Cargando…

Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening

[Image: see text] Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutama...

Descripción completa

Detalles Bibliográficos
Autores principales: Mueller, Ralf, Rodriguez, Alice L., Dawson, Eric S., Butkiewicz, Mariusz, Nguyen, Thuy T., Oleszkiewicz, Stephen, Bleckmann, Annalen, Weaver, C. David, Lindsley, Craig W., Conn, P. Jeffrey, Meiler, Jens
Formato: Texto
Lenguaje:English
Publicado: American Chemical Society 2010
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2857954/
https://www.ncbi.nlm.nih.gov/pubmed/20414370
http://dx.doi.org/10.1021/cn9000389
_version_ 1782180368343891968
author Mueller, Ralf
Rodriguez, Alice L.
Dawson, Eric S.
Butkiewicz, Mariusz
Nguyen, Thuy T.
Oleszkiewicz, Stephen
Bleckmann, Annalen
Weaver, C. David
Lindsley, Craig W.
Conn, P. Jeffrey
Meiler, Jens
author_facet Mueller, Ralf
Rodriguez, Alice L.
Dawson, Eric S.
Butkiewicz, Mariusz
Nguyen, Thuy T.
Oleszkiewicz, Stephen
Bleckmann, Annalen
Weaver, C. David
Lindsley, Craig W.
Conn, P. Jeffrey
Meiler, Jens
author_sort Mueller, Ralf
collection PubMed
description [Image: see text] Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutamate response were identified through high-throughput screening (HTS) of a diverse library of 144,475 substances utilizing a functional assay measuring receptor-induced intracellular release of calcium. Primary hits were tested for concentration-dependent activity, and potency data (EC(50) values) were used for training artificial neural network (ANN) quantitative structure−activity relationship (QSAR) models that predict biological potency from the chemical structure. While all models were trained to predict EC(50), the quality of the models was assessed by using both continuous measures and binary classification. Numerical descriptors of chemical structure were used as input for the machine learning procedure and optimized in an iterative protocol. The ANN models achieved theoretical enrichment ratios of up to 38 for an independent data set not used in training the model. A database of ∼450,000 commercially available drug-like compounds was targeted in a virtual screen. A set of 824 compounds was obtained for testing based on the highest predicted potency values. Biological testing found 28.2% (232/824) of these compounds with various activities at mGluR5 including 177 pure potentiators and 55 partial agonists. These results represent an enrichment factor of 23 for pure potentiation of the mGluR5 glutamate response and 30 for overall mGluR5 modulation activity when compared with those of the original mGluR5 experimental screening data (0.94% hit rate). The active compounds identified contained 72% close derivatives of previously identified PAMs as well as 28% nontrivial derivatives of known active compounds.
format Text
id pubmed-2857954
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher American Chemical Society
record_format MEDLINE/PubMed
spelling pubmed-28579542010-04-21 Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening Mueller, Ralf Rodriguez, Alice L. Dawson, Eric S. Butkiewicz, Mariusz Nguyen, Thuy T. Oleszkiewicz, Stephen Bleckmann, Annalen Weaver, C. David Lindsley, Craig W. Conn, P. Jeffrey Meiler, Jens ACS Chem Neurosci [Image: see text] Selective potentiators of glutamate response at metabotropic glutamate receptor subtype 5 (mGluR5) have exciting potential for the development of novel treatment strategies for schizophrenia. A total of 1,382 compounds with positive allosteric modulation (PAM) of the mGluR5 glutamate response were identified through high-throughput screening (HTS) of a diverse library of 144,475 substances utilizing a functional assay measuring receptor-induced intracellular release of calcium. Primary hits were tested for concentration-dependent activity, and potency data (EC(50) values) were used for training artificial neural network (ANN) quantitative structure−activity relationship (QSAR) models that predict biological potency from the chemical structure. While all models were trained to predict EC(50), the quality of the models was assessed by using both continuous measures and binary classification. Numerical descriptors of chemical structure were used as input for the machine learning procedure and optimized in an iterative protocol. The ANN models achieved theoretical enrichment ratios of up to 38 for an independent data set not used in training the model. A database of ∼450,000 commercially available drug-like compounds was targeted in a virtual screen. A set of 824 compounds was obtained for testing based on the highest predicted potency values. Biological testing found 28.2% (232/824) of these compounds with various activities at mGluR5 including 177 pure potentiators and 55 partial agonists. These results represent an enrichment factor of 23 for pure potentiation of the mGluR5 glutamate response and 30 for overall mGluR5 modulation activity when compared with those of the original mGluR5 experimental screening data (0.94% hit rate). The active compounds identified contained 72% close derivatives of previously identified PAMs as well as 28% nontrivial derivatives of known active compounds. American Chemical Society 2010-01-28 2010-04-21 /pmc/articles/PMC2857954/ /pubmed/20414370 http://dx.doi.org/10.1021/cn9000389 Text en Copyright © 2010 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org.
spellingShingle Mueller, Ralf
Rodriguez, Alice L.
Dawson, Eric S.
Butkiewicz, Mariusz
Nguyen, Thuy T.
Oleszkiewicz, Stephen
Bleckmann, Annalen
Weaver, C. David
Lindsley, Craig W.
Conn, P. Jeffrey
Meiler, Jens
Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title_full Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title_fullStr Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title_full_unstemmed Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title_short Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening
title_sort identification of metabotropic glutamate receptor subtype 5 potentiators using virtual high-throughput screening
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2857954/
https://www.ncbi.nlm.nih.gov/pubmed/20414370
http://dx.doi.org/10.1021/cn9000389
work_keys_str_mv AT muellerralf identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT rodriguezalicel identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT dawsonerics identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT butkiewiczmariusz identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT nguyenthuyt identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT oleszkiewiczstephen identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT bleckmannannalen identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT weavercdavid identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT lindsleycraigw identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT connpjeffrey identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening
AT meilerjens identificationofmetabotropicglutamatereceptorsubtype5potentiatorsusingvirtualhighthroughputscreening