Natural chemical compounds have been widely investigated for their programmed necrosis causing characteristics. One of the conventional methods for screening such compounds is the use of concentrated plant extracts without isolation of active moieties for understanding pharmacological activity. For the last two decades, modern medicine has relied mainly on the isolation and purification of one or two complicated active and isomeric compounds. The idea of multi-target drugs has advanced rapidly and impressively from an innovative model when first proposed in the early 2000s to one of the popular trends for drug development in 2021. Alternatively, fragment-based drug discovery is also explored in identifying target-based drug discovery for potent natural anticancer agents which is based on well-defined fragments opposite to use of naturally occurring mixtures. This review summarizes the current key advancements in natural anticancer compounds; computer-assisted/fragment-based structural elucidation and a multi-target approach for the exploration of natural compounds.

No abstract

No abstract

Background: PIM (Proviral Integration site for Moloney Murine Leukemia virus) kinases are members of the class of kinase family serine/ threonine kinases, which play a crucial role in cancer development. As there is no drug in the market against PIM-1, kinase has transpired as a budding and captivating target for discovering new anticancer agents targeting PIM-1 kinase. Aim: The current research pondered the development of new PIM-1 kinase inhibitors by applying a ligand-based and structure-based drug discovery approach involving 3D QSAR, molecular docking, and dynamics simulation. Method: In this study, association allying the structural properties and biological activity was undertaken using 3D-QSAR analysis. The 3D-QSAR model was generated with the help of 35 compounds from which the best model manifested an appreciated cross-validation coefficient (q2) of 0.8866 and conventional correlation coefficient (r2) of 0.9298, respectively and predicted correlation coefficient (r2 pred) was obtained as 0.7878. Result: The molecular docking analysis demonstrated that the analogs under analysis occupied the active site of PIM-1 kinase receptor and interactions with Lys67 in the catalytic region, Asp186 in the DFG motif, and Glu171 were noticed with numerous compounds. Discussion: Furthermore, the molecular dynamics simulation study stated that the ligand portrayed the strong conformational stability within the active site of PIM-1 kinase protein, forming of two hydrogen bonds until 100 ns, respectively. Conclusion: Overall outcomes of the study revealed that applications of the ligand-based drug discovery approach and structure-based drug discovery strategy conceivably applied to discovering new PIM-1 kinase inhibitors as anticancer agents.