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Guide

Decoding SPR Sensorgrams

A field guide to every sensorgram shape we've seen across hundreds of labs in 15+ countries — what it means, and how to fix it.

Covers14 curve shapes
GroupsSetup · Assay · Operational
How to usePick what you see, read the fix

The 5 Phases of a Sensorgram (BASDR)

A sensorgram through its five phases: baseline, association, steady state, dissociation, regenerationOriginal sketch of the five phases, with the molecules at each step
One binding cycle: baseline in buffer, the analyte arriving and binding, a steady state, the analyte leaving in buffer, then regeneration resets the surface.

Reading the cards: what you see   what you would expect   injection   the problem

B

Baseline

Buffer flows over the sensor, establishing a stable reference signal.

A

Association

Analyte moves to the surface via mass transport and binds to the ligand.

S

Steady-State

Net rate of bound analyte is zero. Saturation may or may not be reached.

D

Dissociation

Buffer returns; analyte dissociates from the ligand.

R

Regeneration

Low pH buffer removes remaining bound analyte to restore the surface.

What are you seeing?

Part 1

Setup & Ligand Issues

Problems with ligand immobilization, regeneration, and sensor chip preparation.

Insufficient Ligand Immobilization: example sensorgramInsufficient Ligand Immobilization: original sketch

SETUP

Insufficient Ligand Immobilization

No signal

What you see

  • Low or no RU response after analyte is flowed
  • Flat sensorgram with no binding signal

What to try

  • Increase ligand concentration
  • Increase coupling time
  • Change surface chemistry
Incomplete Surface Regeneration: example sensorgramIncomplete Surface Regeneration: original sketch

SETUP

Incomplete Surface Regeneration

Baseline rising

What you see

  • Analyte not fully cleared between cycles
  • Progressive baseline increase across runs
  • Reduced binding capacity in subsequent cycles

What to try

  • Optimize regeneration buffer composition, pH, and ionic strength
  • Follow with original running buffer to re-establish baseline
  • Check for non-specific binding; increase flow rate and regeneration time
Rebinding Effects: example sensorgramRebinding Effects: original sketch

SETUP

Rebinding Effects

Slow dissociationPoor model fit

What you see

  • Analyte rebinds to nearby ligands after dissociation
  • Dissociation does not follow a single exponential
  • Baseline never recovered in dissociation phase

What to try

  • Decrease ligand density on sensor; increase flow rates
  • Use single-cycle kinetics
  • Inject soluble ligand as competitor during dissociation
Noisy Data: example sensorgramNoisy Data: original sketch

SETUP

Noisy Data

Noisy data

What you see

  • High noise obscuring binding signal
  • Erratic RU fluctuations across the entire run

What to try

  • Increase analyte concentration
  • Increase amount of immobilized ligand on sensor

Part 2

Assay Issues

Issues arising from analyte preparation, buffer composition, and assay conditions.

Buffer Mismatch (Bulk Shift): example sensorgramBuffer Mismatch (Bulk Shift): original sketch

ASSAY

Buffer Mismatch (Bulk Shift)

High signalPoor model fit

What you see

  • Square-shaped artifact in the binding curve
  • Large, rapid RU changes at start and end of injection
  • Analyte and running buffer compositions differ

What to try

  • Match analyte buffer components with running buffer
  • Dialyze or filter analyte into the same running buffer
  • Run buffer-only reference and subtract from analyte experiment
Carryover Between Cycles: example sensorgramCarryover Between Cycles: original sketch

ASSAY

Carryover Between Cycles

Baseline risingSpikes / drops

What you see

  • Baseline increases across subsequent cycles
  • Sudden buffer jumps or spikes at the start of analyte injection
  • Often caused by high salt or sticky analyte

What to try

  • Verify complete regeneration between cycles
  • Reformulate analyte buffer
  • Add extra washing steps between injections
Analyte Aggregation: example sensorgramAnalyte Aggregation: original sketch

ASSAY

Analyte Aggregation

High signalNoisy dataSpikes / dropsPoor model fitSlow dissociation

What you see

  • Erratic, irregular or noisy binding curves
  • Sharp transient spikes or jumps in signal
  • Abnormally high RU and poor model fitting

What to try

  • Check protein folding and monodispersity
  • Reformulate analyte buffer; replenish with fresh soluble analyte
  • Filter or centrifuge to remove aggregates before injection
Mass Transport Limitations (MTL): example sensorgramMass Transport Limitations (MTL): original sketch

ASSAY

Mass Transport Limitations (MTL)

Poor model fitSlow dissociation

What you see

  • Slow, gradual RU increase during association — faster at higher flow rates
  • Analyte diffusion slower than binding rate
  • Poor data modeling at low analyte concentrations

What to try

  • Use higher flow rates and low-viscosity buffer
  • Decrease ligand density on the sensor
  • Use MTL-corrected models for data fitting

P4PRO with AffiPump is designed to minimize MTLs by delivering analyte quickly and evenly across the sensor surface.

Non-Specific Binding (NSB): example sensorgramNon-Specific Binding (NSB): original sketch

ASSAY

Non-Specific Binding (NSB)

High signalPoor model fit

What you see

  • Steep RU increase from analyte interaction with sensor surface
  • High signal in reference channel — reflects diffusion, not binding
  • Poor model fitting

What to try

  • Increase salt concentration; adjust buffer pH
  • Add BSA or non-ionic surfactants (e.g., Tween 20)
  • Change ligand orientation or sensor surface chemistry

Part 3

Operational, Instrumentation & Other Issues

Issues arising from instrument state, fluidics, temperature, and compound effects.

Baseline Drift: example sensorgramBaseline Drift: original sketch

OPERATIONAL

Baseline Drift

Baseline drifting

What you see

  • Gradual upward or downward RU drift during the run
  • May indicate temperature fluctuations, unstable sensor, or contamination

What to try

  • Stabilize temperature in the instrument environment
  • Replace sensor; equilibrate system with sufficient buffer
  • Flow running buffer until baseline is stable
Air Bubble or Clog in Lines: example sensorgramAir Bubble or Clog in Lines: original sketch

OPERATIONAL

Air Bubble or Clog in Lines

Spikes / dropsNoisy data

What you see

  • Sudden, unpredictable RU spikes and drops during injection and dissociation
  • Erratic signal not correlated with binding events

What to try

  • Check instrument for fluidic leaks; purge lines
  • Degas samples before injection
  • Perform scheduled instrument maintenance
Injection Failure: example sensorgram

OPERATIONAL

Injection Failure

No signal

What you see

  • No RU response after analyte injection
  • May be caused by valve malfunction, air in syringe, or software error

What to try

  • Check injection valves and syringe for air
  • Restart software and re-run system maintenance
Rounded Peak: example sensorgramRounded Peak: original sketch

INSTRUMENTATION

Rounded Peak

Poor model fitSlow dissociation

What you see

  • Inefficient analyte dissociation from the ligand
  • Over- or under-estimation of binding affinity
  • Poor fit with standard 1:1 global model

What to try

  • Implement a regeneration step
  • Use a fit model other than 1:1 global fit
Combination Effects: example sensorgramCombination Effects: original sketch

COMBINED

Combination Effects

High signalSpikes / dropsPoor model fitBaseline risingSlow dissociation

What you see

  • MTLs, protein aggregation, and buffer mismatch simultaneously present
  • Linear upward climb during association with no equilibrium plateau
  • Steady higher baseline; poor fitting across all models

What to try

  • Diagnose each effect individually before applying fixes
  • Address buffer mismatch first, then aggregation, then MTL
  • Refer to Parts 1 & 2 for individual fix protocols

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