Octet Kinetics Assay: Method Development Guideline | Fortebio

Octet Kinetics Assay: Method Development Guideline | Fortebio

Octet kinetics assay: method development guideline 1. Purpose 3. General assay development sequence 1.1 The purpose of this document is to describe the procedure See Figure 1. for developing a ligand binding kinetics assay on Octet® i Ligand (capture) and analyte molecules assignment QKe, RED96, RED96e, RED384 and HTX instruments. The procedures described are for developing binding kinetics ii Biosensor hydration assays for release testing of product batches and relat- iii Ligand optimal density scouting ed applications. The document is intended as a general iv Assay buffer optimization guideline only. Actual method development procedures v Analyte binding optimization may be different as they may be product dependent. vi Assay robustness and specifications testing 1.2 The procedures are aimed at developing kinetics binding assays to establish specificity, accuracy, precision, linearity 4. Ligand and biosensor selection and range as stipulated by the USP 1032 requirements for ligand binding assays. Determine which of the two binding molecules should be assigned as the ligand (for loading/capture/immobilization onto the biosensor surface). Generally, the larger molecule 2. Materials required should be selected as the analyte unless it is an antibody. • ForteBio biosensors: Any part number relevant to the 4.1 Ligand selection. It is recommended that the antibody be capture molecule selected as the ligand for an antibody-antigen interaction • Ligand/receptor/capture molecule: Molecule to be immo- to avoid antibody avidity effects. bilized onto the biosensor surface 4.2 Biosensor selection. When one binding partner has an • Product/analyte:As needed intrinsic tag such as a HIS or GST tag, assign that molecule • 10X Kinetics Buffer (KB) Part No. 18-1092 as the ligand. In this case, an anti-tag biosensor should be • Other assay buffers as needed selected for use. However, in cases of high affinity binding, • Black 96 or 384-well plates:Greiner catalog numbers some anti-tag biosensors may not be appropriate. In such 655209 and 781209 for 96-well and 384-well plates cases, it is recommended that one of the partner mole- respectively. cules be biotinylated and High Precision Streptavidin (SAX) biosensors used for the studies. Note: 96 well plates require 200 µL of reagents or sample while 384-well plates require a minimum of 40 or 80 µL for Note: refer to ForteBio Technical Note 28: Biotinylation of the round and flat bottom plates, respectively Protein for Immobilization onto Streptavidin Biosensors for biotinylation procedures. 1 Assign ligand and analyte based on MW, and tag If no tag is present biotinylate selected ligand and select high precision If tag is present, select streptavidin biosensors (SAX) appropriate biosensor for ligand immobilization Select assay matrix based Perform ligand optimal Perform dose on product stability density studies response studies and assay needs Figure 1: Overview of suggested ligand binding assay sequence on the Octet platform. 5. Biosensor hydration 6. Ligand density scouting 5.1 Hydration plate preparation. The purpose of the load scouting experiment is to assess the optimal loading/capture/immobilization molecule con- Note: While ForteBio recommends the use of 1X Kinetics centration that results in adequate analyte binding without Buffer, binding molecule stability and activity should dic- the introduction of assay artifacts. Assay artifacts could tate the selection of assay buffer. include an undesired drift in the baseline immediately fol- Pipette buffer only into wells corresponding to the number lowing ligand capture, or an undesired biphasic behavior in of biosensors intended for immediate use. Hydrate the the analyte dissociation step such as an initial fast off-rate biosensors passively on the lab bench. (undesired) followed by a slower rate. 5.2 Hydration optimization. Biosensor hydration is typically 6.1 Hydrate the selected biosensors as established in recommended for a minimum of 10 minutes but may need Section 5. to be optimized. Optimal hydration should result in minimal 6.2 Pipette at least three different ligand molecule concen- drift in the baseline step of the assay. To optimize hydra- trations in duplicate into a 96- or 384-well sample plate tion, select three different hydration times. Use at least two targeting low density, mid density and high density. It biosensors per condition to allow for replicates and stag- is recommended that the mid density concentration be ger the hydration to enable simultaneous evaluation on the approximately 150 nM of the ligand based on a 5-minute instrument. Recommended hydration times to evaluate are loading time. High- and low-density concentrations can be 5, 10 and 20 minutes. estimated from this value. Select a constant concentration Note: Actual total biosensor hydration time will depend on of product/analyte to test for binding against each ligand the instrument equilibration setting used prior to the start concentration. As some estimate of the expected KD is of the experiment. This is typically set at 10 minutes. required, the analyte concentration should be estimated at above the expected K , typically 10–20X of the expected Pipette 200 µL of assay buffer into the biosensor hydration D K . If the K is unknown, use a high analyte concentration. plate and an appropriate volume into corresponding wells D D of the sample plate. Perform a baseline step assay (recom- Note: Analyte solubility in the chosen sample matrix may mended time is 2–5 minutes but could be longer). Select limit analyte concentration. the hydration time and baseline step time conditions where the assay baseline drift is minimized and establish this as the optimal hydration time for the rest of the studies. 2 6.3 Perform the load scouting binding assay in this sequence: 7.4 Run a full binding experiment in the sequence: baseline baseline, loading, baseline 2, association and dissociation. (2–5 minutes), loading (5–10 minutes), baseline 2 (2–5 Assay step times should be developed and will depend minutes), association (5–10 minutes) and dissociation on the expected KD of the binding partners. The baseline (2–10 minutes). Actual binding assay step time will de- 2 step time should be optimized to establish a step time pend on the analyte. For each assay condition, include a with minimal drift, i.e. extend assay step time, to achieve negative control where all steps identical except the an- minimal drift prior to the biosensor dipping into analyte for alyte concentration which should be 0 M (buffer or matrix association time. without product/analyte). Note: The Octet Data Acquisition software allows the user to extend an assay step time or move the steps earlier 8. Analyte binding than initially set based on real-time data observation. This Kinetic binding assays should demonstrate binding curva- feature is especially useful during assay development and ture at the top concentrations evaluated, typically concen- should be used during these scouting experiments. trations above the expected KD. A dose response analysis 6.4 Select the lowest ligand concentration that a) results in should be performed with at least 3–5 data points. An an optimal analyte binding response and b) that does not ideal binding profile should have at least two data points below the expected K and two data points above the ex- introduce artifacts in the dissociation step to use for fur- D pected K . It should be noted that this may not be possible ther method development. Optimal analyte response may D be dependent on analyte molecular weight but should in some cases where the analyte is small but the bind- produce appreciable signals to allow for a dose response ing affinity between the two molecules is high (pM). The analysis during analyte titration. analyte should be prepared in the same buffer or matrix as previously determined. Multiple lots of the analyte should be tested to demonstrate assay reproducibility. 7. Assay buffer optimization 8.1 Prepare serial dilutions of the analyte in replicates in the It should be noted that assay buffer/matrix can affect same assay buffer or matrix. The serial dilution could be assay performance. A mini design of experiment (DOE) either 2-fold or 3-fold but should be scouted to establish to scout for optimal assay buffer should be performed data with the binding curvature at the high concentration keeping in mind the desired analyte stability. Ideally, the points and appreciable binding at concentrations lower assay should be run using analyte sample matrix. Howev- than the reported K . er, sample dilution may be necessary if the sample matrix D causes interference with the assay. 8.2 Establish assay shaking speed. The recommended shake speed for Octet binding assays is 1000 RPM. The shake 7.1 Select different buffers or sample matrix conditions to speed may however need to be scouted and optimized evaluate for assay performance. Conditions may include depending on sample type. For example, for virus-like different pH, ionic strength, detergent types and amounts, samples, the optimal shake speed may be lower (typi- etc. Selection of the conditions to evaluate should cally ~ 400 RPM). Shake speed evaluation should aim at depend on the biophysical properties of the binding achieving differentiation of analyte binding response as a molecules, i.e. when the molecules are highly charged, function of concentration. To evaluate shake speed, keep pH and ionic strength of the buffer may be evaluated all assay conditions constant while changing the shake to determine optimal conditions. When the molecule is speed. Evaluate three different shake speeds; 1000 RPM, highly hydrophobic, detergents should be evaluated and 600 RPM, and 400 RPM. spiked into the base buffer. 8.3 Use the established assay conditions and parameters to 7.2 Design a mini DOE with the buffer conditions as the establish analyte association and dissociation step times. variables. The design space may be wider for initial An ideal top analyte concentration should result in binding DOE variables but should be tightened for optimization.

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