Abstract

Background: As a part of our discovery of plant-based lead molecules, we provide a helpful tool, which helps in identification, designing, optimising, structural modifications, and prediction of curcumin, to discover novel analogs with enhanced bioavailability, pharmacologically safe, and anticancer potential.

Methods: QSAR (Quantitative structure-activity relationship) and pharmacophore mapping models were developed and further used to design, synthesize, pharmacokinetics, and in vitro evaluation of curcumin analogs for anticancer activity.

Results: The QSAR model yielded a high activity-descriptors relationship accuracy (r²) of 84%, a high activity prediction accuracy (rcv²) of 81%, and external set prediction accuracy of 89%. The QSAR study indicates that the five chemical descriptors were significantly correlated with anticancer activity. The important pharmacophore features identified were a hydrogen bond acceptor, a hydrophobic centre, and a negative ionizable centre. The model's predictive ability was evaluated against a set of chemically synthesized curcumin analogs. Among the tested compounds, nine curcumin analogs were found with IC₅₀ values of 0.10 to 1.86 μg/mL. The active analogs were assessed for pharmacokinetics compliance. EGFR was identified as a potential target of synthesized active curcumin analogs through docking studies.

Conclusion: Integrating in silico design, QSAR-driven virtual screening, chemical synthesis, and experimental in vitro evaluation may lead to the early discovery of novel and promising anticancer compounds from natural sources. The developed QSAR model and common pharmacophore generation were used as a designing and predictive tool to develop novel curcumin analogs. This study may help optimize the therapeutic relationships of studied compounds for further drug development and their potential safety concerns. This study may guide compound selection and designing novel active chemical scaffolds or new combinatorial libraries of the curcumin series.