Scientia Pharmaceutica

This study reports the exclusive and rapid synthesis of twenty-four derivatives of 1-((mono/bis)trifluoromethyl)phenyl-3-(4-arylthiazol-2-yl)thioureas (series 7, 9 and 11), along with their antimicrobial activities against Candida albicans, Mycobacterium smegmatis and seven additional bacterial strains. The anticancer potential of these compounds was evaluated against various human cancer cell lines, including A549 (lung adenocarcinoma), HeLa (cervical carcinoma), IMR32 (neuroblastoma), MCF-7 (breast adenocarcinoma), HCT116 (colon cancer) and DU145 (prostate cancer). Among these, 1-(3,5-bistrifluoromethylphenyl)-3-(thiazol-2-yl)thiourea (7i) and 1-(4-trifluoromethylphenyl)-3-(4-(3-chlorophenyl)thiazol-2-yl)thiourea (11h) demonstrated significant antimicrobial activity against M. luteus, S. aureus, S. aureus 1 and C. albicans. Additionally, 1-(4-(3-chlorophenyl)thiazol-2-yl)-3-(3-trifluoromethylphenyl)thiourea (9g) and 1-(4-trifluoromethylphenyl)-3-(4-(2-fluorophenyl)thiazol-2-yl)thiourea (11g) showed activity against Mycobacterium smegmatis. The bioassay tests indicated that many of the thiourea derivatives exhibited moderate activity against the A549, HeLa, MCF-7 and HCT116 cancer cell lines.

Mental health disorders, particularly anxiety and insomnia, are increasingly prevalent worldwide, prompting interest in herbal-based complementary therapies. This study surveyed 168 Hungarian healthcare professionals to evaluate their knowledge and recommendations regarding herbal sedatives and analyzed seven commonly suggested OTC products available in Hungary, using thin-layer chromatography (TLC) and UV–Vis spectrophotometry according to the European Pharmacopoeia. The survey revealed that 86.9% of respondents recommend herbal products for nervous system complaints, with Valeriana officinalis and Melissa officinalis being the preferred ingredients. Herbal teas and traditional herbal medicines were the most frequently suggested product categories. Laboratory analysis confirmed the presence of marker compounds in all tested products; however, significant variability in active ingredient concentrations was observed. One homeopathic product contained an unidentified alkaloid-like compound, raising safety concerns. Essential oil yields from tea mixtures also varied markedly, and some products did not meet pharmacopoeial standards for hypericin content. These findings highlight the popularity of phytotherapy among healthcare professionals and the need for stricter quality control of OTC herbal sedatives. Future research should include multi-batch analyses and clinical trials to establish robust evidence for efficacy and safety.

Drug discovery is a complex and expensive process in which only a small proportion of candidate molecules reach clinical approval. Computational methods, particularly computer-aided drug design (CADD), have become fundamental to accelerate and optimize early stages of discovery by integrating chemical, biological, and pharmacokinetic information into predictive models. This review outlines a complete computational workflow for chemical compound analysis, covering molecular structure generation, database selection, evaluation of absorption, distribution, metabolism, excretion and toxicity (ADMET), target prediction, and molecular docking. It focuses on freely accessible and web-based tools that enable reproducible, cost-effective, and scalable in silico studies. Key platforms such as PubChem, ChEMBL, RDKit, SwissADME, TargetNet, and SwissDock are highlighted as examples of how different resources can be integrated to support rational compound design and prioritization. The article also discusses essential methodological principles, data curation strategies, and common limitations in virtual screening and docking analyses. Finally, it explores future directions in computational drug discovery, including the incorporation of artificial intelligence, multi-omics integration, and quantum simulations, to enhance predictive accuracy and translational relevance.