Bioorganic and Medicinal Chemistry Reports

Given the pharmacological significance of fluorine-containing heterocycles, in the present paper, a series of benzimidazole having fluoro-benzene moiety within a single molecular framework were screened for their in vitro antimicrobial activity against some Gram-positive and Gram-negative bacteria and fungal strains. The results of antimicrobial activity demonstrated that fluoro-substituted compounds (13-15 and 17-19) have good antibacterial and antifungal properties as compared to unsubstituted parent compounds (12 and 16). Compound 18 with meta-fluoro substitution group on the phenyl ring of the side chain displayed high activity against Gram-negative bacteria with a MIC value of 31.25 μg/mL. Similarly, 2-(m-fluorophenyl)-benzimidazole derivatives 14 and 18 showed good anti-B. subtilis with a MIC value of 7.81 μg/mL. SAR studies suggested that the presence of methyl substitution group at position 5 of benzimidazole is recommended for significant antifungal activity against C. parapsilosis. The high potency suggested that compound 18 could be a starting point for further optimization to develop novel antimicrobial agents.

Acetylcholinesterase is the main neurotransmitter in the cholinergic system. Impairment of the cholinergic system can be a reason for Alzheimer's and multiple sclerosis. Alzheimer's disease and multiple sclerosis affect patients and their relatives' daily lives enormously. New therapies with more benefits than current therapies for these diseases would facilitate patients' lives. In this respect, discovering novel acetylcholine esterase inhibitors with more effective and fewer side effects is highly important.  Machine learning algorithms are very useful to predict the activity of molecules for a biological target. In this study, our classification models were built with Deep Neural Networks (DNN), Support Vector Machines (SVM), and Extreme Gradient Boosting (XGBoost) to predict molecules as active or inactive for acetylcholinesterase inhibitors. These models were evaluated with various metrics. As a result, The DNN model showed a better ability to classify (accuracy=0.93, F1 score=0.88, MCC=0.8, Roc-Auc=0.89 in the test set) molecules than the other models.

In the present study, GC-FID method for the determination of lidocaine HCl in commercially creams and injection forms was developed and validated. The linearity of method was observed in the concentration range of 0.1-5.0 µg/mL. The accuracy (RE%) and precision (RSD%) values of the within-day and between-day of GC-FID method are less than 10.0% and 3.0%, respectively, and also limit of detection (LOD)  and the limit of quantitation (LOQ) values  were observed as 0.03 and 0.11 µg/mL, respectively. The analytical recovery value of lidocaine HCl was determined as 99.47% on average. As a result, it was concluded that the developed and validated GC-FID method can be easily used in routine analyzes in quality control laboratories.  

Compounds bearing naphthalene and benzimidazole pharmacophores have been reported to possess excellent anticancer activity. In view of this, we designed, synthesized and characterized a series of naphthalene substituted benzimidazole derivatives (11–19), and further evaluated them for antiproliferative activities by employing MTT method. Among the nine investigated molecules, compounds (11 and 13) showed good antiproliferation of the tested cancer cell lines with IC50 values ranging from 0.078 to 0.625 µM. In addition, compound (18) exhibited selective cytotoxicity against HepG2 cell lines with high safety to normal cell (HEK293). Furthermore, cytotoxicity studies of these compounds against normal Human embryonic kidney cells (HEK293) revealed that the target molecules were less selective against HEK293 as compared to methotrexate (positive control). The high potency and selective cytotoxicity suggested that compound 18 could be a starting point for further optimization to develop novel antitumor agents towards liver cancer.