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AFFINImeter Spectroscopy is the software for the advanced analysis of isotherms obtained by spectroscopic techniques, such as 1D- NMR, Uv-vis, circular dichroism, fluorescence
 among others, to calculate binding constants.  Check below the main features:

 

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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.

 

Introduction


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.

 

Conclusions


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.

 

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Acknowledgements


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 http://glycoforum.gr.jp/science/word/glycotechnology/GT-C06E.html.

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.

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.

How to get the most out of biophysical techniques to address binding interactions?

The analysis of isotherms is the more direct way to calculate binding constants for molecular interactions. Isotherms can be obtained using different techniques (ITC, SPR, NMR, Uv-vis, IR, Fluorescence, Circular Dichroism
) and at different experimental conditions.

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1. The global fitting approach allows to simultaneously analyze several isotherms obtained by different biophysical techniques and/or at different experimental conditions in a very accurate manner.

 

 

2. Many interacting systems do not bind with a simple 1:1 model, more complex binding model can be designed to address complex interaction

3. Using tools to globally analyze isotherms obtained by different biophysical techniques is the most reliable method to characterize binding interactions by the orthogonal approach.

Click here to star using AFFINImeter and to start to create your own binding model:

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Expanding the range of applications of ITC in the Pharmaceutical Industry with AFFINImeter: A practical Case.

Many Drug–receptor interactions are characterized by complex binding modes that are far away from the behavior of a standard 1:1 model. This is the case of Heparin (Hp), one of the most commonly prescribed anticoagulant drugs, which exerts its effect through its interaction with the serine protease Antithrombin (AT-III). Hp is a linear heterogeneous polysaccharide containing a specific pentasaccharide sequence that binds AT-III with high nanomolar affinity (responsible for the anticoagulant activity); but AT-III also binds other Hp sequences with lower affinity. Determining the content of AT-III binding pentasacchride in Low Molecular Weight (LMW) Heparins is a requirement for Pharmaceutical companies that manufacture this type of anticoagulants; due to the intrinsic heterogeneity of Hp, obtaining this information it is not straightforward (1).

We have developed a new protocol based on ITC and AFFINImeter to determine the content of AT-III binding pentasaccharide in Heparins, which is summarized in the following scheme:

New method based on AFFINImeter to determine the content of AT-III binding pentasacchride in LMW Hp: 1) use of a tailored binding model that describes the competitive binding between the pentasaccharide (A) and other low affinity sequences (B) with AT-III (M); 2) global fitting of several isotherms registered under different Hp and or AT-III concentrations where the parameters rA and rB (that account for the fraction of A and B in the Hp sample) are fitting parameters and common among the different isotherms.
New method based on AFFINImeter to determine the content of AT-III binding pentasacchride in LMW Hp: 1) use of a tailored binding model that describes the competitive binding between the pentasaccharide (A) and other low affinity sequences (B) with AT-III (M); 2) global fitting of several isotherms registered under different Hp and or AT-III concentrations where the parameters rA and rB (that account for the fraction of A and B in the Hp sample) are fitting parameters and common among the different isotherms.

 

This method illustrates the great potential of the model builder and global fitting AFFINImeter tools to develop protocols of practical utility in the Pharmaceutical industry (2). We have successfully validated the protocol in the analysis of unfractionated Hp and a series LMW Hp in collaboration with the Pharmaceutical company Laboratorios Rovi (http://www.rovi.es/).

References

  1. Nandurkar H., Chong B, Salem H, Gallus A, Ferro V, McKinnon R. Low-molecular-weight heparin biosimilars: potential implications for clinical practice. Internal Medicine Journal, 2012, 44(5), pp 497–500.

  2. For a detailed description of the protocol contact us at support@affinimeter.com

Global fitting: the key for a robust analysis

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.

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

Sometimes, when we perform two or more ITC titration experiments of a complex interacting system under different experimental conditions (i.e. different concentrations and/or experimental setup) we find out that the individual analysis of the corresponding isotherms yields different values of the thermodynamic parameters. This result can be very confusing, especially for newcomers in the field of molecular recognition, because all these experiments are a representation of the same interaction and should converge to provide the same information. Frequently, the explanation for this behaviour is that each individual ITC experiment lacks of sufficient information to unequivocally determine the thermodynamic parameters of the binding event. “It®s like feeling only a separate part of the elephant”.
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 isotherms.
Being aware of the relevance of global analysis, in AFFINImeter we count with the possibility to perform Global fitting of multiple dataseries (isotherms) 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 trough 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 ITC data of complex interactions.

Learn how to perform a global analysis with AFFINImeter:

Global fitting analysis of a protein-ligand binding experiment

Global fitting analysis of a protein-ligand binding experiment

A few weeks ago AFFINImeter launched an Isothermal Titration data Analysis challenge of the analysis of a protein-ligand binding experiments. The participant had to globally analyze a set of Isothermal Titration Calorimetry experiments using AFFINImeter and get the thermodynamic and structural parameters of the interaction between both molecules (the receptor protein and the ligand).

The participants in this contest had the opportunity to demonstrate their ability to propose the right model for a given binding isotherm as well as to get the corresponding parameters upon fitting using AFFINImeter. On their side, less experienced participants had the opportunity to:

The results recently published by Henlz et al in [Methods 59 (2013) 336-348] were taken as a reference to generate the set of ITC isotherms selected for this contest.

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Complete guide of a global analysis of Isothermal Titration Calorimetry data in AFFINImeter

A few days ago AFFINImeter launched an Isothermal Titration Calorimetry (ITC) data analysis challenge. Here the participant had to globally analyse a set of Isothermal Titration Calorimetry experiments using AFFINImeter and get the thermodynamic and structural parameters of the interaction between both molecules (the receptor protein and the ligand).

The participants in this contest had the opportunity to demonstrate their ability to propose the right model for a given binding isotherm as well as to get the corresponding parameters upon fitting using AFFINImeter. On their side, less experienced participants had the opportunity to:

During the last days we though it might be useful to help you throughout the fittings proposed for the contest. Therefore, we have prepared a video that explains, step by step, How to fit CURVE 1. IMPORTANTLY, this information will be of great help to solve step 2, the global fitting of CURVES 1-4.

The data proposed for the contest will remain available here, in case you want to learn more about it or to try it by yourself.

(more…)

How to perform a Global Fitting Analysis?

The Global fitting of multiple isotherms is one of the advanced tools that AFFINImeter offers to facilitate the analysis and interpretation of isothermal titration experiments and to expand the range of applications of this technique.

The following video tutorial describes the global fitting of three isotherms of a displacement assay describing, a receptor interacting with a tight ligand, with a weak ligand, or with both ligands simultaneously, in a competitive experiment where the ligands are mixed in the syringe of the ITC equipment.

 

If you want to know more about global fittings with AFFINImeter you can also download the case of use “Global Analysis in ITC Displacement Titrations with AFFINImeter” that describes a Displacement Titration Assay to determine the thermodynamics of HIV-protease with indinavir, a high-affinity binder, and with acetyl-pepstatin, a weaker ligand.

ITC displacement titrations offer an attractive alternative to standard assays when working with ultra-high or ultra-low- affinity interacting systems. The method requires the fitting of at least two isotherms that share various adjustable parameters. The case study exemplifies the potential advantages of using AFFINImeter in ITC displacement assays. The software offers unique advanced tools that enhance the robustness of the method and makes it more versatile, facilitating the acquisition of reliable thermodynamic data from ultra-high of ultra-low affinity systems. Thus, it opens a door for new applications of the displacement assay.