How to Make Your Surface Plasmon Resonance Experiments Successful

The technique of Surface Plasmon Resonance (SPR), allows scientists to monitor biomolecular binding interactions label-free, in real-time and using automation. Unlike many other techniques that provide information only on the start and end points of a binding experiment, SPR can be used to measure association (on) and dissociation (off) rate constants as well as the equilibrium dissociation constant (K_D). Life science applications include antibody characterization, interaction proteomics, biopharmaceuticals and biogenerics. In the drug development process, SPR plays an important role - it provides valuable insight from the Drug Discovery process (often starting with simple yes/no binding) all the way to the determination of proper dosing in patients (where knowing kinetics (on and off rates) is critical).

Researchers can study all classes of biomolecules using SPR including: proteins, peptides, DNA/RNA, lipids, carbohydrates, small molecules, cells and bacteria. In addition to being used for affinity and kinetics analysis, SPR can also be used for thermodynamic studies and as a very precise and accurate method for determining the concentration of a biomolecule (concentration analysis).

For those of you thinking about, or planning on, using SPR, we offer insights on how to use the technique successfully, gained from working with this technique for a number of years:

Planning the Experiment and Sample Preparation

• (Note: we will use the following terminology - the half of the binding pair that will be attached to the sensor chip surface is the target. The other half of the binding pair flowing over the surface is the analyte.)
• First, determine how you will couple your target to the sensor chip surface. To start, select either coupling or capture chemistry – (if you aren’t sure which to try first, there are plenty of resources to guide you,[1]^,[2] determining the type of experiment will also help you choose the proper chip³). Keep in mind that you do not want to couple your target to the surface near the binding pocket on the molecule.
• Before you begin your experiment, estimate the maximum response you can expect from your experiment (assuming one-to-one binding). Divide the molecular weight of your analyte by the molecular weight of the target, then multiply by the amount of target you would like to couple or capture on the chip. You should aim for the maximum response to be at least 50-100 for initial experiments.
• Use only active, fresh targets and analytes to maximize binding efficiency
• Be sure to spin down samples prior to dilution in the running buffer. Centrifuging samples for one or two minutes will prevent significant problems later on (e.g. clogged tubing).
• Degas your running buffer thoroughly before starting an experiment, use an in-line degasser if available, and eliminate air from all injections. Air passing over the flow cell can cause dropped data points, variable responses, or a total loss of response.
• Use additives such as Tween, NaCl or BSA to reduce non-specific binding.
  
  Successful runs
  
• Eliminate carryover. One or two washes between injections will typically suffice, but if you’re analyzing sticky samples or using concentrated regeneration solutions, three or more may be needed. Do a buffer injection after the washes are complete to make sure there is no carryover.
• Minimize mass transport. Run the assay at a higher flow rate, or immobilize the target molecule at a low density on the sensor chip surface. This will make the association kinetics more accurate, and the probability of analyte rebinding during the dissociation phase will also be minimized when target immobilization levels are low.
• Be sure to run replicates, blanks and at least four or five sample concentrations. For replicates, we recommend re-injecting samples two or three times. Repeatability of the sample responses indicates that the protein is stable on the surface and that the regeneration solution used is not causing denaturation. Blank injections can help correct for baseline problems (e.g. a decaying baseline in a capture experiment). Injection of samples at multiple concentrations increases the accuracy of the kinetic fits.
• Repeat the experiment on multiple days. Comparing results from repeat experiments will increase confidence in the quality and trustworthiness of the data.
• At the end of your experiment, don’t forget to clean the instrument thoroughly. Contamination of the instrument and the tubing can lead to errant results the next time you run or you can cause damage to the instrument (e.g. if there is salt buildup from buffers).
  
  Data Analysis
  
• Be sure to have curvature in the association part of the sensorgram. For accurate kinetics, the maximum response needs to be reached with your highest concentration analyte injections, or be capable of being calculated.
• To determine an accurate dissociation rate (k_d), you need to observe at least a 10% decrease in the dissociation signal. If needed, increase the dissociation time until you see the 10% decrease.
• We recommend global fits of data. When doing a global fit of SPR sensorgrams, pay close attention to the residuals – you want them to be minimal and random.
• While it may be tempting, resist the urge to adapt the model to make up for problematic sensorgram shapes (e.g. inappropriately apply bulk shift corrections in the fitting program). If you’re following good practices, this should be a rare event.
• Keep in mind, even the best thought out experiment doesn’t always go according to plan. If the data cannot be fit to a model, or globally, you should consider changing how you run the experiment – switch which half of the binding pair is coupled, or change the experiment from covalent coupling to capture.
  

  Final Thought
  When publishing results, provide all the details needed for someone to repeat the experiment. Show sensorgrams with kinetic fits and include details like how much target was coupled to the surface and at what concentration, what was used for regeneration, etc. This thoroughness will be appreciated by users trying to replicate your results or others using your paper as a reference point to run similar samples.