Novel 1,3-dioxolane–coumarin hybrids: From synthesis to pharmacological In Vitro-In Silico profiling
Abstract
In this study, we report the design, synthesis, and comprehensive biological evaluation of a novel series of linear 1,3-dioxolane–coumarin hybrids (DCH1–DCH7) as promising multi-target therapeutic agents. The synthesis involved an optimized multi-step approach beginning with a Pechmann condensation followed by selective esterification reactions, yielding high-purity compounds confirmed via FTIR, 1H-NMR, and 13C-NMR analyses. The hybrids were systematically screened for their antioxidant, anticancer, anti-inflammatory, antidiabetic, and antimicrobial activities. In addition, their biocompatibility was assessed using non-cancerous human cell lines and commensal bacterial strains. Among the synthesized hybrids, DCH4 exhibited remarkable antioxidant and anticancer properties, while DCH1 showed superior anti-inflammatory and antifungal activity. DCH2 demonstrated potent antidiabetic and anti-anaerobic bacterial efficacy, and DCH5 emerged as the most active against aerobic gram-negative bacteria. These bioactivities were closely linked to specific structural modifications, as revealed through structure–activity relationship analyses. In silico evaluations using ProTox-II, PreADME, and SwissADME tools predicted favorable drug-likeness, low toxicity, high oral bioavailability, and acceptable pharmacokinetic profiles, further supporting their therapeutic relevance. Importantly, all hybrids displayed minimal cytotoxic effects on non-cancerous cells and exhibited selective…
Read the paper
Related studies
- Quantum dots: synthesis, bioapplications, and toxicity
- A Guide to In Silico Drug Design
- Quantum Computing for Healthcare: A Review
- Automated in Silico Design of Homogeneous Catalysts
- Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach
- In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.