TY - CHAP
T1 - QSAR-based CMs and TOMOCOMD-CARD approach for the discovery of new tyrosinase inhibitor chemicals
AU - Casañola-Martin, Gerardo M.
AU - Le-Thi-Thu, Huong
AU - Marrero-Ponce, Yovani
AU - Torrens, Francisco
AU - Rescigno, Antonio
AU - Abad, Concepción
AU - Khan, Mahmud Tareq Hassan
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Quantitative Structure-Activity Relationship (QSAR)
KW - TOMOCOMD-CARDD
KW - Tyrosinase Inhibitor
UR - http://www.scopus.com/inward/record.url?scp=84882739568&partnerID=8YFLogxK
U2 - 10.2174/978160805379711201010298
DO - 10.2174/978160805379711201010298
M3 - Capítulo
AN - SCOPUS:84882739568
SN - 9781608054336
SP - 298
EP - 341
BT - Recent Trends on QSAR in the Pharmaeutical Perceptions
PB - Bentham Science Publishers Ltd.
ER -