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 mainsteps of the biochemical melanin pathway. In humans it is also related to the process of freeradicalscavenging avoiding UV-radiations side-effects. However, abnormal overproductionof melanin lead to hyperpigmentation, that includes, melanoma, lentigenes, age spots andother skin disorders. Therefore, the research of novel chemical with inhibitory activity againstthe enzyme remains as a challenge to scientific community. In this chapter we survey theresults achieved in the elucidation of new tyrosinase inhibitors by using QuantitativeStructure-Activity Relationships (QSAR) and TOMOCOMD-CARDD (TOpologicalMOlecular COMputational Design-Computer-Aided Rational Drug Design) approach. Later,the use of different chemometric, machine learning and artificial intelligence techniques formodeling the tyrosinase inhibitory activity is showed. Finally, it has been shown that thealgorithm proposed in this chapter was being used to the ligand-based virtual screening ofseveral in-house databases, and many classes of compounds from both natural and syntheticsources. These compounds were found to have potent inhibitory profiles against the enzymecompared to the current reference depigmenting agents, kojic acid and L-mimosine.