In silico modelling of azole derivatives with tyrosinase inhibition ability: Application of the models for activity prediction of new compounds
| Autor: | Indrani Adhikari, Ashis Nandy, Binoy Behari Goswami, Biplab De, Achintya Saha |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Azoles
In silico Tyrosinase Quantitative Structure-Activity Relationship Multifunctional Enzymes 01 natural sciences Biochemistry Melanin Structural Biology Animals Enzyme Inhibitors chemistry.chemical_classification Molecular Structure 010405 organic chemistry Monophenol Monooxygenase Organic Chemistry 0104 chemical sciences Molecular Docking Simulation 010404 medicinal & biomolecular chemistry Computational Mathematics Enzyme chemistry Docking (molecular) Azole Pharmacophore |
| Zdroj: | Computational biology and chemistry. 74 |
| ISSN: | 1476-928X |
| Popis: | Tyrosinase is a metal containing multifunctional enzymes found in animals, fruits and vegetables and constitutes the primary cause for diseases resulting from overproduction of melanin as well as for browning of fruits. Inhibitors of the enzyme have thus gained increased importance in food and cosmetic industry. In the present work, a group of azole derivatives with tyrosinase inhibitory activity were explored to analyse the prime structural attributes of the potent inhibitors. In silico models have been developed in order to have a close insight regarding features of the molecular fragments that may affect the activity of the molecules conducively. The biological pharmacophore of the inhibitors that accounts for their interaction with the tyrosinase enzyme has been ascertained based on the development of a 3D pharmacophore model. The models thus developed were subsequently utilised for screening a set of compounds that were previously synthesised in-house and were reported to possess antioxidant activity. The final selection of active molecules in the screening process was done based on the docking interactions of the molecules with the tyrosinase enzyme and assessment of their degree of binding to the protein. Thus the developed models have been successfully utilised for identifying active compounds from a series of untested molecules. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect