A Sensorgram


A sensorgram

In the previous pages you have learned what the important parts are of the curves and sensorgrams, the following figures show a low and a high-quality sensorgram.

Low quality sensorgram
Low quality sensorgram

High quality sensorgram
High quality sensorgram

In conclusion: what to look for before you attempt a fitting on a set of curves?

  • The baseline is flat. When the running buffer is flowing, the drift of the baseline is close to zero.
  • On injection of the analyte, the buffer jump is very low.
  • The association is free of mass transport.
  • The curves are following the single exponential
  • The curves have sufficient curvature
  • There is at least one replicate
  • The analyte concentration is around 0.1 – 10 times the expected KD
  • The curves are well spaced in the sensorgram
  • At least one of the curves is reaching steady state (when possible)
  • The overall response is low
  • The response is proportional to the analyte concentration and kinetics
  • The dissociation is long enough to decay a sufficient amount in response
  • The injections were randomized to avoid systematic errors

When the curves are not high quality, you must optimize the experimental conditions before attempting any fitting. Fitting on bad curves will give you bad answers and waste your time. Therefore, start optimizing (1).

One of the drawbacks of the immobilisation is that the ligand is random orientated on the sensor chip surface. This can lead to difficulty in solving interactions. As an alternative, the ligand can be captured with an antibody. When a protein has a specific sequence like the 6xHIS or a FLAG-tag the capture approach is very easy. Other steps you can take:

  • check ligand and analyte for purity and uniformity
  • lower ligand density on the sensor chip
  • increase flow rate to check for mass transport
  • reverse ligand and analyte on the sensor chip
  • change the immobilization chemistry (e.g. thiol coupling)
  • add or remove salts
  • add or remove detergents

References

(1)Rich, R. L. and Myszka, D. G. Survey of the year 2007 commercial optical biosensor literature. J.Mol.Recognit. 21: 355-400; (2008). Goto reference