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ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery
Orphan nuclear receptors are potential therapeutic targets. The Orphan Nuclear Receptor Ligand Binding Database (ONRLDB) is an interactive, comprehensive and manually curated database of small molecule ligands targeting orphan nuclear receptors. Currently, ONRLDB consists of ∼11 000 ligands, of whic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4669993/ https://www.ncbi.nlm.nih.gov/pubmed/26637529 http://dx.doi.org/10.1093/database/bav112 |
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author | Nanduri, Ravikanth Bhutani, Isha Somavarapu, Arun Kumar Mahajan, Sahil Parkesh, Raman Gupta, Pawan |
author_facet | Nanduri, Ravikanth Bhutani, Isha Somavarapu, Arun Kumar Mahajan, Sahil Parkesh, Raman Gupta, Pawan |
author_sort | Nanduri, Ravikanth |
collection | PubMed |
description | Orphan nuclear receptors are potential therapeutic targets. The Orphan Nuclear Receptor Ligand Binding Database (ONRLDB) is an interactive, comprehensive and manually curated database of small molecule ligands targeting orphan nuclear receptors. Currently, ONRLDB consists of ∼11 000 ligands, of which ∼6500 are unique. All entries include information for the ligand, such as EC50 and IC50, number of aromatic rings and rotatable bonds, XlogP, hydrogen donor and acceptor count, molecular weight (MW) and structure. ONRLDB is a cross-platform database, where either the cognate small molecule modulators of a receptor or the cognate receptors to a ligand can be searched. The database can be searched using three methods: text search, advanced search or similarity search. Substructure search, cataloguing tools, and clustering tools can be used to perform advanced analysis of the ligand based on chemical similarity fingerprints, hierarchical clustering, binning partition and multidimensional scaling. These tools, together with the Tree function provided, deliver an interactive platform and a comprehensive resource for identification of common and unique scaffolds. As demonstrated, ONRLDB is designed to allow selection of ligands based on various properties and for designing novel ligands or to improve the existing ones. Database URL: http://www.onrldb.org/ |
format | Online Article Text |
id | pubmed-4669993 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-46699932015-12-07 ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery Nanduri, Ravikanth Bhutani, Isha Somavarapu, Arun Kumar Mahajan, Sahil Parkesh, Raman Gupta, Pawan Database (Oxford) Original Article Orphan nuclear receptors are potential therapeutic targets. The Orphan Nuclear Receptor Ligand Binding Database (ONRLDB) is an interactive, comprehensive and manually curated database of small molecule ligands targeting orphan nuclear receptors. Currently, ONRLDB consists of ∼11 000 ligands, of which ∼6500 are unique. All entries include information for the ligand, such as EC50 and IC50, number of aromatic rings and rotatable bonds, XlogP, hydrogen donor and acceptor count, molecular weight (MW) and structure. ONRLDB is a cross-platform database, where either the cognate small molecule modulators of a receptor or the cognate receptors to a ligand can be searched. The database can be searched using three methods: text search, advanced search or similarity search. Substructure search, cataloguing tools, and clustering tools can be used to perform advanced analysis of the ligand based on chemical similarity fingerprints, hierarchical clustering, binning partition and multidimensional scaling. These tools, together with the Tree function provided, deliver an interactive platform and a comprehensive resource for identification of common and unique scaffolds. As demonstrated, ONRLDB is designed to allow selection of ligands based on various properties and for designing novel ligands or to improve the existing ones. Database URL: http://www.onrldb.org/ Oxford University Press 2015-11-04 /pmc/articles/PMC4669993/ /pubmed/26637529 http://dx.doi.org/10.1093/database/bav112 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Nanduri, Ravikanth Bhutani, Isha Somavarapu, Arun Kumar Mahajan, Sahil Parkesh, Raman Gupta, Pawan ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title | ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title_full | ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title_fullStr | ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title_full_unstemmed | ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title_short | ONRLDB—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
title_sort | onrldb—manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4669993/ https://www.ncbi.nlm.nih.gov/pubmed/26637529 http://dx.doi.org/10.1093/database/bav112 |
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