Current Topics in Medicinal Chemistry - Volume 18, Issue 11, 2018

Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.

Observational experimental designs are usually employed in metabolomics to elucidate pathological mechanisms underlying disease development and to discover candidate biomarkers for diagnosis. However, intervention trials can also be a suitable starting point before performing a validation study in lager epidemiological cohorts, with a great potential in personalized medicine to investigate how different patients respond to similar stimuli. In the present work, we provide a review of the literature on the application of metabolomics to investigate metabolic alterations associated with diabetes, the diabetes predisposing state of insulin resistance and the oral glucose tolerance test as a case study to demonstrate the complementarity of observational and interventional study designs.

Neurodegenerative diseases are likely to emerge as the second cause of mortality in the world in coming years. NDDs cause tremendous financial burden on the healthcare system along with profound effect on families and patient. Disease-modifying treatment strategies with proven efficacy for these disorders are still lacking. Documentation proved that oxidative stress plays a leading role in the pathophysiology of many neurodegenerative disorders. Molecules with good antioxidant profile could be explored for the doctoring of these conditions. Neuroprotective effects of bioflavonoid morin have been well recognized in the literature. Morin being super antioxidant compound helped in preventing and curing these disorders by suppression of ROS and by inhibition of multiple targets. In this review, we tried to explain various neuropathological conditions with their target sites and neurobiological mechanisms of morin.

In this paper, a Multilinear Regression (MLR) analysis has been carried out in order to accurately predict physicochemical properties and biological activities of a group of antibacterial quinolones by means of a set of structural descriptors called topological indices. The aim of this work is to develop prediction equations for these properties after collecting the maximum number of data from the literature on antibacterial quinolones. The five regression functions selected by presenting the best combination of various statistical parameters, subsequently validated by means of internal validation (intercorrelation, Y-randomization and leave-one-out cross-validation tests), allowed the reliable prediction of minimum inhibitory concentration 50 versus Staphylococcus aureus (MIC50Sa), Streptococcus pyogenes (MIC50Spy) and Bacteroides fragilis (MIC50Bf), Mean Residence Time (MRT) after oral administration and volume of distribution (VD). We conclude that the combination of molecular topology methods and MLR provides an excellent tool for the prediction of pharmacological properties.

Research on new antimicrobial agents is needed, as more and more microorganisms that cause antibiotic-resistant diseases are emerging commercially. In this group, we can find strains of Staphylococcus aureus and Escherichia coli, which are highly opportunistic species. Faced with this perspective, research using essential oils present in plants is emerging as a therapeutic alternative for the treatment of antimicrobial infections. Many of these oils have, in their composition, monoterpene α-pinene, that shows to have antibacterial activity. The purpose of this research is to evaluate the antimicrobial activity of the positive enantiomer of α-pinene against strains of Staphylococcus aureus ATCC 25923 and Escherichia coli ATCC 25922. The methodologies used were: Disc-diffusion test, broth microdilution and bacterial death kinetics, all of which were standardized by CLSI. As a result, inhibition halos of 11 mm was obtained for the gram-positive strain and 12 mm for the gram-negative strain, both at the same concentration, 160 μl / ml. In addition, it was possible to observe with the death curve that the concentrations (1.25 μl/mL and 2.5 μl/mL of the (+)-α-pinene were able to eliminate the formation of bacterial colonies at one time of exposure of 2 hours for the E. coli strain. However, the death curve of the S. aureus strain was characterized by non-elimination of bacterial colonies at a 24 hours exposure time used for the experiment. Only amikacin evidenced its bacterial killing rate of all colonies within two hours of exposure. At the end, it was possible to verify the activity of the phytoconstituent against Escherichia coli strains ATCC 25922 and Staphylococcus aureus ATCC 25923, recommending the continuity of the studies with the use of different methodologies so that (+) - α-pinene in the future can be a compound used in antimicrobial therapy.

Background: Despite several advancements in antifungal drug discovery, fungal diseases like Invasive Candidiasis (IC) still remain associated with high rates of morbidity and mortality worldwide. Thus there is an enormous need for anti-Candida drugs. Objective: The main objectives of the work included: 1. To investigate therapeutically significant classes of secondary metabolites produced by S. chrestomyceticus strain ADP4. 2. To investigate and analyze inhibition of significant virulence attributes of C. albicans, such as, biofilm and secretory hydrolytic enzymes by ADP4 secondary metabolites. 3. Mechanistic analysis of probable compounds for their site of action on Secretary Aspartyl Proteinase 3 (Sap3). Methods: Metabolite extract-SDB (MESDB) of S. chrestomyceticus strain ADP4 was fractionated on silica gel column chromatography. Fractions were analyzed for anti-Candida activity by disc diffusion assay. Active fractions were further purified by differential solvent treatment. MIC90 values were determined by broth dilution method. MFC was based on counting viable cells. Inhibition of yeast to hyphae transition and that of production of hydrolytic enzymes were estimated by plate assays. GC-MS of MESDB and Partially Purified Metabolite preparations (PPMs) was done. GRIP docking studies with Sap 3 of C. albicans was done using VLife MDS 4.6 software. Results: Chemical profiling showed that ADP4 secondary metabolites contained alkaloids, flavonoids, polyphenols, terpenoids and triterpenes. The MESDB and the PPMs showed low or no cytotoxicity but were able to effectively contain virulence attributes of Candida pathogen. Docking studies revealed that some of the probable compounds have affinity for aspartic acid residue in Sap3 enzyme of C. albicans. Conclusion: Secondary metabolite of strain ADP4 included important classes of therapeutically important compounds. Their anti-Candida activity was mediated by inhibition of critical virulence factors of the pathogen.