Cooperativity, absolute interaction, and algebraic optimization

We consider a measure of cooperativity based on the minimal interaction required to generate an observed titration behavior. We describe the corresponding algebraic optimization problem and show how it can be solved using the nonlinear algebra tool . Moreover, we compute the minimal interactions and minimal molecules for several binding polynomials that describe the oxygen binding of various hemoglobins under different conditions. We compare their minimal interaction with the maximal slope of the Hill plot, and discuss similarities and discrepancies with a view towards the shapes of the binding curves.

New insights on the interaction mechanism of rhTNFα with its antagonists Adalimumab and Etanercept

TNFα is a pro-inflammatory cytokine that is a therapeutic target for inflammatory autoimmune disorders. Thus, TNFα antagonists are successfully used for the treatment of these disorders. Here, new association patterns of rhTNFα and its antagonists Adalimumab and Etanercept are disclosed. Active rhTNFα was purified by IMAC from the soluble fraction of transformed E. coli. Protein detection was assessed by SDS-PAGE and western blot. The KD values for rhTNFα interactions with their antagonists were obtained by non-competitive ELISA and by microscale thermophoresis. Molecular sizes of the complexes were characterized by SEC-HPLC. Surprisingly, both antagonists recognized the monomeric form of rhTNFα under reducing and non-reducing conditions, indicating unexpected bindings of the antagonists to lineal epitopes and to one protomer of rhTNFα. Binding curves of two phases with low and high KD values (<10−9 M and >10−8 M) were observed during thermophoresis experiments, suggesting the generation of complexes with different stoichiometry, which were confirmed by SEC-HPLC. This pioneer investigation revealed interactions of rhTNFα with Adalimumab and Etanercept never described before, which constitute valuable data for future approaches into the study of their interaction mechanism.

Kinetic Exclusion Assay of Biomolecules by Aptamer Capture

DNA aptamers are short nucleotide oligomers selected to bind a target ligand with affinity and specificity rivaling that of antibodies. These remarkable features recommend aptamers as candidates for analytical and therapeutic applications that traditionally use antibodies as biorecognition elements. Numerous traditional and emerging analytical techniques have been proposed and successfully implemented to utilize aptamers for sensing purposes. In this work, we exploited the analytical capabilities offered by the kinetic exclusion assay technology to measure the affinity of fluorescent aptamers for their thrombin target and quantify the concentration of analyte in solution. Standard binding curves constructed by using equilibrated mixtures of aptamers titrated with thrombin were fitted with a 1:1 binding model and provided an effective Kd of the binding in the sub-nanomolar range. However, our experimental results suggest that this simple model does not satisfactorily describe the binding process; therefore, the possibility that the aptamer is composed of a mixture of two or more distinct Kd populations is discussed. The same standard curves, together with a four-parameter logistic equation, were used to determine “unknown” concentrations of thrombin in mock samples. The ability to identify and characterize complex binding stoichiometry, together with the determination of target analyte concentrations in the pM–nM range, supports the adoption of this technology for kinetics, equilibrium, and analytical purposes by employing aptamers as biorecognition elements.

Allostery in oligomeric receptor models

We show how equilibrium binding curves of receptor homodimers can be expressed as rational polynomial functions of the equilibrium binding curves of the constituent monomers, without approximation and without assuming independence of receptor monomers. Using a distinguished spanning tree construction for reduced graph powers, the method properly accounts for thermodynamic constraints and allosteric interactions between receptor monomers (i.e. conformational coupling). The method is completely general; it begins with an arbitrary undirected graph representing the topology of a monomer state-transition diagram and ends with an algebraic expression for the equilibrium binding curve of a receptor oligomer composed of two or more identical and indistinguishable monomers. Several specific examples are analysed, including guanine nucleotide-binding protein-coupled receptor dimers and tetramers composed of multiple ‘ternary complex’ monomers.

Significance Testing and Multivariate Analysis of Datasets from Surface Plasmon Resonance and Surface Acoustic Wave Biosensors: Prediction and Assay Validation for Surface Binding of Large Analytes

In this study, we performed uni- and multivariate data analysis on the extended binding curves of several affinity pairs: immobilized acetylcholinesterase (AChE)/bioconjugates of aflatoxin B1(AFB1) and immobilized anti-AFB1 monoclonal antibody/AFB1-protein carriers. The binding curves were recorded on three mass sensitive cells operating in batch configurations: one commercial surface plasmon resonance (SPR) sensor and two custom-made Love wave surface-acoustic wave (LW-SAW) sensors. We obtained 3D plots depicting the time-evolution of the sensor response as a function of analyte concentration using real-time SPR binding sensograms. These “calibration” surfaces exploited the transient periods of the extended kinetic curves, prior to equilibrium, creating a “fingerprint” for each analyte, in considerably shortened time frames compared to the conventional 2D calibration plots. The custom-made SAW sensors operating in different experimental conditions allowed the detection of AFB1-protein carrier in the nanomolar range. Subsequent statistical significance tests were performed on unpaired data sets to validate the custom-made LW-SAW sensors.

Allostery in oligomeric receptor models

We show how equilibrium binding curves of receptor heterodimers and homodimers can be expressed as rational polynomial functions of the equilibrium binding curves of the constituent monomers, without approximation and without assuming independence of receptor monomers. Using a distinguished spanning tree construction for reduced graph powers, the method properly accounts for thermodynamic constraints and allosteric coupling between receptor monomers.

Comparing enzyme activity modifiers equations through the development of global data fitting templates in Excel

The classical way of defining enzyme inhibition has obscured the distinction between inhibitory effect and the inhibitor binding constant. This article examines the relationship between the simple binding curve used to define biomolecular interactions and the standard inhibitory term (1+([I]/Ki)). By understanding how this term relates to binding curves which are ubiquitously used to describe biological processes, a modifier equation which distinguishes between inhibitor binding and the inhibitory effect, is examined. This modifier equation which can describe both activation and inhibition is compared to standard inhibitory equations with the development of global data fitting templates in Excel, and via the global fitting of these equations to previously reported enzyme kinetic data. This equation and the template developed in this article should prove to be useful tools in the study of enzyme inhibition and activation.