Literature DB >> 15993056

A physicogenetic method to assign ligand-binding relationships between 7TM receptors.

Thomas M Frimurer1, Trond Ulven, Christian E Elling, Lars-Ole Gerlach, Evi Kostenis, Thomas Högberg.   

Abstract

A computational protocol has been devised to relate 7TM receptor proteins (GPCRs) with respect to physicochemical features of the core ligand-binding site as defined from the crystal structure of bovine rhodopsin. The identification of such receptors that already are associated with ligand information (e.g., small molecule ligands with mutagenesis or SAR data) is used to support structure-guided drug design of novel ligands. A case targeting the newly identified prostaglandin D2 receptor CRTH2 serves as a primary example to illustrate the procedure.

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Year:  2005        PMID: 15993056     DOI: 10.1016/j.bmcl.2005.05.102

Source DB:  PubMed          Journal:  Bioorg Med Chem Lett        ISSN: 0960-894X            Impact factor:   2.823


  11 in total

1.  Seeing the future of bioactive lipid drug targets.

Authors:  Jilly F Evans; John H Hutchinson
Journal:  Nat Chem Biol       Date:  2010-07       Impact factor: 15.040

2.  Chemogenomic approaches to drug discovery: similar receptors bind similar ligands.

Authors:  T Klabunde
Journal:  Br J Pharmacol       Date:  2007-05-29       Impact factor: 8.739

Review 3.  Chemogenomic approaches to rational drug design.

Authors:  D Rognan
Journal:  Br J Pharmacol       Date:  2007-05-29       Impact factor: 8.739

4.  Computational chemogenomics: is it more than inductive transfer?

Authors:  J B Brown; Yasushi Okuno; Gilles Marcou; Alexandre Varnek; Dragos Horvath
Journal:  J Comput Aided Mol Des       Date:  2014-04-27       Impact factor: 3.686

5.  Protein-ligand interaction prediction: an improved chemogenomics approach.

Authors:  Laurent Jacob; Jean-Philippe Vert
Journal:  Bioinformatics       Date:  2008-08-01       Impact factor: 6.937

6.  Virtual screening of GPCRs: an in silico chemogenomics approach.

Authors:  Laurent Jacob; Brice Hoffmann; Véronique Stoven; Jean-Philippe Vert
Journal:  BMC Bioinformatics       Date:  2008-09-06       Impact factor: 3.169

7.  A systematic prediction of multiple drug-target interactions from chemical, genomic, and pharmacological data.

Authors:  Hua Yu; Jianxin Chen; Xue Xu; Yan Li; Huihui Zhao; Yupeng Fang; Xiuxiu Li; Wei Zhou; Wei Wang; Yonghua Wang
Journal:  PLoS One       Date:  2012-05-30       Impact factor: 3.240

8.  Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets.

Authors:  Gerard Jp van Westen; Remco F Swier; Jörg K Wegner; Adriaan P Ijzerman; Herman Wt van Vlijmen; Andreas Bender
Journal:  J Cheminform       Date:  2013-09-23       Impact factor: 5.514

9.  Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets.

Authors:  Gerard Jp van Westen; Remco F Swier; Isidro Cortes-Ciriano; Jörg K Wegner; John P Overington; Adriaan P Ijzerman; Herman Wt van Vlijmen; Andreas Bender
Journal:  J Cheminform       Date:  2013-09-24       Impact factor: 5.514

Review 10.  Computational approaches in target identification and drug discovery.

Authors:  Theodora Katsila; Georgios A Spyroulias; George P Patrinos; Minos-Timotheos Matsoukas
Journal:  Comput Struct Biotechnol J       Date:  2016-05-07       Impact factor: 7.271

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