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Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database
Gao, HW (Gao, Hongwei)
2018
Source PublicationPHYTOMEDICINE
ISSN0944-7113
Volume38Issue:1Pages:145-157
Abstract

Background: Tyrosinase plays a key role in the formation of skin melanin. The excessive accumulation of skin melanin will cause the serious aesthetic problems for human beings. Hypothesis/purpose: To find the potent tyrosinase inhibitors using computational simulation from TCM Database@Taiwan. Study design: Inhibitors of tyrosinase have been thought as potential drugs for the decrease of melanin synthesis in the process of pigmentation. To develop new tyrosinase inhibitors, we performed a virtual screening from Traditional Chinese medicine (TCM) and Druglike Databases using the best 3D QSAR pharmacophore model as a 3D search query. Methods: A total of 109 compounds were obtained after filtering by Lipinski's rule of five. Finally, 148 compounds (22 from training set, 17 from test set, 109 from TCM and Druglike databases) were selected for further docking studies. De Novo Evolution designed the top 10 candidates from the docking results. Results: Hypo1 was selected as the best quantitative pharmacophore model, because Hypo1 has characters of the highest cost difference (353.773), the lowest RMS (1.985), the lowest Error (121.440), and the best correlation coefficient (0.933). By the analysis of interaction amino acids in the top 10 hits including two controls, HIS42, HIS60, HIS204, HIS208, ARG209 and VAL218 are identified as the key binding site residues, ARG209 and VAL218 are the critical residues for the inhibitory activity of tyrosinase. This finding is consistent with the results from literatures. Conclusion: De Novo Evolution study suggested Tyrosinase_1(star)_Evo_4, Tyrosinase_23(star)_Evo_7, magnolone.cdx_15_Evo_4, compound_2.cdx_2_Evo_2, Compound_B_Evo_5, Compound_C_Evo_9, Compound_D_Evo_6 and malabaricone_C.cdx_3_Evo_10 as the potential tyrosinase inhibitor candidates. De Novo Evolution study also suggested compound_2.cdx_2_Evo_2 as the most potential tyrosinase inhibitor candidate. A total of ten novel leading compounds were identified to have the favorable interaction with tyrosinase by the docking analyses.

KeywordTyrosinase Inhibitors Tcm Pharmacophore Models Docking
DOI10.1016/j.phymed.2017.11.012
Indexed BySCI
WOS IDWOS:000425172900016
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/5220
Collection省部共建新疆特有药用资源利用重点实验室
AffiliationChinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Key Lab Plant Resources & Chem Arid Reg, Urumqi 830011, Peoples R China
Recommended Citation
GB/T 7714
Gao, HW . Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database[J]. PHYTOMEDICINE,2018,38(1):145-157.
APA Gao, HW .(2018).Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database.PHYTOMEDICINE,38(1),145-157.
MLA Gao, HW ."Predicting tyrosinase inhibition by 3D QSAR pharmacophore models and designing potential tyrosinase inhibitors from Traditional Chinese medicine database".PHYTOMEDICINE 38.1(2018):145-157.
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