Development and validation of fluorescent receptor assays based on the human recombinant estrogen receptor subtypes alpha and beta

Boer, Theo de; Otjens, Debby; Muntendam, Alex; Meulman, Eric; Oostijen, Martine van; Ensing, K

doi:10.1016/j.jpba.2003.11.006

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…For immunoassays, fluorescence assays, SPR, NMR and ACE, RSD% values of 2 to 10% have been reported in favorable cases. However, sometimes these favorable precision values have not been reached . Some reasons for this lack in precision can easily be avoided.…”

Section: Introduction and Objectivementioning

confidence: 99%

Experimental design and measurement uncertainty in ligand binding studies by affinity capillary electrophoresis

et al. 2019

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Experimental design and measurement uncertainty in ligand binding studies by affinity capillary electrophoresisIn all life sciences ligand binding assays (LBAs) play a crucial role. Unfortunately these are very error prone. One part of this uncertainty results from the unavoidable random measurement uncertainty, another part can be attributed to the experimental design. To investigate the latter, uncertainty propagation was evaluated as a function of the given experimental design. A design space including the normalized maximum response range (nMRR), the data point position (DPP), the data point range (DPR) and the number of data points (NoDP) was defined. Based on ten measured ms ACE source data sets 20 specific parameter sets were selected by Design of Experiments. Monte Carlo simulations using 100 000 repeats for every parameter set were employed. The resulting measurement uncertainty propagation factors (measurement uncertainty multiplier: MUM) were used to describe the whole design space by polynomial regression. The resulting 5-dimensional response surface was investigated to evaluate the design parameter's influence and to find the minimal uncertainty propagation. It could be shown, that the nMRR is of highest importance, followed by DPP and DPR. Interestingly, the NoDP is less relevant. However, the interactions of the four parameters need to be carefully considered during design optimization. Using at least five data points which cover over 40% of the upper part of the binding hyperbola (DPP Ͼ 0.57) the MUM will be minimized (MUM approximately 1.5) when the nMRR is appropriate. It is possible to reduce the measurement uncertainty propagation more than one order of magnitude.Abbreviations: , electrophoretic mobility; c KD , theoretical mobility at the ligand concentration equals the K D -value; c , mobility of the complex; f , mobility of the free analyte; AIQ, analytical instrument qualification; aMRR, absolute maximum response range; BGE, background electrolyte; BSA, bovine serum albumin; c, concentration; c 0 , in absence of ligand; c Ý , in presence of a theoretically infinite ligand concentration; CD, sulfobutyl ether betacyclodextrine derivates; CI mean , confidence interval of the mean; const, constant parameter; conti, continuous parameters; DPP, data point position; DPR, data point range; DS, design space; E-systems, example analyte/ligand systems; G, Gradient; HC, hydrocorti-sone; HPAC, high performance affinity chromatography; HSA, human serum albumin; K A , association constant; K D , dissociation constant; LBA, ligand binding assay; LBAs, ligand binding assays; MRR, maximum response range; ms ACE, mobility shift affinity capillary electrophoresis; MUM, measurement uncertainty multiplier; MUP, measurement uncertainty propagation; nDS, normalized design space; nMRR, normalized maximum response range; NoDP, number of data points; PMS, parameter sets; PPS, pentosan polysulfate; R", complexed fraction; RSD, relative standard deviation; SOP, standard operating procedure; SPR, surface plasmon resona...

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Section: Introduction and Objectivementioning

confidence: 99%

Experimental design and measurement uncertainty in ligand binding studies by affinity capillary electrophoresis

et al. 2019

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“…Nonspecific adsorptions, which can increase FP value, exhibit a strong effect on FP and result in a large measurement error. Although a few studies 18,19 reported that CS could bind with ER, to our knowledge, they did not report whether CS was suitable for FP (e.g., Adamczyk’s fluorescent molecule is not suitable for FP 24) and whether CS had the nonspecific adsorption. We noticed that the CS could bind with ER, and the FP value of the CS-ERs solution increased with the increasing concentration of the ER; when all CS was saturated by ER, the FP value reached the maximum.…”

Section: Resultsmentioning

confidence: 93%

“…CS is not a newly discovered or synthesized compound; its IC 50 and RBA with respect to the ES have been reported by many authors, 18,19 but as a tracer, some of its properties need to be further determined.…”

Section: Saturation Binding Assay: Cs Had a Moderate Binding Affinitymentioning

confidence: 99%

High-Throughput Screening Assays for Estrogen Receptor by Using Coumestrol, a Natural Fluorescence Compound

Wang

Zhou

et al. 2014

SLAS Discovery

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Estrogen receptor (ER) is a ligand-inducible transcriptional factor involving in cell growth, differentiation, and diseases, so detection and identification of compounds having estrogenic effects are of great importance in the drug discovery industry. We have developed and validated a rapid, simple, and homogeneous method that can detect estrogenic compounds. This human ERα/β binding assay uses fluorescence polarization (FP) by applying an autofluorescent phytoestrogen, coumestrol (CS). A nonspecific adsorption assay shows that no obvious nonspecific adsorption is detected between CS and ERs. In the Scatchard plot analysis, the convex curve exhibits a positive cooperative binding, indicating that the binding of CS induces a conformational change of the ER to form a dimer and increases the affinity for the additional CS. In the Hill plot analysis, CS shows moderate binding affinity with both ERα and ERβ, and the measured Kdof CS is 32.66 µM and 36.14 µM, respectively, indicating that CS is applicable to the ER binding assay for determination of potent ligands of moderate binding affinity. Four typical ligands are selected to verify the ER binding assays, and the results are consistent with the reported data. All of above make the FP method based on CS suitable for high-throughput screening.

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“…[41,49,50]). The K D is mostly in the range of 10 -3 -10 -9 M. One example for a fluorescent ligand binding validation study that concerns the GMP-regulated quality assessment has been published by de Boer et al [51]. In this concentration analyses study an intra-assay precision of 7 % (RSD%) and an inter-assayprecision of 12 % (RSD%) are determined.…”

Section: Fluorescence Based Ligand Binding Assaysmentioning

confidence: 99%

Data quality in drug discovery: the role of analytical performance in ligand binding assays

Wätzig

Oltmann-Norden

Steinicke

et al. 2015

J Comput Aided Mol Des

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Despite its importance and all the considerable efforts made, the progress in drug discovery is limited. One main reason for this is the partly questionable data quality. Models relating biological activity and structures and in silico predictions rely on precisely and accurately measured binding data. However, these data vary so strongly, such that only variations by orders of magnitude are considered as unreliable. This can certainly be improved considering the high analytical performance in pharmaceutical quality control. Thus the principles, properties and performances of biochemical and cell-based assays are revisited and evaluated. In the part of biochemical assays immunoassays, fluorescence assays, surface plasmon resonance, isothermal calorimetry, nuclear magnetic resonance and affinity capillary electrophoresis are discussed in details, in addition radiation-based ligand binding assays, mass spectrometry, atomic force microscopy and microscale thermophoresis are briefly evaluated. In addition, general sources of error, such as solvent, dilution, sample pretreatment and the quality of reagents and reference materials are discussed. Biochemical assays can be optimized to provide good accuracy and precision (e.g. percental relative standard deviation <10 %). Cell-based assays are often considered superior related to the biological significance, however, typically they cannot still be considered as really quantitative, in particular when results are compared over longer periods of time or between laboratories. A very careful choice of assays is therefore recommended. Strategies to further optimize assays are outlined, considering the evaluation and the decrease of the relevant error sources. Analytical performance and data quality are still advancing and will further advance the progress in drug development.

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Development and validation of fluorescent receptor assays based on the human recombinant estrogen receptor subtypes alpha and beta

Cited by 12 publications

References 21 publications

Experimental design and measurement uncertainty in ligand binding studies by affinity capillary electrophoresis

Experimental design and measurement uncertainty in ligand binding studies by affinity capillary electrophoresis

High-Throughput Screening Assays for Estrogen Receptor by Using Coumestrol, a Natural Fluorescence Compound

Data quality in drug discovery: the role of analytical performance in ligand binding assays

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