From laboratory to computer models: Enhancing coumarin discovery through interdisciplinary research

Coumarin-derived compounds have garnered extensive interest due to their diverse applications in medicinal chemistry, pharmacology, food, and cosmetics. There are pros and cons to both in vitro and in silico methods used in coumarin-based research. The focus is on their roles, pros, and cons in finding out the biomedical properties of these compounds. In vitro studies, conducted in controlled environments, enable detailed investigations into cellular mechanisms, enzyme interactions, and cytotoxic effects. These studies are valuable for elucidating coumarin’s biological activity and therapeutic potential. Although these studies are accurate, morally acceptable, and repeatable, their inability to fully replicate complex biological systems necessitates extrapolation to real-life situations. In contrast, in silico studies leverage computational tools to model molecular interactions, predict pharmacokinetic behaviors, and simulate biological pathways. These techniques are time- and cost-efficient, capable of high-throughput screening, and useful for hypothesis generation. However, their reliability depends on the accuracy of input data and assumptions, which can limit their predictive power in real-world scenarios. Integrating these two study types provides a synergistic framework that enhances coumarin-based research. In silico models can guide the design of experiments, while in vitro assays validate computational predictions. Emerging technologies, such as machine learning, organ-on-a-chip systems, and 3D cell cultures, promise to further refine this integration, enabling faster, more accurate, and ethical research. We conducted an investigation and a literature review, utilizing PubMed data and limiting the publication period from 2000 to mid-2024. This study demonstrates the effective combination of in vitro and in silico methods to advance coumarin-based research and unlock its full therapeutic potential.