QSAR modeling and molecular docking studies of 2-oxo-1, 2-dihydroquinoline-4- carboxylic acid derivatives as p-glycoprotein inhibitors for combating cancer multidrug resistance.

Multidrug resistance (MDR) proteins related to the ATP-binding cassette family are found in a very wide range of human tumors and result in therapeutic failure. The overexpression of efflux pumps such as ABCB1 is one of the mechanisms of MDR. This paper aims to develop a reliable quantitative structure-activity relationship (QSAR) model that best describes the correlation between the activity and the molecular structures in order to predict the inhibitory biological activity towards ABCB1. In this regard, a series of quinoline derivatives of 18 compounds were analyzed using different linear and non-linear machine learning (ML) regression methods including k-nearest neighbors (KNN), decision tree (DT), back propagation neural networks (BPNN) and gradient boosting-based (GB) methods. Their aim is to explain the origin of the activity of these investigated compounds and therefore, design new quinoline derivatives with higher effect on ABCB1. A total of 16 ML predictive models were developed on different number of 2D and 3D descriptors and were evaluated using the coefficient of determination (R2) and the root mean squared error (RMSE) statistical metrics. Among all developed models, A GB-based model in particular catboost achieved the highest predictive quality, with one descriptor, expressed by R2 and RMSE of 95% and 0.283 respectively. Molecular docking studies against the target crystal structure of the outward-facing p-glycoprotein (6C0V) revealed significant binding affinities via both hydrophobic and H-bond interactions with the relevant compounds. The 17 has shown the highest binding energy of -9.22 kcal/mol. Therefore, it can suggest that 17 may prove to be a valuable potential lead structure for the design and synthesis of more potent P-glycoprotein inhibitors for combination used with anti-cancer drugs for cancer multidrug resistance management.

[Application of robustness test for assessment of the measurement uncertainty at the end of development phase of a chromatographic method for quantification of water-soluble vitamins]. / Application du test de robustesse pour l'évaluation de l'incertitude de mesure au terme de phase de développement d'une méthode chromatographique de quantification de cinq vitamines hydrosolubles.

OBJECTIVE: We propose in this work an efficient way to evaluate the measurement of uncertainty at the end of the development step of an analytical method, since this assessment provides an indication of the performance of the optimization process. METHOD: The estimation of the uncertainty is done through a robustness test by applying a Placquett-Burman design, investigating six parameters influencing the simultaneous chromatographic assay of five water-soluble vitamins. The estimated effects of the variation of each parameter are translated into standard uncertainty value at each concentration level. RESULTS: The values obtained of the relative uncertainty do not exceed the acceptance limit of 5%, showing that the procedure development was well done. In addition, a statistical comparison conducted to compare standard uncertainty after the development stage and those of the validation step indicates that the estimated uncertainty are equivalent. CONCLUSION: The results obtained show clearly the performance and capacity of the chromatographic method to simultaneously assay the five vitamins and suitability for use in routine application.

Comments on "innovative method for carbon dioxide determination in human postmortem cardiac gas samples using headspace-gas chromatography-mass spectrometry and stable labeled isotope as internal standard" by Varlet et al.

Varlet et al. recently proposed a headspace-gas chromatography-mass spectrometry (HS-GC-MS) method applicable for the routine determination of CO2 in gaseous biologic matrices. This developed bioanalytical method was fully validated according to the SFSTP 1997 guidelines using the accuracy profile as a graphical decision-making tool.In this letter, we discuss the validity of HS-GC-MS method based on the newest SFSTP guideline. In particular, we demonstrate by the estimation of the ß-expectation tolerance interval that the error total exceeds the acceptance limits (30%) for the second concentration level (0.5µmol mL(-1) vial HS). Furthermore, we show through the risk profile that the probability to have future results inside the ±30% acceptance limits is smaller than 95%.

An overall uncertainty approach for the validation of analytical separation methods.

The aim of this paper is to recommend a new strategy for the analytical validation based on the uncertainty profile as a graphical decision-making tool, and to exemplify a novel method to estimate the measurement uncertainty. Indeed, the innovative formula that we offer to assess the uncertainty is based on the calculation of the ß-content tolerance interval. Three chemometric methodologies are exposed to build the (ß, γ) tolerance interval, namely: the Satterthwaite approximation, the GPQ method (generalized pivotal confidence) and the MLS procedure (modified large simple). Furthermore, we illustrate the applicability and flexibility of the uncertainty profile to assess the fitness of the purpose of chromatographic and electrophoretic analytical methods, which use different instrumental techniques such as liquid chromatography (LC-UV, LC-MS), gas chromatography (GC-FID, GC-MS) and capillary electrophoresis (CE, CE-MS). In addition, we demonstrate here that (ß, γ) tolerance intervals will provide perfect estimates of the routine uncertainty. In particular, we show that there is no difference statistically between the uncertainties estimated by our methodology as of the validation stage with those obtained from the routine phase.

Remarks on "Reply to the responses to the comments on "uncertainty profiles for the validation of analytical methods" by Saffaj and Ihssane".

This letter provides an opportunity to expand further on the problems associated with using tolerance interval for share validated analytical methods and to estimate the measurement uncertainty. Indeed, we propose at clarifying points that have been raised by Rozet et al. (Talanta 100 (2012) 290-292) as some of them merit to be discussed. In that respect, we demonstrate here that ß-content, γ-confidence tolerance intervals will provide perfect estimates of the routine uncertainty. In particular, we confirm that there is "no statistically significant difference" between the uncertainties estimated by our methodology with those obtained from the routine phase. Obviously, this is an opportunity to show which of the two types of tolerance interval i.e., ß-expectation tolerance interval or ß-content, γ-confidence tolerance interval allows a perfect estimate of the routine uncertainty. Furthermore, we prove that the ß-expectation tolerance interval does not provide an adequate balance between consumer risk and producer risk.

A Bayesian approach for application to method validation and measurement uncertainty.

The aim of this paper is to apply a new technique for the validation of quantitative analytical procedures based on Bayesian simulation and accuracy profile. Also, an original strategy for estimating measurement uncertainty by the same approach has been developed. The performance of our proposal was confirmed by application to analytical and bio-analytical methods. Compared to the classical strategy, the new approach has a more holistic character. It means that it is no longer necessary to know the various individual steps into which the analytical method can be broken down since this latter is taken as a whole. Furthermore, the Bayesian accuracy profile procedure allows to control the risk associated with the future use of the analytical method.

Uncertainty profiles for the validation of analytical methods.

This article aims to expose a new global strategy for the validation of analytical methods and the estimation of measurement uncertainty. Our purpose is to allow to researchers in the field of analytical chemistry get access to a powerful tool for the evaluation of quantitative analytical procedures. Indeed, the proposed strategy facilitates analytical validation by providing a decision tool based on the uncertainty profile and the ß-content tolerance interval. Equally important, this approach allows a good estimate of measurement uncertainty by using data validation and without recourse to other additional experiments. In the example below, we confirmed the applicability of this new strategy for the validation of a chromatographic bioanalytical method and the good estimate of the measurement uncertainty without referring to any extra effort and additional experiments. A comparative study with the SFSTP approach showed that both strategies have selected the same calibration functions. The holistic character of the measurement uncertainty compared to the total error was influenced by our choice of profile uncertainty. Nevertheless, we think that the adoption of the uncertainty in the validation stage controls the risk of using the analytical method in routine phase.