Literature DB >> 30354114

Nuclear Receptors Database Including Negative Data (NR-DBIND): A Database Dedicated to Nuclear Receptors Binding Data Including Negative Data and Pharmacological Profile.

Manon Réau1, Nathalie Lagarde1,2, Jean-François Zagury1, Matthieu Montes1.   

Abstract

Nuclear receptors (NRs) are transcription factors that regulate gene expression in various physiological processes through their interactions with small hydrophobic molecules. They constitute an important class of targets for drugs and endocrine disruptors and are widely studied for both health and environment concerns. Since the integration of negative data can be critical for accurate modeling of ligand activity profiles, we manually collected and annotated NRs interaction data (positive and negative) through a sharp review of the corresponding literature. 15 116 positive and negative interactions data are provided for 28 NRs together with 593 PDB structures in the freely available Nuclear Receptors Database Including Negative Data ( http://nr-dbind.drugdesign.fr ). The NR-DBIND contains the most extensive information about interaction data on NRs, which should bring valuable information to chemists, biologists, pharmacologists and toxicologists.

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Year:  2018        PMID: 30354114     DOI: 10.1021/acs.jmedchem.8b01105

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  5 in total

1.  Predicting the binding of small molecules to nuclear receptors using machine learning.

Authors:  Azhagiya Singam Ettayapuram Ramaprasad; Martyn T Smith; David McCoy; Alan E Hubbard; Michele A La Merrill; Kathleen A Durkin
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

2.  Hits Discovery on the Androgen Receptor: In Silico Approaches to Identify Agonist Compounds.

Authors:  Manon Réau; Nathalie Lagarde; Jean-François Zagury; Matthieu Montes
Journal:  Cells       Date:  2019-11-13       Impact factor: 6.600

3.  Predicting Potential Endocrine Disrupting Chemicals Binding to Estrogen Receptor α (ERα) Using a Pipeline Combining Structure-Based and Ligand-Based in Silico Methods.

Authors:  Asma Sellami; Matthieu Montes; Nathalie Lagarde
Journal:  Int J Mol Sci       Date:  2021-03-11       Impact factor: 5.923

4.  Allosteric Regulation of 3CL Protease of SARS-CoV-2 and SARS-CoV Observed in the Crystal Structure Ensemble.

Authors:  Akinori Kidera; Kei Moritsugu; Toru Ekimoto; Mitsunori Ikeguchi
Journal:  J Mol Biol       Date:  2021-10-27       Impact factor: 5.469

Review 5.  Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns.

Authors:  Asma Sellami; Manon Réau; Matthieu Montes; Nathalie Lagarde
Journal:  Front Endocrinol (Lausanne)       Date:  2022-09-13       Impact factor: 6.055

  5 in total

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