Enhanced parrot optimizer for Meridianin derivative design: Synthesis optimization, biological evaluation, and molecular docking insights

• Enhanced Parrot Optimizer (EPO) algorithm is introduced as an effective tool for optimizing the synthesis of meridianin derivatives, showcasing its power in high-dimensional optimization problems. • Optimization of synthesis parameters (temperature, reaction time, solvent ratio) led to a high reaction yield of 92.3% and a purity of 95.4%, outperforming conventional methods. • Compound 3b exhibited 95.2% cytotoxicity inhibition of MCF7 cells, the highest among synthesized compounds, establishing it as a promising candidate for anticancer applications. • Compound 3b also demonstrated the lowest IC50 value (42.5 µg/mL) in antioxidant activity, highlighting its potential for combating oxidative stress-related diseases. • Molecular docking studies revealed strong binding interactions between compound 3b and significant protein targets, such as EGFR (-9.2 kcal/mol), BCL-2 (-8.7 kcal/mol), and VEGFR (-8.5 kcal/mol), supporting its multi-targeting capabilities. • The study compares the Enhanced Parrot Optimizer (EPO) with other popular metaheuristic algorithms, such as PSO, GA, and ACO, and shows EPO’s superior convergence rate, stability, and optimization power. • The findings provide an integrated framework for the rational design of bioactive compounds through the synergy of computational optimization, experimental validation, and molecular docking, advancing drug discovery in medicinal chemistry. Meridianin derivatives, which were discovered to possess multifarious biological activities, have excellent potential to be used as multifunctional therapeutic agents, particularly in cancer and oxidative stress-related disease treatments. However, the challenges associated with increasing their synthesis and defining SARs have limited their extensive application. This study attempts to overcome these challenges by using an Enhanced Parrot Optimizer (EnPO), a highly efficient metaheuristic algorithm, to optimize key synthesis parameters, including reaction temperature, time, and solvent ratio, in an attempt to maximize the yield and purity of the reaction. The optimized synthesis conditions were evaluated through computational modeling, while in silico biological activity was assessed via molecular docking simulations. Docking experiments revealed strong interactions between meridianin derivatives and major protein targets. Comparative studies confirmed that EnPO outperformed conventional optimization techniques, such as PSO, GA, and ACO, in terms of convergence speed, solution quality, and robustness. The novelty of this study lies in the development and application of a behaviorally adaptive optimizer (EnPO), integrating hierarchical guidance, mimicry dynamics, and weighted behavior selection—features absent in traditional algorithms. This work represents the first integration of such an optimizer for simultaneous computational optimization and biological evaluation of meridianin derivatives. The findings reported that the optimal synthesis parameters yielded meridianin derivatives with a reaction yield of 92.3% and purity of 95.4%. Compound 3b demonstrated the highest cytotoxicity, exhibiting 95.2% inhibition of MCF7 cells, and the lowest IC50 value for antioxidant activity at 42.5 µg/mL. The docking results showed high binding affinities, with compound 3b exhibiting the best binding energy to EGFR at -9.2 kcal/mol through hydrogen bonding and π-π stacking interactions.This study demonstrates the efficacy of the Enhanced Parrot Optimizer for driving chemical synthesis optimization and highlights the therapeutic potential of meridianin derivatives as multi-target agents.