The simultaneous detection and quantification of p-aminobenzoic acid and its phase 2 biotransformation metabolites in human urine using LC–MS/MS

Design, synthesis and molecular modeling of isatin-aminobenzoic acid hybrids as antibacterial and antibiofilm agents

Number of factors, including newly emerging infectious diseases and an increase in multi-drug resistant microbial pathogens with particular relevance for Gram-positive bacteria, make the treatment of infectious diseases in hospital-based healthcare a major challenge in the medical community. 4-Aminobenzoic acid (PABA), has demonstrated a variety of biological actions particularly, antimicrobial activity. In our study we coupled this vitamin-like molecule with different isatin derivatives. We investigated the antibacterial activity of the synthesized Schiff's bases. The compounds showed high selective activity against Gram-positive bacteria and showed weak or no activity against both Gram-negative bacteria and fungi. Compound 2a showed highest activity against S. aureus and B. subtilis (MIC 0.09 mmol/L). Additionally, these substances exhibit strong anti-B. Subtilis biofilm formation. We were able to shed insight on the binding mode of these new inhibitors using in silico docking of the compounds in the binding sites of a 3D structure of B. subtilis histidine kinase/Walk. The binding free energy of the compound 2a to the catalytic domain walk, of histidine kinase enzyme of B. subtilis bacteria, was calculated using molecular mechanics/generalized born surface area scoring. The key residues for macromolecule-ligand binding were postulated. The optimized 3D protein-ligand binding modes shed light on the B. subtilis HK/Walk-ligand interactions that afford a means to assess binding affinity to design new HK/Walk inhibitor as antibacterial agents.

Virtual Screening, Structural Analysis, and Formation Thermodynamics of Carbamazepine Cocrystals

In this study, the existing set of carbamazepine (CBZ) cocrystals was extended through the successful combination of the drug with the positional isomers of acetamidobenzoic acid. The structural and energetic features of the CBZ cocrystals with 3- and 4-acetamidobenzoic acids were elucidated via single-crystal X-ray diffraction followed by QTAIMC analysis. The ability of three fundamentally different virtual screening methods to predict the correct cocrystallization outcome for CBZ was assessed based on the new experimental results obtained in this study and data available in the literature. It was found that the hydrogen bond propensity model performed the worst in distinguishing positive and negative results of CBZ cocrystallization experiments with 87 coformers, attaining an accuracy value lower than random guessing. The method that utilizes molecular electrostatic potential maps and the machine learning approach named CCGNet exhibited comparable results in terms of prediction metrics, albeit the latter resulted in superior specificity and overall accuracy while requiring no time-consuming DFT computations. In addition, formation thermodynamic parameters for the newly obtained CBZ cocrystals with 3- and 4-acetamidobenzoic acids were evaluated using temperature dependences of the cocrystallization Gibbs energy. The cocrystallization reactions between CBZ and the selected coformers were found to be enthalpy-driven, with entropy terms being statistically different from zero. The observed difference in dissolution behavior of the cocrystals in aqueous media was thought to be caused by variations in their thermodynamic stability.

Combinative ex vivo studies and in silico models ProTox-II for investigating the toxicity of chemicals used mainly in cosmetic products

Human data on remains sparse and of varying quality and reproducibility. Ex vivo experiments and animal experiments currently is the most preferred way to predict the skin sensitization approved by the regulatory agencies across the world. However, there is a constant need and demand to reduce animal experiments and provide the scope of alternative methods to animal testing. In this study, we have compared the predictive performance of the published computational tools such as ProTox-II, SuperCYPsPred with the data obtained from ex-vivo experiments. From the results of the retrospective analysis, it can be observed that the computational predictions are in agreement with the experimental results. The computational models used here are generative models based on molecular structures and machine learning algorithms and can be applied also for the prediction of skin sensitization. Besides prediction of the toxicity endpoints, the models can also provide deeper insights into the molecular mechanisms and adverse outcome pathways (AOPs) associated with the chemicals used in cosmetic products.

4-Aminobenzoic Acid Derivatives: Converting Folate Precursor to Antimicrobial and Cytotoxic Agents

4-aminobenzoic acid (PABA), an essential nutrient for many human pathogens, but dispensable for humans, and its derivatives have exhibited various biological activities. In this study, we combined two pharmacophores using a molecular hybridization approach: this vitamin-like molecule and various aromatic aldehydes, including salicylaldehydes and 5-nitrofurfural, via imine bond in one-step reaction. Resulting Schiff bases were screened as potential antimicrobial and cytotoxic agents. The simple chemical modification of non-toxic PABA resulted in constitution of antibacterial activity including inhibition of methicillin-resistant Staphylococcus aureus (minimum inhibitory concentrations, MIC, from 15.62 µM), moderate antimycobacterial activity (MIC ≥ 62.5 µM) and potent broad-spectrum antifungal properties (MIC of ≥ 7.81 µM). Some of the Schiff bases also exhibited notable cytotoxicity for cancer HepG2 cell line (IC50 ≥ 15.0 µM). Regarding aldehyde used for the derivatization of PABA, it is possible to tune up the particular activities and obtain derivatives with promising bioactivities.

A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us?

INTRODUCTION

Manifestations of fatigue range from chronic fatigue up to a severe syndrome and myalgic encephalomyelitis. Fatigue grossly affects the functional status and quality of life of affected individuals, prompting the World Health Organization to recognize it as a chronic non-communicable condition.

OBJECTIVES

Here, we explore the potential of urinary metabolite information to complement clinical criteria of fatigue, providing an avenue towards an objective measure of fatigue in patients presenting with the full spectrum of fatigue levels.

METHODS

The experimental group consisted of 578 chronic fatigue female patients. The measurement design was composed of (1) existing clinical fatigue scales, (2) a hepatic detoxification challenge test, and (3) untargeted proton nuclear magnetic resonance (¹H-NMR) procedure to generate metabolomics data. Data analysed via an in-house Matlab script that combines functions from a Statistics and a PLS Toolbox.

RESULTS

Multivariate analysis of the original 459 profiled ¹H-NMR bins for the low (control) and high (patient) fatigue groups indicated complete separation following the detoxification experimental challenge. Important bins identified from the ¹H-NMR spectra provided quantitative metabolite information on the detoxification challenge for the fatigue groups.

CONCLUSIONS

Untargeted ¹H-NMR metabolomics proved its applicability as a global profiling tool to reveal the impact of toxicological interventions in chronic fatigue patients. No clear potential biomarker emerged from this study, but the quantitative profile of the phase II biotransformation products provide a practical visible effect directing to up-regulation of crucial phase II enzyme systems in the high fatigue group in response to a high xenobiotic-load.

Biotransformation profiles from a cohort of chronic fatigue women in response to a hepatic detoxification challenge

Chronic fatigue, in its various manifestations, frequently co-occur with pain, sleep disturbances and depression and is a non-communicable condition which is rapidly becoming endemic worldwide. However, it is handicapped by a lack of objective definitions and diagnostic measures. This has prompted the World Health Organization to develop an international instrument whose intended purpose is to improve quality of life (QOL), with energy and fatigue as one domain of focus. To complement this objective, the interface between detoxification, the exposome, and xenobiotic-sensing by nuclear receptors that mediate induction of biotransformation-linked genes, is stimulating renewed attention to a rational development of strategies to identify the metabolic profiles in complex multifactorial conditions like fatigue. Here we present results from a seven-year study of a cohort of 576 female patients suffering from low to high levels of chronic fatigue, in which phase I and phase II biotransformation was assessed. The biotransformation profiles used were based on hepatic detoxification challenge tests through oral caffeine, acetaminophen and acetylsalicylic acid ingestion coupled with oxidative stress analyses. The interventions indicated normal phase I but increased phase II glucuronidation and glycination conjugation. Complementarity was indicated between a fatigue scale, medical symptoms and associated energy-related parameters by application of Chi-square Automatic Interaction Detector (CHAID) analysis. The presented study provides a cluster of data from which we propose that multidisciplinary inputs from the combination of a fatigue scale, medical symptoms and biotransformation profiles provide the rationale for the development of a comprehensive laboratory instrument for improved diagnostics and personalized interventions in patients with chronic fatigue with a view to improving their QOL.

New insights into the catalytic mechanism of human glycine N-acyltransferase

Even though the glycine conjugation pathway was one of the first metabolic pathways to be discovered, this pathway remains very poorly characterized. The bi-substrate kinetic parameters of a recombinant human glycine N-acyltransferase (GLYAT, E.C. 2.3.1.13) were determined using the traditional colorimetric method and a newly developed HPLC-ESI-MS/MS method. Previous studies analyzing the kinetic parameters of GLYAT, indicated a random Bi-Bi and/or ping-pong mechanism. In this study, the hippuric acid concentrations produced by the GLYAT enzyme reaction were analyzed using the allosteric sigmoidal enzyme kinetic module. Analyses of the initial rate (v) against substrate concentration plots, produced a sigmoidal curve (substrate activation) when the benzoyl-CoA concentrations was kept constant, whereas the plot with glycine concentrations kept constant, passed through a maximum (substrate inhibition). Thus, human GLYAT exhibits mechanistic kinetic cooperativity as described by the Ferdinand enzyme mechanism rather than the previously assumed Michaelis-Menten reaction mechanism.