QSAR-Based CMs and TOMOCOMD-CARD Approach for the Discovery of New Tyrosinase Inhibitor Chemicals.

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.