6533b838fe1ef96bd12a516f
RESEARCH PRODUCT
New tyrosinase inhibitors selected by atomic linear indices-based classification models.
Mahmud Tareq Hassan KhanMahmud Tareq Hassan KhanArjumand AtherM. N. SultankhodzhaevFrancisco TorrensYovani Marrero-ponceYovani Marrero-ponceGerardo M. Casañola-martinsubject
Quantitative structure–activity relationshipMolecular modelStereochemistryTyrosinaseClinical BiochemistryMolecular ConformationPharmaceutical ScienceQuantitative Structure-Activity RelationshipBiochemistrySensitivity and SpecificityChemometricsDrug DiscoveryComputer SimulationEnzyme InhibitorsMolecular BiologyTraining setChemistryMonophenol MonooxygenaseOrganic ChemistryLinear discriminant analysisTriterpenesDiscriminantModels ChemicalTopological indexMolecular MedicineBiological systemdescription
In the present report, the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones is presented. 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 behavior is shown between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2005-09-09 | Bioorganicmedicinal chemistry letters |