Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.

Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.

In this study, we report a ligand-guided homology modeling approach allowing the analysis of relevant binding site residue conformations and the identification of two novel histamine H3 receptor ligands with binding affinity in the nanomolar range. The newly developed method is based on exploiting a...

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Bibliographic Details
Main Authors: David Schaller, Stefanie Hagenow, Holger Stark, Gerhard Wolber
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0218820
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spelling doaj-b5dadd02760e4ea09cccb90ae0c19b592021-03-03T20:36:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01146e021882010.1371/journal.pone.0218820Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.David SchallerStefanie HagenowHolger StarkGerhard WolberIn this study, we report a ligand-guided homology modeling approach allowing the analysis of relevant binding site residue conformations and the identification of two novel histamine H3 receptor ligands with binding affinity in the nanomolar range. The newly developed method is based on exploiting an essential charge interaction characteristic for aminergic G-protein coupled receptors for ranking 3D receptor models appropriate for the discovery of novel compounds through virtual screening.https://doi.org/10.1371/journal.pone.0218820
collection DOAJ
language English
format Article
sources DOAJ
author David Schaller
Stefanie Hagenow
Holger Stark
Gerhard Wolber
spellingShingle David Schaller
Stefanie Hagenow
Holger Stark
Gerhard Wolber
Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
PLoS ONE
author_facet David Schaller
Stefanie Hagenow
Holger Stark
Gerhard Wolber
author_sort David Schaller
title Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
title_short Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
title_full Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
title_fullStr Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
title_full_unstemmed Ligand-guided homology modeling drives identification of novel histamine H3 receptor ligands.
title_sort ligand-guided homology modeling drives identification of novel histamine h3 receptor ligands.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description In this study, we report a ligand-guided homology modeling approach allowing the analysis of relevant binding site residue conformations and the identification of two novel histamine H3 receptor ligands with binding affinity in the nanomolar range. The newly developed method is based on exploiting an essential charge interaction characteristic for aminergic G-protein coupled receptors for ranking 3D receptor models appropriate for the discovery of novel compounds through virtual screening.
url https://doi.org/10.1371/journal.pone.0218820
work_keys_str_mv AT davidschaller ligandguidedhomologymodelingdrivesidentificationofnovelhistamineh3receptorligands
AT stefaniehagenow ligandguidedhomologymodelingdrivesidentificationofnovelhistamineh3receptorligands
AT holgerstark ligandguidedhomologymodelingdrivesidentificationofnovelhistamineh3receptorligands
AT gerhardwolber ligandguidedhomologymodelingdrivesidentificationofnovelhistamineh3receptorligands
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