cells at both cellular and organism levels. Toward this goal, we introduce a rapidly emerging technology, field-effect biosensing (FEB), to determine specific biomolecular interactions. FEB is a benchtop, label-free, and reliable biomolecular detection technique to determine specific interactions and uses high-quality electronic-based biosensors. The FEB technology can monitor interactions in the nanomolar range due to the biocompatible nanomaterials used on its biosensor surface. As a proof of concept, the protein-protein interaction (PPI) between heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) was elucidated. Hsp90 is an ATP-dependent molecular chaperone that plays an essential role in the folding, stability, maturation, and quality control of many proteins, thereby regulating multiple vital cellular functions. Cdc37 is regarded as a protein kinase-specific molecular chaperone, as it specifically recognizes and recruits protein kinases to Hsp90 to regulate their downstream signal transduction pathways. As such, Cdc37 is considered a co-chaperone of Hsp90. The chaperone-kinase pathway (Hsp90/Cdc37 complex) is hyper-activated in multiple malignancies promoting cellular growth; therefore, it is a potential target for cancer therapy. The present study demonstrates the efficiency of FEB technology using the Hsp90/Cdc37 model system. FEB detected a strong PPI between the two proteins (KD values of 0.014 &#181;M, 0.053 &#181;M, and 0.072 &#181;M in three independent experiments). In summary, FEB is a label-free and cost-effective PPI detection platform, which offers fast and accurate measurements.

Field-effect biosensing (FEB) is a label-free technique for detecting biomolecular interactions. It measures the electric current through the graphene biosensor to which the binding targets are immobilized. The FEB technology was used to evaluate biomolecular interactions between Hsp90 and Cdc37 and a strong interaction between the two proteins was detected.

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The Use of a &#946;-lactamase-based Conductimetric Biosensor Assay to Detect Biomolecular Interactions

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental monitoring, and food safety control. In this context, we used &#946;-lactamases as efficient reporter enzymes in several protein-protein interaction studies. Furthermore, their ability to accept insertions of peptides or structured proteins/domains strongly encourages the use of these enzymes to generate chimeric proteins. In a recent study, we inserted a single-domain antibody fragment into the Bacillus licheniformis BlaP &#946;-lactamase. These small domains, also called nanobodies, are defined as the antigen-binding domains of single chain antibodies from camelids. Like common double chain antibodies, they show high affinities and specificities for their targets. The resulting chimeric protein exhibited a high affinity against its target while retaining the &#946;-lactamase activity. This suggests that the nanobody and &#946;-lactamase moieties remain functional. In the present work, we report a detailed protocol that combines our hybrid &#946;-lactamase system to the biosensor technology. The specific binding of the nanobody to its target can be detected thanks to a conductimetric measurement of the protons released by the catalytic activity of the enzyme.

In this work, we report a new method to study protein-protein interactions using a conductimetric biosensor based on the hybrid &#946;-lactamase technology. This method relies on release of protons upon hydrolysis of &#946;-lactams.

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental ...

Bioengineering

Quantitative Analysis of RPA-ssDNA Binding Kinetics Using Label-Free Methods

Analyzing DNA-Protein Interactions with Streptavidin-Based Biolayer Interferometry

Protein-DNA interactions underpin essential cellular processes. Understanding these interactions is critical for elucidating the molecular mechanisms of various pathways. Key factors such as the structure, sequence, and length of a DNA molecule can significantly influence protein binding. Bio-layer interferometry (BLI) is a label-free technique that measures binding kinetics between molecules, offering a straightforward and precise approach to quantitatively study protein-DNA interactions. A major advantage of BLI over traditional gel-based methods is its ability to provide real-time data on binding kinetics, enabling accurate measurement of the equilibrium dissociation constant (KD) for dynamic protein-DNA interactions. This article presents a basic protocol for determining the KD value of the interaction between a DNA replication protein, replication protein A (RPA), and a single-stranded DNA (ssDNA) substrate. RPA binds ssDNA with high affinity but must also be easily displaced to facilitate subsequent protein interactions within biological pathways. In the described BLI assay, biotinylated ssDNA is immobilized on a streptavidin-coated biosensor. The binding kinetics (association and dissociation) of RPA to the biosensor-bound DNA are then measured. The resulting data are analyzed to derive precise values for the association rate constant (ka), dissociation rate constant (kd), and equilibrium binding constant (KD) using system software.

This article describes a protocol for studying DNA-protein interactions using a streptavidin-based biolayer interferometry (BLI) system. It outlines the essential steps and considerations for utilizing either basic or advanced binding kinetics to determine the equilibrium binding affinity (KD) of the interaction.

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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Receptors and enzyme proteins are important biomolecules that act as binding targets for bioactive small molecules. Thus, the rapid and global validation of the drug-protein interactions is highly desirable for not only understanding the molecular mechanisms underlying therapeutic efficacy but also for assessing drug characteristics, such as adsorption, distribution, metabolism, excretion, and toxicity (ADMET) for clinical use. Here, we present a biosensor-based high throughput strategy for the biopanning of T7 phage-displayed short peptides that can be easily displayed on the phage capsid. Subsequent analysis of the amino acid sequences of peptides containing short segments, as &#34;broken relics&#34;, of the drug-binding sites using bioinformatics programs in receptor ligand contact (RELIC) suite, is also shown. By applying this method to two clinically approved drugs, an anti-tumor irinotecan, and an anti-flu oseltamivir, the detailed process for collecting the drug-recognizing peptide sequences and highlighting the drug-binding sites of the target proteins are explained in this paper. The strategy described herein can be applied for any small molecules of interest.

This study aimed to present a strategy for identifying drug-peptide interactions. The strategy involves the biopanning of drug-recognizing short peptides based on a quartz-crystal microbalance (QCM) biosensor, followed by bioinformatics analysis for quantitatively assessing the information obtained for the drug recognition and annotation of the drug-binding sites on proteins.

Receptors and enzyme proteins are important biomolecules that act as binding targets for bioactive small molecules. Thus, the rapid and global validation ...

High-Sensitivity Detection of Compound-Protein Binding Using Fluorescence

Detection of CD40 Protein-Umbelliferone Interaction via Differential Scanning Fluorescence

The investigation of interactions between different molecules is a crucial aspect of understanding disease pathogenesis and screening for drug targets. Umbelliferone, an active ingredient in Tibetan medicine Vicatia thibetica, exhibits an immunomodulatory effect with an unknown mechanism. The CD40 protein is a key target in the immune response. Therefore, this study employs the principle of differential scanning fluorescence technology to analyze the interactions between CD40 protein and umbelliferone using fluorescent enzyme markers. Initially, the stability of the protein fluorescent orange dye was experimentally verified, and the optimal dilution ratio of 1:500 was determined. Subsequently, it was observed that the temperature melting (Tm) value of CD40 protein tended to decrease with an increase in concentration. Interestingly, the interaction between CD40 protein and umbelliferone was found to enhance the thermal stability of CD40 protein. This study represents the first attempt to detect the binding potential of small molecule compounds and proteins using fluorescence microplates and fluorescent dyes. The technique is characterized by high sensitivity and accuracy, promising advancements in the fields of protein stability, protein structure, and protein-ligand interactions, thus facilitating further research and exploration.

Author Spotlight: Streamlining PCR Methods for Enhanced Accessibility and Efficiency

This protocol describes a unique method for detecting the binding between compounds and protein molecules, offering the advantages of minimal protein sample loss and high data accuracy.

The investigation of interactions between different molecules is a crucial aspect of understanding disease pathogenesis and screening for drug targets. ...