Analysis of asymmetry of agonist concentration-effect curves

Repurposing conformational changes in ANL superfamily enzymes to rapidly generate biosensors for organic and amino acids

Biosensors are powerful tools for detecting, real-time imaging, and quantifying molecules, but rapidly constructing diverse genetically encoded biosensors remains challenging. Here, we report a method to rapidly convert enzymes into genetically encoded circularly permuted fluorescent protein-based indicators to detect organic acids (GECFINDER). ANL superfamily enzymes undergo hinge-mediated ligand-coupling domain movement during catalysis. We introduce a circularly permuted fluorescent protein into enzymes hinges, converting ligand-induced conformational changes into significant fluorescence signal changes. We obtain 11 GECFINDERs for detecting phenylalanine, glutamic acid and other acids. GECFINDER-Phe3 and GECFINDER-Glu can efficiently and accurately quantify target molecules in biological samples in vitro. This method simplifies amino acid quantification without requiring complex equipment, potentially serving as point-of-care testing tools for clinical applications in low-resource environments. We also develop a GECFINDER-enabled droplet-based microfluidic high-throughput screening method for obtaining high-yield industrial strains. Our method provides a foundation for using enzymes as untapped blueprint resources for biosensor design, creation, and application.

Antioxidants: Classification, Natural Sources, Activity/Capacity Measurements, and Usefulness for the Synthesis of Nanoparticles

Natural extracts are the source of many antioxidant substances. They have proven useful not only as supplements preventing diseases caused by oxidative stress and food additives preventing oxidation but also as system components for the production of metallic nanoparticles by the so-called green synthesis. This is important given the drastically increased demand for nanomaterials in biomedical fields. The source of ecological technology for producing nanoparticles can be plants or microorganisms (yeast, algae, cyanobacteria, fungi, and bacteria). This review presents recently published research on the green synthesis of nanoparticles. The conditions of biosynthesis and possible mechanisms of nanoparticle formation with the participation of bacteria are presented. The potential of natural extracts for biogenic synthesis depends on the content of reducing substances. The assessment of the antioxidant activity of extracts as multicomponent mixtures is still a challenge for analytical chemistry. There is still no universal test for measuring total antioxidant capacity (TAC). There are many in vitro chemical tests that quantify the antioxidant scavenging activity of free radicals and their ability to chelate metals and that reduce free radical damage. This paper presents the classification of antioxidants and non-enzymatic methods of testing antioxidant capacity in vitro, with particular emphasis on methods based on nanoparticles. Examples of recent studies on the antioxidant activity of natural extracts obtained from different species such as plants, fungi, bacteria, algae, lichens, actinomycetes were collected, giving evaluation methods, reference antioxidants, and details on the preparation of extracts.

Vascular tone and angiogenesis modulation by catecholamine coordinated to ruthenium

Catecholamines participate in angiogenesis, an important tumor development process. However, the way catecholamines interact with their receptors has not been completely elucidated, and doubts still remain as to whether these interactions occur between catechol and/or amine sites and particular amino acid residues on the catecholamine receptors. To evaluate how catechol and amine groups contribute to angiogenesis, we immobilized the catechol site through ruthenium ion (Ru) coordination, to obtain species with the general formula [Ru(NH₃)₄(catecholamine-R)]Cl. We then assessed the angiogenic activity of the complexes in a chorioallantoic membrane model (CAM) and examined vascular reactivity and calcium mobilization in rat aortas and vascular cells. [Ru(NH₃)₄(catecholamine-R)]Cl acted as partial agonists and/or antagonists of their respective receptors and induced calcium mobilization. [Ru(NH₃)₄(isoproterenol)]⁺ [Ru(NH₃)₄(noradrenaline)]⁺, and [Ru(NH₃)₄(adrenaline)]⁺ behaved as antiangiogenic complexes, whereas [Ru(NH₃)₄(dopamine)]⁺ proved to be a proangiogenic complex. In conclusion, catecholamines and [Ru(NH₃)₄(catecholamine-R)]Cl can modulate angiogenesis, and catechol group availability can modify the way these complexes impact the vascular tone, suggesting that catecholamines and their receptors interact differently after catecholamine coordination to ruthenium.

Mathematical modeling of G protein-coupled receptor function: what can we learn from empirical and mechanistic models?

Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.

Modeling of age-dependent amyloid accumulation and γ-secretase inhibition of soluble and insoluble Aβ in a transgenic mouse model of amyloid deposition

According to the “amyloid hypothesis,” accumulation of amyloid beta (Aβ) peptides in the brain is linked to the development of Alzheimer's disease. The aims of this investigation were to develop a model for the age-dependent amyloid accumulation and to quantify the age- and treatment-duration-dependent efficacy of the γ-secretase inhibitor MRK-560 in the Tg2576 transgenic mouse model of amyloid deposition. Soluble and insoluble Aβ40 and Aβ42 brain concentrations were compiled from multiple naïve, vehicle, and MRK-560-treated animals. The age of Tg2576 mice in the studies ranged between 3.5 and 26 months. Single doses of MRK-560 inhibited soluble Aβ40 levels in animals up to 9 months old. In contrast, MRK-560 did not cause significant acute effects on soluble Aβ40 levels in animals older than 13 months. Absolute levels of Aβ variants increased exponentially over age and reached a plateau at ∼20 months. In the final model, it was assumed that MRK-560 inhibited the Aβ production rate with an Aβ level-dependent IC₅₀.The age-dependent increase in Aβ levels was best described by a logistic model that stimulated the production rate of soluble Aβ. The increase in insoluble Aβ was defined as a function of soluble Aβ by using a scaling factor and a different turnover rate. The turnover half-life for insoluble Aβ was estimated at 30 days, explaining that at least a 4-week treatment in young animals was required to demonstrate a reduction in insoluble Aβ. Taken together, the derived knowledge could be exploited for an improved design of new experiments in Tg2576 mice.

EC50 estimation of antioxidant activity in DPPH· assay using several statistical programs

DPPH(·) assay is a reliable method to determine the antioxidant capacity of biological substrates. The DPPH(·) radical scavenging activity is generally quantified in terms of inhibition percentage of the pre-formed free radical by antioxidants, and the EC(50) (concentration required to obtain a 50% antioxidant effect) is a typically employed parameter to express the antioxidant capacity and to compare the activity of different compounds. In this study, the EC(50) estimation was performed using a comparative approach based on various regression models implemented in six specialized computer programs: GraphPad Prism® version 5.01, BLeSq, OriginPro® 8.5.1, SigmaPlot® 12, BioDataFit® 1.02, and IBM SPSS Statistics® Desktop 19.0. For this project, quercetin, catechin, ascorbic acid, caffeic acid, chlorogenic acid and acetylcysteine were screened as antioxidant standards with DPPH(·) assay to define the EC(50) parameters. All the statistical programs gave similar EC(50) values, but GraphPad Prism® five-parameter analysis pointed out a best performance, also showing a minor variance in relation to the actual EC(50).

Evaluation of an asymmetry parameter for curve-fitting in single-chemical and mixture toxicity assessment

In mixture toxicity, concentration-effect data are often used to generate conclusions on combined effect. While models of combined effect are available for such assessments, proper fitting of the data is critical to obtaining accurate conclusions. In this study an asymmetry parameter (s) was evaluated for data-fitting and compared with our previous approach. Inhibition of bioluminescence was assessed with Vibrio fischeri at 15, 30 and 45-min of exposure with seven or eight concentrations and a control (each duplicated) for each single-chemical (A or B) and mixture (A:B). Concentration-effect data were fitted to sigmoid curves using the four-parameter logistic function (4PL) and the five-parameter logistic minus one-parameter (5PL-1P) function. For the 4PL, parameters included minimum effect, maximum effect, EC(50) and slope, while for the 5PL-1P the minimum effect parameter was removed and an asymmetry parameter was added. A total of 72 mixture toxicity data sets were evaluated, representing 432 single-chemical and 216 mixture curves. Mean coefficients of determination (r(2)) for all 648 curves showed that the 5PL-1P gave better fitting (0.9982 ± 0.0018) than the 4PL (0.9973 ± 0.0030). For both functions, the sum-of-squares of the residuals (SS-Res) was determined for each curve. The 5-parameter rational regression best described the relationship between the decrease in sum-of-squares of the residuals (i.e., 4PL: SS-Res - 5PL-1P: SS-Res) and log s, with fitting improved the most at low values of s (s<0.8). This held even when curves with r(2) values ≤ 0.9970 were removed from the analyses. Subsequent review of the combined effects obtained via the 4PL and the 5PL-1P functions resulted in a change in the interpretation of combined effect in 39/216 (18%) cases.

Mixture toxicity of S(N)2-reactive soft electrophiles: 2-evaluation of mixtures containing ethyl α-halogenated acetates

Four ethyl α-halogenated acetates were tested in (1) sham and (2) nonsham combinations and (3) with a nonreactive nonpolar narcotic. Ethyl iodoacetate (EIAC), ethyl bromoacetate (EBAC), ethyl chloroacetate (ECAC), and ethyl fluoroacetate (EFAC), each considered to be an SN2-H-polar soft electrophile, were selected for testing based on their differences in electro(nucleo)philic reactivity and time-dependent toxicity (TDT). Agent reactivity was assessed using the model nucleophile glutathione, with EIAC and EBAC showing rapid reactivity, ECAC being less reactive, and EFAC lacking reactivity at ≤250 mM. The model nonpolar narcotic, 3-methyl-2-butanone (3M2B), was not reactive. Toxicity of the agents alone and in mixture was assessed using the Microtox acute toxicity test at three exposure durations: 15, 30 and 45 min. Two of the agents alone (EIAC and EBAC) had TDT values >100%. In contrast, ECAC (74 to 99%) and EFAC (9 to 12%) had partial TDT, whereas 3M2B completely lacked TDT (<0%). In mixture testing, sham combinations of each agent showed a combined effect consistent with predicted effects for dose-addition at each time point, as judged by EC(50) dose-addition quotient values. Mixture toxicity results for nonsham ethyl acetate combinations were variable, with some mixtures being inconsistent with the predicted effects for dose-addition and/or independence. The ethyl acetate-3M2B combinations were somewhat more toxic than predicted for dose-addition, a finding differing from that observed previously for α-halogenated acetonitriles with 3M2B.

Effect of asymmetry of concentration–response curves on the results obtained by the receptorial responsiveness method (RRM): an in silico study

The receptorial responsiveness method (RRM) was proposed to estimate changes in the concentration of an agonist in the microenvironment of its receptor. Usually, this is done by providing the equieffective concentration of another agonist for the same receptor or for a largely overlapping postreceptorial signaling (“test agonist”). The RRM is a special nonlinear regression algorithm to analyze a concentration–response (E/c) curve that represents the simultaneous actions of a single agonist concentration to be estimated and of increasing concentrations of the test agonist. The aim of this study was to explore whether asymmetry of the E/c curve to be analyzed influences the reliability of the RRM. For this purpose, computer simulation was performed by constructing symmetric and asymmetric E/c curves using the operational model of agonism, and then these curves were analyzed with the RRM. To perform the RRM, 2 types of equations were used: one involving the Hill equation, the simplest model of the E/c relationship, and one containing the Richards equation, an advanced model properly handling E/c curve asymmetry. Results of this study indicate that E/c curve asymmetry does not significantly influence the accuracy of the estimates provided by the RRM. Thus, when using the RRM, it is not necessary to replace the Hill equation with the Richards equation to obtain useful estimates. Furthermore, it was found that estimation of a high concentration of a high-efficacy agonist can fail when the RRM is performed with a low-efficacy test agonist in a system characterized by a small operational slope factor.

qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis

The qpcR library is an add-on to the free R statistical environment performing sigmoidal model selection in real-time quantitative polymerase chain reaction (PCR) data analysis. Additionally, the package implements the most commonly used algorithms for real-time PCR data analysis and is capable of extensive statistical comparison for the selection and evaluation of the different models based on several measures of goodness of fit.

AVAILABILITY

www.dr-spiess.de/qpcR.html.

SUPPLEMENTARY INFORMATION

Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under 'Supplemental Data'.

Highly accurate sigmoidal fitting of real-time PCR data by introducing a parameter for asymmetry

BACKGROUND

Fitting four-parameter sigmoidal models is one of the methods established in the analysis of quantitative real-time PCR (qPCR) data. We had observed that these models are not optimal in the fitting outcome due to the inherent constraint of symmetry around the point of inflection. Thus, we found it necessary to employ a mathematical algorithm that circumvents this problem and which utilizes an additional parameter for accommodating asymmetrical structures in sigmoidal qPCR data.

RESULTS

The four-parameter models were compared to their five-parameter counterparts by means of nested F-tests based on the residual variance, thus acquiring a statistical measure for higher performance. For nearly all qPCR data we examined, five-parameter models resulted in a significantly better fit. Furthermore, accuracy and precision for the estimation of efficiencies and calculation of quantitative ratios were assessed with four independent dilution datasets and compared to the most commonly used quantification methods. It could be shown that the five-parameter model exhibits an accuracy and precision more similar to the non-sigmoidal quantification methods.

CONCLUSION

The five-parameter sigmoidal models outperform the established four-parameter model with high statistical significance. The estimation of essential PCR parameters such as PCR efficiency, threshold cycles and initial template fluorescence is more robust and has smaller variance. The model is implemented in the qpcR package for the freely available statistical R environment. The package can be downloaded from the author's homepage.

Biphasic characteristic of interactions between stiripentol and carbamazepine in the mouse maximal electroshock-induced seizure model: a three-dimensional isobolographic analysis

The anticonvulsant effects produced by stiripentol (STP), carbamazepine (CBZ), and their combination in the maximal electroshock (MES)-induced seizures in mice were investigated using three-dimensional (3D) isobolographic analysis. With 3D isobolography, the combinations of both drugs at the fixed-ratios of 1:3, 1:1, and 3:1 for 16%, 50% and 84% antiseizure effects, respectively, were examined in order to evaluate the preclinical characteristics of the interactions between STP and CBZ. Additionally, to characterize precisely the types of interactions observed in the MES test, free plasma and total brain CBZ concentrations were estimated for all fixed-ratios tested. The 3D isobolographic analysis showed that STP and CBZ combined at the fixed-ratio of 1:3 produced supra-additive (synergistic) interactions in the MES test for the anticonvulsant effects ranging between 16% and 84%. In contrast, the combination of STP with CBZ at the fixed-ratio of 3:1 exerted sub-additive (antagonistic) interactions in 3D isobolography for all antiseizure effects examined in the MES test. Only the combination of STP and CBZ at the fixed-ratio of 1:1 was additive for the investigated effects (16%, 50% and 84%) in 3D isobolography. Pharmacokinetic evaluation of CBZ concentrations revealed that STP increased both free plasma and total brain CBZ concentrations for all fixed-ratio combinations tested (1:3, 1:1 and 3:1). In conclusion, the 3D isobolographic findings suggest that the combination of STP with CBZ exerted biphasic characteristics of interactions in the MES test, despite the pharmacokinetic increase in CBZ content in plasma and brains of experimental animals.

Pharmacokinetic–pharmacodynamic modelling of the schedule-dependent effect of the anti-cancer agent CHS 828 in a rat hollow fibre model

N-(6-Chlorophenoxyhexyl)-N'-cyano-N''-4-pyridylguanidine (CHS 828) is a novel anticancer agent that shows schedule-dependent effects in vitro and in vivo, as well as in Phase I clinical trials. A rat hollow fibre model was used to investigate whether this dependency is due to pharmacokinetic and/or pharmacodynamic factors. The effect on two cell lines, MDA-MB-231 (breast cancer) and CCRF-CEM (leukaemia) were studied after CHS 828 was administered orally as a single dose or in a 5-day schedule, at different total dose levels. The 5-day schedules were associated with greater effects on both cell lines compared with single doses. A one-compartment pharmacokinetic model, with a half-life of 2.3h and a consecutive zero- and first-order process to describe dissolution and absorption, fit the concentration data. Pharmacokinetics were dose-dependent, as the fraction absorbed decreased with increasing dose. Clearance increased with accumulative exposure. Twenty hours after administration, concentrations started to increase again, probably due to coprophagy. Pharmacokinetic-pharmacodynamic models characterized the cell growth and cell kill over time and showed that schedule-dependent antitumour effects were present also when the dose-dependent pharmacokinetics were accounted for. The prolonged schedules of CHS 828 were therefore associated with greater antitumour effects than single doses of the same total exposure.

Toxicity of terpenes to spores and mycelium of Penicillium digitatum

Spores, although often considered metabolically inert, catalyze a variety of reactions. The use of spores instead of mycelium for bioconversions has several advantages. In this paper, we describe the difference in susceptibility of mycelium and spores against toxic substrates and products. A higher resistance of spores toward the toxic effects of bioconversion substrates and products is an advantage that has not been studied in detail until now. This paper shows that spores of Penicillium digitatum ATCC 201167 are on average over 2.5 times more resistant than mycelium toward the toxicity of substrates, intermediates, and products of the geraniol bioconversion pathway. Furthermore, the higher resistance of spores to citral was shown as an advantage in its biotransformation by P. digitatum. Using three different approaches the toxicity of the compounds were tested. The order of toxicity toward P. digitatum was, starting with the most toxic, citral > nerol/geraniol > geranic acid > methylheptenone >> acetaldehyde.

Assessing the (a)symmetry of concentration-effect curves: empirical versus mechanistic models

Modeling the shape of concentration-effect curves is of prime importance in pharmacology. Geometric descriptors characterizing these curves (the upper and lower asymptotes, the mid-point, the mid-point slope, and the point of inflection) are used for drug comparison or for assessing the change in agonist function after a system modification. The symmetry or asymmetry around the mid-point of a concentration-effect curve is a fundamental property that, regretfully, is often overlooked because, generally, models yielding exclusively symmetric curves are used. In the present review, empirical and mechanistic models are examined in their ability to fit experimental data. The geometric parameters of a survey of empirical models, the Hill equation, a logistic variant that we call the modified Hill equation, the Richards function, and the Gompertz model are determined. To analyze the relationship between asymmetry and mechanism, some examples from the ionic channel field, in an increasing degree of complexity, are used. It is shown that asymmetry arises from ionic channels with multiple binding sites that are partly occupied. The operational model of agonism is discussed both in its empirical general formulation and including the signal transduction mechanisms through G-protein-coupled receptors. It is shown that asymmetry results from systems where receptor distribution is allowed. Developed mathematical models are compared for describing experimental data on alpha-adrenoceptors. The existence or not of a relationship between the shape of the curves and receptor reserve is discussed.

Analysis of ligand-receptor interactions from the molecular level to the whole-body level

A system for the quantitative analysis of ligand-receptor interactions is presented, based on models of different levels of complexity. For two pools of receptors, binding of a radioactive ligand is described by b = [(Bml x A(nl))/(K(nl)dl + A(nl))] + [(Bm2 x A(n2))/(Kn2(d2) + A(n2))], (1) where b is the number of bound receptors at a ligand concentration [A], Bml and Bm2 are the receptor concentrations. Kdl and Kd2 are dissociation constants for the ligand-receptor complex, and n1 and n2 are Hill coefficients. The magnitude of the physiological response for a system consisting of two discrete pools of receptors with different affinities is given by p = [(Pm x A(nl))/(EC50(nl) + A(nl))] + [(Pm2 x A(n2)/(EC50(n2)2 + A(n2))], (2) where p is the magnitude of the response to an agonist (or antagonist) at concentration [A], Pml and Pm2 are the maximal magnitudes of the responses for the individual pools of receptors, EC50(1) and EC50(2) are the agonist concentrations giving responses of magnitudes Pm1/2 and Pm2/2, and n1 and n2 are Hill coefficients. The parameters of these equations show: the number of pools of receptors with different affinities for the ligand (Kd or EC50), the number of active receptors (Bmax) or the magnitudes of the maximal response (Pmax), and the numbers of ligand molecules binding with the receptor (n, the Hill coefficient). E is the efficiency (E = Bmax/2Kd, or E = Pmax/2EC50) and gives the overall characteristics of the activity of the effector system. This method of analysis can be applied to any biological reactions whose results can be presented quantitatively.