Literature DB >> 24666037

NRLiSt BDB, the manually curated nuclear receptors ligands and structures benchmarking database.

Nathalie Lagarde1, Nesrine Ben Nasr, Aurore Jérémie, Hélène Guillemain, Vincent Laville, Taoufik Labib, Jean-François Zagury, Matthieu Montes.   

Abstract

Nuclear receptors (NRs) constitute an important class of drug targets. We created the most exhaustive NR-focused benchmarking database to date, the NRLiSt BDB (NRs ligands and structures benchmarking database). The 9905 compounds and 339 structures of the NRLiSt BDB are ready for structure-based and ligand-based virtual screening. In the present study, we detail the protocol used to generate the NRLiSt BDB and its features. We also give some examples of the errors that we found in ChEMBL that convinced us to manually review all original papers. Since extensive and manually curated experimental data about NR ligands and structures are provided in the NRLiSt BDB, it should become a powerful tool to assess the performance of virtual screening methods on NRs, to assist the understanding of NR's function and modulation, and to support the discovery of new drugs targeting NRs. NRLiSt BDB is freely available online at http://nrlist.drugdesign.fr .

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Year:  2014        PMID: 24666037     DOI: 10.1021/jm500132p

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


  18 in total

1.  Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.

Authors:  Jie Xia; Ermias Lemma Tilahun; Eyob Hailu Kebede; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2015-02-09       Impact factor: 4.956

2.  Consensus queries in ligand-based virtual screening experiments.

Authors:  Francois Berenger; Oanh Vu; Jens Meiler
Journal:  J Cheminform       Date:  2017-11-28       Impact factor: 5.514

3.  Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

Authors:  Jie Xia; Terry-Elinor Reid; Song Wu; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2018-05-08       Impact factor: 4.956

4.  Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores.

Authors:  Nathalie Lagarde; Solenne Delahaye; Jean-François Zagury; Matthieu Montes
Journal:  J Cheminform       Date:  2016-09-06       Impact factor: 5.514

5.  Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors.

Authors:  David Lagorce; Dominique Douguet; Maria A Miteva; Bruno O Villoutreix
Journal:  Sci Rep       Date:  2017-04-11       Impact factor: 4.379

Review 6.  Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement.

Authors:  Viet-Khoa Tran-Nguyen; Didier Rognan
Journal:  Int J Mol Sci       Date:  2020-06-19       Impact factor: 5.923

7.  Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction.

Authors:  Joel Wahl; Martin Smieško
Journal:  Int J Mol Sci       Date:  2018-06-15       Impact factor: 5.923

8.  Exponential consensus ranking improves the outcome in docking and receptor ensemble docking.

Authors:  Karen Palacio-Rodríguez; Isaias Lans; Claudio N Cavasotto; Pilar Cossio
Journal:  Sci Rep       Date:  2019-03-26       Impact factor: 4.379

9.  ONRLDB--manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery.

Authors:  Ravikanth Nanduri; Isha Bhutani; Arun Kumar Somavarapu; Sahil Mahajan; Raman Parkesh; Pawan Gupta
Journal:  Database (Oxford)       Date:  2015-12-04       Impact factor: 3.451

Review 10.  Decoys Selection in Benchmarking Datasets: Overview and Perspectives.

Authors:  Manon Réau; Florent Langenfeld; Jean-François Zagury; Nathalie Lagarde; Matthieu Montes
Journal:  Front Pharmacol       Date:  2018-01-24       Impact factor: 5.810

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