Analysis of Fluorescence Polarization competition assays with AFFINImeter

Fluorescence Polarization competition assays are widely used in numerous research fields to determine the affinity of unlabeled ligands that compete with a fluorescent probe for binding with the same macromolecule. Herein, we show how to perform a thoughtful analysis of these experiments with AFFINImeter for spectroscopic techniques, to elucidate, not just IC50 values, but also a quantitative direct measurement (KA) of the binding affinity.



Fluorescence polarization (FP) is a powerful technique that nowadays is widely utilized in high-throughput screening (HTS) and drug discovery (1). In FP assays monitoring a binding event is possible mainly because this technique is sensitive to changes in molecular weight. The assay requires of a fluorescent molecule (the probe) that is excited by plane-polarized light. For small molecules, the initial polarization decreases rapidly due to rotational diffusion during the lifetime of the fluorescence, which results in low fluorescence polarization. When the small fluorescent molecule binds to a larger molecule (and consequently of slower rotation) an increased fluorescent polarization is observed (Fig. 1).
Advances in experimental aspects of the technique like assay design and fluorescent probes is enabling the application of FP to increasingly complex biological processes (1).

Fig.1. The principle of fluorescence polarization (2).


Frequently, a competition displacement assay format is used in FP experiments where a fluorescent labelled molecule bound to a macromolecule is displaced by an unlabeled molecule with the consequent decrease of polarization. This assay yields a quantitative measure of IC50 values (half maximal inhibitory concentration) of the unlabeled competitors. However, IC50 does not provide a direct measure of affinity and the calculation of the binding constant (KA) is often desirable. In this sense, the software AFFINImeter Spectroscopy offers exclusive analysis tools to perform a thoughtful analysis of FP competition assays, to directly deliver values of binding constants of the interaction between the competitor and the macromolecule. As an illustrative example, we present herein the use of AFFINImeter Spectroscopy for the analysis of FP competition assays to characterize oligosaccharide –protein interactions.


FP competition assays to study the binding between midkine and chondroitin sulfate-like tetrasaccharides

Midkine is a cytokine which biological activity is regulated by its binding with glycosaminoglycans (GAGs), such as heparin and chondroitin sulfate. To better understand these recognition processes Pedro M. Nieto et al. have recently reported the binding of a series of synthetic chondroitin sulfate-like tetrasaccharides with midkine, using FP competition assays (3). First, the direct binding of midkine and a fluorescein labelled heparin hexasaccharide (fluorescent probe) was monitored in a direct FP titration (Fig. 2a). Second, FP competition assays were performed, in which the polarization of samples containing fixed concentrations of midkine and fluorescent probe was recorded in the presence of increasing concentrations of different synthetic sugars to obtain the corresponding IC50 values (Fig. 2b) (3).








Fig.2. a) Binding curve of the titration of fluorescent probe with midkine 3a;b) Representative competition curve (semi-log plot) of an FP competition assay where the fluorescent probe is displaced from a pre-formed complex with midkine by the competitor.


Analysis of FP competition assays with AFFINImeter Spectroscopy

The determination of KA of the interaction of the unlabeled ligand with the macromolecule in an FP competition assay is possible if the corresponding curve is analyzed using a competitive binding model where two equilibria are described, one between the free species and the macromolecule–probe complex and one between the free species and the macromolecule–competitor complex. In this analysis, the KA value of the interaction between probe and macromolecule can be fixed (as it can be previously calculated from the direct binding experiment) in order to determine KA of the competitor-macromolecule complex. Yet, a more robust approach consists of a global analysis of direct and competitive curves where constraints between experimental parameters are imposed. Using this approach, we have used AFFINImeter Spectroscopy in the analysis of data from the direct measurement of the fluorescent labelled hexasaccharide binding to midkine and together with data from the displacement assay using an unlabeled, synthetic disaccharide as a competitor (4).

An AFFINImeter fitting project was generated where the curve from the direct titration and two curves from replicates of the competitive assay were included. A 1:1 simple binding model and a competitive model were used to fit direct and competitive data, respectively (Fig. 3).

Fig.3. Schematic representation of the binding models used to fit the FP data.5 These models can be easily built with the “model builder” tool of AFFINImeter where a) in the 1:1 model “M” represents the species sensitive to binding (fluorescent probe) and “A” represents the titrant (midkine); b) in the competitive model “M” is the sensitive species (probe), A is the titrant (competitor) and B is a third species involved in the event (midkine in a preformed complex with the probe).


In the analysis, the fitting parameters considered were the KA of each complex, the signal value of the unbound state (s0), and the maximum signal change (Δsmax) of the midkine-probe complex formation. Δsmax of the midkine-competitor complex is equal to zero because the competitor is not fluorescent. Since midkine-probe binding is present in both models, restrictions were made considering that KA and Δsmax of the 1:1 model (FS↔MA) are equal to the same parameters describing this equilibrium in the competitive model (FS↔MB). Besides, s0 was common between replicates of the competitive assay. It is worth to mention that the curves analyzed are the mean of three replicate experiments and the corresponding standard deviation of the curve data points are also considered in the fitting process.  The global analysis performed in this way returned the KA of the interaction of midkine with the probe, (3.09 ± 0.18)*107 M-1, and with the competitor, (5.30 ± 0.52)*106 M-1 (Fig. 4). Additionally, AFFINImeter automatically generates the species distribution plot, valuable in the interpretation of results. The species distribution plot of Fig. 4c shows the displacement of the probe by the unlabeled disaccharide in the competition assay.


Fig.4. a) Global analysis of FP curves from the direct titration of probe (10 nM) with midkine (12 – 750 nM) and from a competitive assay consisting of a sample with probe (10 nM) and midkine (63 nM) where the competitor is added at increasing concentrations (0 – 20 mM). Curves from two replicates of the competitive assay were used in the analysis. All the polarization values are the average of three replicate wells and the error bars represent the corresponding standard deviation; b) values of KA, s0 and Δsmax determined for each equilibrium; c) species distribution semi-log plot of the competitive assay.



This case study exemplifies the utility of AFFINImeter Spectroscopy in the analysis of FP competitive binding assays. The advantages of using this software rely on the possibility to obtain reliable KA values of the binding between competitor and macromolecule from a global analysis where KA and Δsmax of the probe-macromolecule complex, are shared parameters between curves (they are not pre-determined fixed parameters). Besides, standard deviation between replicates is taken into account in the fitting process. Ultimately, these tools provide a more robust analysis and reliable characterization of binding interactions monitored through competitive assays.


Try AFFINImeter Spectroscopy


We would like to thank Dr Pedro Nieto Mesa and Dr José Luis de Paz Carrera from the Institute of Chemical Research (IIQ) of the Spanish National Research Council (CSIC), for kindly share with us the FP data presented herein.


References & Notes

1 Hall, M.; Yasgar, A.; Peryea, T.; Braisted, J.; Jadhav, A.; Simeonov, A.; Coussens, N. Fluorescence Polarization Assays In High-Throughput Screening And Drug Discovery: A Review. Methods and Applications in Fluorescence 2016, 4, 022001.

2 This figure has been taken from

3 a) Solera, C.; Macchione, G.; Maza, S.; Kayser, M.; Corzana, F.; de Paz, J.; Nieto, P. Chondroitin Sulfate Tetrasaccharides: Synthesis, Three-Dimensional Structure And Interaction With Midkine. Chemistry – A European Journal 2016, 22, 2356-2369; b) Maza, S.; Gandia-Aguado, N.; de Paz, J.; Nieto, P. Fluorous-Tag Assisted Synthesis Of A Glycosaminoglycan Mimetic Tetrasaccharide As A High-Affinity FGF-2 And Midkine Ligand. Bioorganic & Medicinal Chemistry 2018, 26, 1076-1085.

4 The competitor is a synthetic disulfated disaccharide described in ref. 3b as compound 18.

5 These model were created with the “model builder” tool, exclusive of AFFINImeter. For more information go to AFFINImeter knowledge center.

Working with AFFINImeter models based on a stoichiometric equilibria approach

The appropriate design and use of binding models in AFFINImeter pass through an understanding of the nomenclature that the software uses to describe a given experimental setup and the species that take part in the assay.
AFFINImeter contemplates the presence of up to three species participating in the experiment: 1) the titrant, or compound placed in the syringe; 2) the titrate, or compound in the calorimetric cell and 3) a co-solute or third compound that can be in the syringe and/or in the cell. These species are labelled in the reaction builder as follows:

As illustrated in Fig. 1, M always refers to the compound placed in the calorimetric cell and A always refers to the compound in the syringe. B always refers to a third component that can be in the syringe (Fig. 1b), in the cell (Fig. 1c) or in both places at once (Fig. 1d):


Once the nomenclature of  AFFINImeter is clear, you can download this note that our scientific team have prepared to understand how our users can be working with models based on a stoichiometric equilibria approach:


You can also check our latest post where we describe “The concepts of stoichiometric and site binding constants”


AFFINImeter is on sales!


This month we have prepared a special offer just to let you exploit the full potential of AFFINImeter:

 15 % off in our Advanced plans*.

Select the technique AFFINImeter Spectroscopy and/or AFFINImeter ITC.




… Use this coupon in our online shop and get right away your discount!


To use our online shop it will be necessary to have an AFFINImeter account, to create one click here.

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Or if you prefer we can send you an official quotation, click on the button below:​

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*The promotion is available until May 31st and applicable for all AFFINImeter Advanced plan (ITC and/or Spectroscopy) which duration is equal or greater 1 year. The advanced account includes Global fitting, access to complex binding models, Kinetic information (KinITC tool available for AFFINImeter ITC), orthogonal approach (Multitechnique analysis available in AFFINImeter Spectroscopy)...




AFFINImeter new version!

Last week we announced a release of our new software: AFFINImeter for Spectroscopic Techniques.  Together with this release, we have also improved several aspects of the AFFINImeter software, see what is new in our new version:

1. As we have already mentioned, in this version included a new technique: Spectroscopy (and all its variants: UV-vis, InfraRed, Fluorescence, Circular Dichroism… among others)

  • Just upload new data, select Spectroscopy technique and follow the wizard to import your data.
  • Data must be uploaded in CSV format.
  • Create projects of Fitting and Global fitting with any model you want.

2. Recent activity shows you the latest modified/created files or projects of any technique


3. Now AFFINImeter will use the maximum width of your screen to show your data/projects, for a better experience using wide-screen monitors.

4. Navigation path visible in all views

Fixed problems:

1. Fixed recursively deleting a folder and its contents

2. More validations while selecting a model for NMR technique (and Spectroscopy also):

  • In NMR and SPEC, you cannot use a model that only contains A in its reactions. Now more here

3. Multiple minor usability improvements and performance tweaks.

4. Multiple bug fixes and issues suggested by our users have been implemented and resolved.


What does it look like to you?

It might look like a plain hat or an elephant being eaten by a boa constrictor, but actually, the shape of this curve looks like a typical spectrum of UV-Vis determined by changes in the intensity of this energy and also it represents the logo of our new software:

AFFINImeter for spectroscopic techniques!


Hence, we want to take this opportunity to launch AFFINImeter Spectroscopy software.

It is a new software for the processing and advanced analysis of binding isotherms obtained from different spectroscopic techniques: 1D-NMR, Uv-vis, fluorescence, circular dichroism, differential scanning fluorimetry…


…and from now on, you will be able to start using it:

Get a free trial

To get started, we have prepared some scientific material as an example of how to use AFFINImeter Spectroscopy:

We have prepared a special offer to celebrate the launch of AFFINImeter for Spectroscopic techniques.
Using this code coupon you will get a 25% off*, to buy through our online shop:


 You can also ask for a quotation here 
*The discount will be applied until 2018/03/03.

New agreement: Mestrelab Research & AFFINImeter

Mestrelab Research and Software 4 Science Developments-AFFINImeter have agreed to enhance the use of advanced analysis of binding isotherms from 2D-NMR titrations. For this reason, all users interested to acquire a Mnova Binding license will benefit from a free annual license of AFFINImeter- NMR.

Mnova Binding is a powerful tool that automatically processes 2D HSQC type of protein-ligand titration spectra, tracks the peak movement and computes the Kd‘s for multiple peaks.

AFFINImeter for Nuclear Magnetic Resonance allows the advanced analysis of binding isotherms from 2D NMR titrations to measure binding constants (KA). Use it to:

  • Simultaneous upload and processing of 2D titration spectra.
  • Automated peak tracking of stacked spectra.
  • Automated generation of binding curves.
  • Easy exporting of binding curves into AFFINImeter-NMR.

More info here: Start using AFFINImeter-NMR



Open position: Chief Operating & Financial Officer (COFO)

Founded in 2013, Software 4 Science Developments (S4SD) is a leading cloud computing service provider of scientific software AFFINImeter, with more than 1.000 users including the biggest pharmaceutical corporations and research centres and Universities. The company is headquartered in Santiago de Compostela.

We are looking for a COFO to manage the planning and business functions, as well as the overall operations of the company. In addition to general responsibility for financial planning and controls, personnel administration, systems and physical facilities, the COFO should plan for the changing needs of the organization, share responsibility for strategic planning, practice management, and marketing, and contribute to aligning organizational structure with strategy. The COFO will lead and direct the operational and administrative functions of the firm, including accounting and finance, human resources, facilities, conflicts, and records management. This person will be a member of the firm’s Executive Committee.

The COFO supports to the CEO in:

  • Matters of strategy and business development, coordinating the different areas of the company.
  • Providing strategic support through facilitating or advising strategy development while demonstrating foresight, conceptual capability and environmental market awareness. The COFO should manage the leads acquisition and integration for short and long-term strategy development.
  • Development and management of transverse projects of transformation (digital, organization and processes), ensuring the constant simplification and growth of the business. Management of internal communication related to the transformation activities.
  • Managing the corporate agenda, including the various internal/external committees and boards.
  • Constant relation to Shareholders & Senior Management.

The COFO is responsible for:

  • Finding public and private sources of funding.
  • Financial Management: Including planning, forecasting, budgeting, variance analysis, profitability analysis, financial reporting, general ledger accounting, billing, cash flow control, banking relationships, tax planning, tax reporting, trust accounting, payroll, and other financial management functions.
  • Human Resource Management: Including recruiting, selection, training and development, performance evaluation, budgeting and salary administration, employee relations, benefits administration, workers’ compensation, job design and other human resource management functions.
  • Systems Management: Participation in the design and implementation of a KPI information system for all areas of the company, operational audits, cost/benefit analysis, information services, document management systems and procedures, information storage and retrieval, litigation support, and other systems management functions.

Required skills:

  • Bachelor’s degree and preferably an MBA
  • 8+ years of experience, 3+ in a senior position as a Chief Operational Officer and/or Chief Financial Officer, preferably in software companies and/or startup environments.
  • Competencies skills: Used to working in international environments. Results-oriented, strategic thinker and planner. Teamwork. Communication and interpersonal skills. Synthesis and presentation skills. Time management and ability to prioritize. Hands-on proactive attitude. Analytical. Creativity. Proficiency in English / Native Spanish

We offer:

  • Salary: based on interview, bonuses
  • Real ownership and results
  • And a competitive, friendly, international team!

Please contact to

AFFINImeter Spectroscopy


Is a new software for the advanced analysis of isotherms obtained by spectroscopic techniques, such as Uv-vis, circular dichroism, fluorescence… among others, to calculate binding constants.
We are pleased to announce that we are going to release very soon a beta version of AFFINImeter Spectroscopy. That is why we would like to invite you to become one of our beta testers, just click on the button below!

I want to become a beta tester!



I want to become a beta tester!

Global fitting: the key for a robust analysis

Download use case: Global Fitting


The Indian parable of “The six blind men and the elephant” tells the story of six blind men who touch an elephant in the hope of learning what it is like. As each one can only feel a different part of the animal the individual conclusions obtained are in disagreement and none of them provides a real view of the full elephant. “only by sharing what each of you knows can you possibly reach a true understanding”; that´s the moral behind this nice story.


Fig 1: The six blind men and the elephant: only a global analysis of the overall data provides a true understanding.

The binding assay(s) achieved to characterize a molecular interaction often provides not just one, but several binding curves from which the affinity constant is obtained.
Sometimes, an individual fit of these curves yield a set of binding constants that are significantly different from them; this result can be very confusing because, in principle, these binding curves are a representation of the same binding event and should converge to provide the analogous information. Often, the explanation for this behaviour is that the different curves indeed provide only partial and/or different information of the interaction, not enough to unequivocally determine the binding affinity through individual analysis.

“It´s like feeling only a separate part of the elephant”

This is a typical scenario when facing the study of complex binding events that involve more than one equilibrium and several binding curves are obtained, i.e. from different frequencies of the spectra in a titration experiment, from data registered using different techniques (ITC, NMR, Optical Spectroscopies…) and/or from experiments performed at different concentrations of the species participating in the binding event.

Analogous to the parable of the six men and the elephant, the way to get a true understanding of the binding event consist of the global analysis of the different curves.

Fig 2: The binding curve obtained from 2D NMR titrations.

Being aware of the relevance of global analysis, in AFFINImeter we count with the possibility to perform Global fitting of multiple data to tailored binding models where one or more fitting parameters are shared between isotherms. The number and identity of the parameters shared are selected by the user.
Moreover, two or more parameters can be related through mathematical relationships designed by the user. All these features make our global fitting tool the most potent among others to perform a robust analysis of binding data of complex interactions.

About the disuses of  Isothermal Titration Calorimetry in drug discovery research

Isothermal Titration Calorimetry (ITC) is the gold standard for the calculation of affinity in molecular interactions. Many times, researchers claim that the high consumption of sample does not offset the use of ITC for Kd calculation.
Conversely, ITC hides many surprises in the acquisition data that can provide more information in a single experiment that other techniques that are more expensive and more complicated to use.

Download the PDF file of Implementation of kinITC into AFFINImeter


1. ITC collects data from the interaction as a function of time that can be analyzed to obtain kinetic information (kon and koff values). It can cover a very similar range as Surface Plasmon Resonance in a “label-free” and “in-solution” manner (Fig 1).

2. ITC can also provide valuable information about the mechanism of interaction. The high sensitivity of the ITC sensor makes it sensitive to more intriguing interactions as conformational changes, cooperativity…

Using a global fitting approach for the analysis of the isotherms and a model builder to create tailored binding models, the different mechanisms of interaction can be confirmed and characterized.

Find attached a couple of publications describing the application of this new method for ITC data analysis:

Download the PDF file of Implementation of kinITC into AFFINImeter