No abstract

Background: The frequent use of antibacterial agents is leading to antimicrobial resistance, which is one of the biggest threats to global health today. Therefore, the discovery of novel antimicrobial agents is still urgently needed to overcome the severe infections caused by these putative pathogens resistant to currently available drugs. Objective: The present work was aimed to synthesize and investigate the preliminary structure-activity relationships (SARs) of isoxazoline and pyrazoline derivatives as antimicrobial agent. Methods: Target compounds were obtained in a multistep reaction synthesis and the antimicrobial activity was investigated in several species; two gram negative (Escherichia coli and Pseudomonas aeruginosa), two gram positive (Staphylococcus aureus and Bacillus subtilis) and one fungi (Candida albicans), using cup-plate agar diffusion method. The most potent compounds were docked into glucosamine-6-phosphate synthase (GlcN-6-P), the molecular target enzyme for antimicrobial agents, using Autodock 4.2 program. Results: Herein, thirteen novel target compounds were synthesized in moderate to good isolated yield. Based on the SARs, two compounds (2c and 5c) were found to be potent antimicrobial agents on all tested targets, recording potency higher than amoxicillin, the standard antimicrobial drug. Compound 2b identified as selective for gram negative, while compound 7a found to be selective for gram positive. The hit compounds (2c, 5a, 5c and 5d) were subjected to docking study on glucosamine-6-phosphate synthase (GlcN-6-P). All hits were found to bind to the orthosteric (active) site of the enzyme, which might represent a competitive mechanism of inhibition. Conclusion: The newly synthesized heterocyclic compounds could serve as potent leads for the development of novel antimicrobial agents.

Glycosidases, including β-D-galactosidase, are involved in a variety of metabolic disorders, such as diabetes, viral or bacterial infections, and cancer. Accordingly, we were prompted to find new β-D-galactosidase inhibitors. Towards this end, we scanned the pharmacophoric space of this enzyme using a set of 41 known inhibitors. Genetic algorithm and multiple linear regression analyses were used to select an optimal combination of pharmacophoric models and physicochemical descriptors to yield self-consistent and predictive quantitative structure-activity relationship (QSAR). Five pharmacophores emerged in the QSAR equations suggesting the existence of more than one binding mode accessible to ligands within β-D-galactosidase pocket. The successful pharmacophores were complemented with strict shape constraints in an attempt to optimize their receiver-operating characteristic curve profiles. The validity of the QSAR equations and the associated pharmacophoric models were experimentally established by the identification of several β-D-galactosidase inhibitors retrieved via in silico search of two structural databases: the National Cancer Institute list of compounds and our in house built structural database of established drugs and agrochemicals.

Glycosidases, including β-D-glucosidase, are involved in a variety of metabolic disorders such as diabetes, viral or bacterial infections and cancer. Accordingly, we were prompted to find new β-D-glucosidase inhibitors. Towards this end we scanned the pharmacophoric space of this enzyme using a set of 41 known inhibitors. Genetic algorithm and multiple linear regression analyses were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors to yield self-consistent and predictive quantitative structure-activity relationship (QSAR). Three pharmacophores emerged in the QSAR equations, suggesting the existence of more than one binding mode accessible to ligands within the β-D-glucosidase pocket. The successful pharmacophores were complemented with strict shape constraints in an attempt to optimize their receiver-operating characteristic (ROC) curve profiles. The validity of the QSAR equations and the associated pharmacophoric models were established experimentally by the identification of several β-D-glucosidase inhibitors retrieved via in silico search of two structural databases, namely the National Cancer Institute (NCI) list of compounds, and our in-house structural database of established drugs and agrochemicals (DAC).

KEYWORDS(E)-Chalcone derivatives were synthesized by the Claisen-Schmidt condensation of aromatic aldehydes with methyl ketones. 5-Arylfuran-2-carboxaldehydes (1a-b) were synthesized by Meerwein´s method and condensed with 2-acetylpyrole or 2-acetylfuran to produce the new chalcone derivatives (2a-d). The new chalcones were characterized using FT-IR and GC-MS. The synthesized compounds were also screened against some bacterial species to evaluate their activity as promising antibacterial agents.