Discovery of Potential Tyrosinase Inhibitors via Machine Learning and Molecular Docking with Experimental Validation of Activity and Skin Permeation.

ABSTRACT: Tyrosinase, a copper-dependent oxidase, plays a critical role in melanin biosynthesis and is a target in skin-whitening cosmetics. Conventional inhibitors like arbutin and kojic acid are widely used but suffer from cytotoxicity, instability, and inconsistent efficacy, highlighting the need for safer, more effective alternatives. In this study, two ligand-based machine learning models were developed: one to predict the biological activity of compounds and the other to estimate specific pIC₅₀ values. These models were employed to screen potential tyrosinase inhibitors from natural product libraries and FDA-approved drug databases. Subsequently, the molecules identified through machine learning screening were subjected to more precise multi tyrosinase-like structures molecular dock

SUBMITTER: Kang W 

PROVIDER: S-EPMC12409553 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature