Tyrosinase is an oxidoreductase enzyme (EC 1.14.18.1) involved in the two main
steps of the biochemical melanin pathway. In humans it is also related to the process of freeradical
scavenging avoiding UV-radiations side-effects. However, abnormal overproduction
of melanin lead to hyperpigmentation, that includes, melanoma, lentigenes, age spots and
other skin disorders. Therefore, the research of novel chemical with inhibitory activity against
the enzyme remains as a challenge to scientific community. In this chapter we survey the
results achieved in the elucidation of new tyrosinase inhibitors by using Quantitative
Structure-Activity Relationships (QSAR) and TOMOCOMD-CARDD (TOpological
MOlecular COMputational Design-Computer-Aided Rational Drug Design) approach. Later,
the use of different chemometric, machine learning and artificial intelligence techniques for
modeling the tyrosinase inhibitory activity is showed. Finally, it has been shown that the
algorithm proposed in this chapter was being used to the ligand-based virtual screening of
several in-house databases, and many classes of compounds from both natural and synthetic
sources. These compounds were found to have potent inhibitory profiles against the enzyme
compared to the current reference depigmenting agents, kojic acid and L-mimosine.
Keywords: Tyrosinase Inhibitor, TOMOCOMD-CARDD, Quantitative Structure-
Activity Relationship (QSAR).
