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In silico Discovery of Novel Tyrosinase Inhibitors using Atom Based Linear Indices
Gerardo M. Casañola-Martín
* 1, 2 ,
Yovani Marrero-Ponce
1, 3 ,
Mahmud Tareq Hassan Khan
4, 5 ,
Arjumand Ather
5 ,
Mukhlis N. Sultankhodzhaev
6 ,
Francisco Torrens
3
1  Unit of Computer-Aided Molecular “Biosilico” Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy and Department of Drug Design, Chemical Bioactive Center. Central University of Las Villas, Santa Clara, 54830, Villa Clara, C
2  Department of Biological Sciences, Faculty of Agricultural Sciences, University of Ciego de Avila, 69450, Ciego de Avila, Cuba
3  Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, Poligon la Coma s/n (detras de Canal Nou) P. O. Box 22085, E-46071 Valencia, Spain
4  Pharmacology Research Laboratory, Faculty of Pharmaceutical Sciences, University of Science and Technology Chittagong, Chittagong, Bangladesh
5  Department of Biochemistry and Molecular Biology, Center for Biotechnology, University of Ferrara, Via L. Borsari, 46, FE 44100 Ferrara, Italy
6  S. Yunusov Institute of Chemistry of Plant Substances, Academy of Sciences, Uzbekistan, Tashkent
Published: 30 November 2006 by MDPI in The 10th International Electronic Conference on Synthetic Organic Chemistry session Computational Chemistry
https://doi.org/10.3390/ecsoc-10-01451
Abstract: In the present report it is presented the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones. In this sense, discriminant models were applied and globally good classifications of 93.51% and 92.46% were observed for non-stochastic and stochastic linear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67% and 89.44%. In addition, these fitted models were used in the screening of new cycloartane compounds isolated from herbal plants. A good behaviour is showed between the theoretical and experimental results. These results provided a useful tool that can be used in the identification of new tyrosinase inhibitor compounds.
Keywords: TOMOCOMD-CARDD Software, Atom-based Linear Indices, LDA-based QSAR Model, Tyrosinase Inhibitor, Cycloartanes, Ligand-based Virtual Screening
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