A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors
The tyrosinase is a bifunctional, copper-containing enzyme widely distributed in the phylogenetic tree. This en-zyme is involved in the production of melanin and some other pigments in humans, animals and plants, including skin pigmentations in mammals, and browning process in plants and vegetable...
Saved in:
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
Bentham Science Publishers
2016
|
Subjects: | |
Online Access: | http://repository.vnu.edu.vn/handle/VNU_123/11503 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Vietnam National University, Hanoi |
Language: | English |
id |
oai:112.137.131.14:VNU_123-11503 |
---|---|
record_format |
dspace |
spelling |
oai:112.137.131.14:VNU_123-115032017-04-05T14:27:40Z A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors Le, Thi Thu Huong Drug-likenessfiltering Molecular docking QSAR modeling Similarity searching Tyrosinase inhibitor Virtual screening The tyrosinase is a bifunctional, copper-containing enzyme widely distributed in the phylogenetic tree. This en-zyme is involved in the production of melanin and some other pigments in humans, animals and plants, including skin pigmentations in mammals, and browning process in plants and vegetables. Therefore, enzyme inhibitors has been under the attention of the scientist community, due to its broad applications in food, cosmetic, agricultural and medicinal fields, to avoid the undesirable effects of abnormal melanin overproduction. However, the research of novel chemical with anti-tyrosinase activity demands the use of more efficient tools to speed up the tyrosinase inhibitors discovery process. This chapter is focused in the different components of a predictive modeling workflow for the identification and prioritization of potential new compounds with activity against the tyrosinase enzyme. In this case, two structure chemical libraries Spectrum Collectionand Drugbankare used in this attempt to combine different virtual screening data mining tech-niques, in a sequential manner helping to avoid the usually expensive andtime consumingtraditional methods. Some of the sequential steps summarize here comprise the use of drug-likenessfilters, similarity searching, classificationand po-tencyQSAR multiclassifier systems, modeling molecular interactions systems, and similarity/diversity analysis. Finally, the methodologies showed here provide a rational workflow for virtual screening hit analysis and selection as a promis-sory drug discovery strategy for use in target identification phase 2016-05-30T17:34:14Z 2016-05-30T17:34:14Z 2014 Article 1568-0266 http://repository.vnu.edu.vn/handle/VNU_123/11503 en application/pdf Bentham Science Publishers |
institution |
Vietnam National University, Hanoi |
building |
VNU Library & Information Center |
country |
Vietnam |
collection |
VNU Digital Repository |
language |
English |
topic |
Drug-likenessfiltering Molecular docking QSAR modeling Similarity searching Tyrosinase inhibitor Virtual screening |
spellingShingle |
Drug-likenessfiltering Molecular docking QSAR modeling Similarity searching Tyrosinase inhibitor Virtual screening Le, Thi Thu Huong A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
description |
The tyrosinase is a bifunctional, copper-containing enzyme widely distributed in the phylogenetic tree. This en-zyme is involved in the production of melanin and some other pigments in humans, animals and plants, including skin
pigmentations in mammals, and browning process in plants and vegetables. Therefore, enzyme inhibitors has been under
the attention of the scientist community, due to its broad applications in food, cosmetic, agricultural and medicinal fields,
to avoid the undesirable effects of abnormal melanin overproduction. However, the research of novel chemical with anti-tyrosinase activity demands the use of more efficient tools to speed up the tyrosinase inhibitors discovery process. This
chapter is focused in the different components of a predictive modeling workflow for the identification and prioritization
of potential new compounds with activity against the tyrosinase enzyme. In this case, two structure chemical libraries
Spectrum Collectionand Drugbankare used in this attempt to combine different virtual screening data mining tech-niques, in a sequential manner helping to avoid the usually expensive andtime consumingtraditional methods. Some of
the sequential steps summarize here comprise the use of drug-likenessfilters, similarity searching, classificationand po-tencyQSAR multiclassifier systems, modeling molecular interactions systems, and similarity/diversity analysis. Finally,
the methodologies showed here provide a rational workflow for virtual screening hit analysis and selection as a promis-sory drug discovery strategy for use in target identification phase |
format |
Article |
author |
Le, Thi Thu Huong |
author_facet |
Le, Thi Thu Huong |
author_sort |
Le, Thi Thu Huong |
title |
A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
title_short |
A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
title_full |
A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
title_fullStr |
A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
title_full_unstemmed |
A Rational Workflow for Sequential Virtual Screening of Chemical Libraries on Searching for New Tyrosinase Inhibitors |
title_sort |
rational workflow for sequential virtual screening of chemical libraries on searching for new tyrosinase inhibitors |
publisher |
Bentham Science Publishers |
publishDate |
2016 |
url |
http://repository.vnu.edu.vn/handle/VNU_123/11503 |
_version_ |
1680966061348880384 |