Phenolics, abundant in plants, constitute a significant portion of phytoconstituents consumed in the human diet. The phytochemical screening of the aerial parts of Centaurium spicatum led to the isolation of five phenolics. The anti-tyrosinase activities of the isolated compounds were assessed through a combination of in vitro experiments and multiple in silico approaches. Docking and molecular dynamics (MD) simulation techniques were utilized to figure out the binding interactions of the isolated phytochemicals with tyrosinase. The findings from molecular docking analysis revealed that the isolated phenolics were able to bind effectively to tyrosinase and potentially inhibit substrate binding, consequently diminishing the catalytic activity of tyrosinase. Among isolated compounds, cichoric acid displayed the lowest binding energy and the highest extent of polar interactions with the target enzyme. Analysis of MD simulation trajectories indicated that equilibrium was reached within 30 ns for all complexes of tyrosinase with the isolated phenolics. Among the five ligands studied, cichoric acid exhibited the lowest interaction energies, rendering its complex with tyrosinase the most stable. Considering these collective findings, cichoric acid emerges as a promising candidate for the design and development of a potential tyrosinase inhibitor. Furthermore, the in vitro anti-tyrosinase activity assay unveiled significant variations among the isolated compounds. Notably, cichoric acid exhibited the most potent inhibitory effect, as evidenced by the lowest IC50 value (7.92 ± 1.32 µg/ml), followed by isorhamnetin and gentiopicrin. In contrast, sinapic acid demonstrated the least inhibitory activity against tyrosinase, with the highest IC50 value. Moreover, cichoric acid exhibited a mixed inhibition mode against the hydrolysis of l-DOPA catalyzed by tyrosinase, with Ki value of 1.64. Remarkably, these experimental findings align well with the outcomes of docking and MD simulations, underscoring the consistency and reliability of our computational predictions with the actual inhibitory potential observed in vitro.
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