Green Synthesized Silver Nanoparticles Using Lactobacillus Acidophilus as an Antioxidant, Antimicrobial, and Antibiofilm Agent Against Multi-drug Resistant Enteroaggregative Escherichia Coli.

The present study was envisaged to employ the green synthesis and characterization of silver nanoparticles (AgNPs) using the potential probiotic strain Lactobacillus acidophilus, to assess its antibacterial as well as antibiofilm activity against multi-drug-resistant enteroaggregative Escherichia coli (MDR-EAEC) strains and to investigate their antioxidant activity. In this study, AgNPs were successfully synthesized through an eco-friendly protocol, which was then confirmed by its X-ray diffraction (XRD) pattern. A weight loss of 15% up to 182 °C with a narrow exothermic peak between 170 °C and 205 °C was observed in thermogravimetric analysis-differential thermal analysis (TGA-DTA), while aggregated nanoclusters were observed in scanning electron microscopy (SEM). Moreover, the transmission electron microscopy (TEM) imaging of AgNPs revealed a spherical morphology and crystalline nature with an optimum size ranging from 10 to 20 nm. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values of green synthesized AgNPs against the MDR-EAEC strains were found to be 7.80 mg/L and 15.60 mg/L, respectively. In vitro time-kill kinetic assay revealed a complete elimination of the MDR-EAEC strains after 180 min on co-incubation with the AgNPs. Moreover, the green synthesized AgNPs were found safe by in vitro haemolytic assay. Besides, the green synthesized AgNPs exhibited significant biofilm inhibition (P < 0.001) formed by MDR-EAEC strains. Additionally, a concentration-dependent antioxidant activity was observed in 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. Hence, this study demonstrated potential antibacterial as well as antibiofilm activity of green synthesized AgNPs against MDR-EAEC strains with antioxidant properties and warrants further in-depth studies to explore it as an effective antimicrobial agent against MDR infections.

Virtual screening and repositioning of inconclusive molecules of beta-lactamase Bioassays-A data mining approach.

This study focuses on the best possible way forward in utilizing inconclusive molecules of PubChem bioassays AID 1332, AID 434987 and AID 434955, which are related to beta-lactamase inhibitors of Mycobacterium tuberculosis (Mtb). The inadequacy in the experimental methods that were observed during the invitro screening resulted in an inconclusive dataset. This could be due to certain moieties present within the molecules. In order to reconsider such molecules, insilico methods can be suggested in place of invitro methods For instance, datamining and medicinal chemistry methods: have been adopted to prioritise the inconclusive dataset into active or inactive molecules. These include the Random Forest algorithm for dataminning, Lilly MedChem rules for virtually screening out the promiscuity, and Self Organizing Maps (SOM) for clustering the active molecules and enlisting them for repositioning through the use of artificial neural networks. These repositioned molecules could then be prioritized for downstream drug discovery analysis.