Abstract
In this review an overview of the application of computational approaches is given. Specifically, the uses of Quantitative Structure-Activity Relationship (QSAR) methods for in silico identification of new families of compounds as novel tyrosinase inhibitors are revised. Assembling, validation of models through prediction series, and virtual screening of external data sets are also shown, to prove the accuracy of the QSAR models obtained with the TOMOCOMD-CARDD (TOpological MOlecular COMputational Design- Computer-Aided Rational Drug Design) software and Linear Discriminant Analysis (LDA) as statistical technique. Together with this, a database is collected for these QSAR studies, and could be considered a useful tool in future QSAR modeling of tyrosinase activity and for scientists that work in the field of this enzyme and its inhibitors. Finally, a translation to real world applications is shown by the use of QSAR models in the identification and posterior in-vitro evaluation of different families of compounds. Several different classes of compounds from various sources (natural and synthetic) were identified. Between them, we can find tetraketones, cycloartanes, ethylsteroids, lignans, dicoumarins and vanilloid derivatives. Finally, some considerations are discussed in order to improve the identification of novel drug-like compounds based on the use of QSAR-Ligand-Based Virtual Screening (LBVS).
Keywords: Tyrosinase Inhibitor, TOMOCOMD-CARDD, Quantitative Structure-Activity Relationship (QSAR), Ligand-Based Virtual Screening (LBVS), Linear Discriminant Analysis (LDA), melanin hyperpigmentation, Melanogenesis, ligand-guided drug design, neuro-informatics, molecular descrip-tors (MDs), Dragon software, kojic acid tripeptides, novel N-substituded N-nitrosohydroxylamines, STATISTICA, BIOACTIVITY CONVERGENCE, Atom-Based Bilinear Indices, Wilks, ’, statistics, non-stochastic bilinear indices, Anti-Tyrosinase Activity, LBVS, Atom-Based Quadratic Indices, QSAR-LDA, Lignan Family, Cluster Analysis, K-means cluster analysis, Matthews´correlation coefficient
Current Pharmaceutical Design
Title: Ligand-Based Computer-Aided Discovery of Tyrosinase Inhibitors. Applications of the TOMOCOMD-CARDD Method to the Elucidation of New Compounds
Volume: 16 Issue: 24
Author(s): Yovani Marrero-Ponce, Gerardo M. Casanola-Martin, Mahmud Tareq Hassan Khan, Francisco Torrens, Antonio Rescigno and Concepcion Abad
Affiliation:
Keywords: Tyrosinase Inhibitor, TOMOCOMD-CARDD, Quantitative Structure-Activity Relationship (QSAR), Ligand-Based Virtual Screening (LBVS), Linear Discriminant Analysis (LDA), melanin hyperpigmentation, Melanogenesis, ligand-guided drug design, neuro-informatics, molecular descrip-tors (MDs), Dragon software, kojic acid tripeptides, novel N-substituded N-nitrosohydroxylamines, STATISTICA, BIOACTIVITY CONVERGENCE, Atom-Based Bilinear Indices, Wilks, ’, statistics, non-stochastic bilinear indices, Anti-Tyrosinase Activity, LBVS, Atom-Based Quadratic Indices, QSAR-LDA, Lignan Family, Cluster Analysis, K-means cluster analysis, Matthews´correlation coefficient
Abstract: In this review an overview of the application of computational approaches is given. Specifically, the uses of Quantitative Structure-Activity Relationship (QSAR) methods for in silico identification of new families of compounds as novel tyrosinase inhibitors are revised. Assembling, validation of models through prediction series, and virtual screening of external data sets are also shown, to prove the accuracy of the QSAR models obtained with the TOMOCOMD-CARDD (TOpological MOlecular COMputational Design- Computer-Aided Rational Drug Design) software and Linear Discriminant Analysis (LDA) as statistical technique. Together with this, a database is collected for these QSAR studies, and could be considered a useful tool in future QSAR modeling of tyrosinase activity and for scientists that work in the field of this enzyme and its inhibitors. Finally, a translation to real world applications is shown by the use of QSAR models in the identification and posterior in-vitro evaluation of different families of compounds. Several different classes of compounds from various sources (natural and synthetic) were identified. Between them, we can find tetraketones, cycloartanes, ethylsteroids, lignans, dicoumarins and vanilloid derivatives. Finally, some considerations are discussed in order to improve the identification of novel drug-like compounds based on the use of QSAR-Ligand-Based Virtual Screening (LBVS).
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Cite this article as:
Marrero-Ponce Yovani, M. Casanola-Martin Gerardo, Tareq Hassan Khan Mahmud, Torrens Francisco, Rescigno Antonio and Abad Concepcion, Ligand-Based Computer-Aided Discovery of Tyrosinase Inhibitors. Applications of the TOMOCOMD-CARDD Method to the Elucidation of New Compounds, Current Pharmaceutical Design 2010; 16 (24) . https://dx.doi.org/10.2174/138161210792389216
DOI https://dx.doi.org/10.2174/138161210792389216 |
Print ISSN 1381-6128 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4286 |
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