Identification of Novel Tyrosinase Inhibitors with Nanomolar Potency Using Virtual Screening Approaches

Abstract

Introduction: Hyperpigmentation disorders are caused by excess production of the pigment melanin, catalyzed by the enzyme tyrosinase. Novel tyrosinase inhibitors are needed as therapeutic agents to treat these conditions.

Method: To discover new inhibitors, we performed a virtual screening of the ZINC20 library containing 1.4 billion compounds. An initial filter for drug-likeness, ADMET properties, and synthetic accessibility reduced the library to 10,217 hits. Quantitative structure-activity relationship (QSAR) modeling of this subset predicted nanomolar inhibitory potency for several chemical scaffolds. Comparative molecular docking studies and rigorous binding energy calculations further prioritized four cysteine-containing dipeptide compounds based on predicted strong binding affinity and mode to tyrosinase.

Results: Microsecond-long molecular dynamics simulations provided additional atomistic insights into the stability of inhibitor-enzyme binding interactions. This integrated computational workflow effectively sampled an extremely large chemical space to discover four novel tyrosinase inhibitors with half-maximal inhibitory concentration values below 10 nM.

Conclusion: Overall, this demonstrates the power of virtual screening and multi-faceted computational techniques to accelerate the discovery of potent bioactive ligands from massive compound libraries by efficiently sampling chemical space.

Keywords: QSAR.; Tyrosinase; molecular docking; molecular dynamics simulation.