Background and Objective: Recently, many scientific teams have been able to elucidate the structural and functional aspects of highly complex macromolecules due to the significant contribution of highly sophisticated bioinformatics platforms, representing these days a primordial steps in drug design and development processes. Materials and Methods: In this context, this work aimed to investigate in depth some fundamental properties of four bio-compounds, using diverse computational approaches but also to reveal the distribution of these compounds across kinase families and their possible biotransformation pathways. Results: The degree of polarity of compound 1 was the most important among the four tested compounds, while compound 2 exhibited the best natural product-likeness property score (P=1). Concerning metabolism part, data revealed that almost all tested compounds could be considered as non-substrate and non-inhibitor for cytochrome P450 isoforms, but could be effective to target key kinases, especially the class of serine/threonine-protein kinase. The hepatoprotective effect of compound 3 was considerably high (Pa=0.902), while compound 4 could be suitable to inhibit testosterone 17 beta-dehydrogenase (NADP⁺) (Pa=0.912). Conclusion: Both experimental and bioinformatics analysis are mandatory in this era to characterize the full potential of molecules, providing advanced research in modern biology.