ArticleACS chemical neuroscience2010
Identification of Metabotropic Glutamate Receptor Subtype 5 Potentiators Using Virtual High-Throughput Screening.
Article in ACS chemical neuroscience, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
20 citing papers in PubMed, 48 citations in OpenAlex.
- A Comparison between Enrichment Optimization Algorithm (EOA)-Based and Docking-Based Virtual Screening.International journal of molecular sciences · 2021Article
- General Purpose Structure-Based Drug Discovery Neural Network Score Functions with Human-Interpretable Pharmacophore Maps.Journal of chemical information and modeling · 2021Article
- Evaluation of QSAR Equations for Virtual Screening.International journal of molecular sciences · 2020Article
- Identification of Novel Allosteric Modulators of Metabotropic Glutamate Receptor Subtype 5 Acting at Site Distinct from 2-Methyl-6-(phenylethynyl)-pyridine Binding.ACS chemical neuroscience · 2019Article
- QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery.Frontiers in pharmacology · 2018Article
- 3D-QSAR modelling dataset of bioflavonoids for predicting the potential modulatory effect on P-glycoprotein activity.Data in brief · 2016Article
- Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout.Journal of computer-aided molecular design · 2016Article
- Computational methods in drug discovery.Beilstein journal of organic chemistry · 2016Review
- Computational approaches in target identification and drug discovery.Computational and structural biotechnology journal · 2016Review
- Prediction of multi-target networks of neuroprotective compounds with entropy indices and synthesis, assay, and theoretical study of new asymmetric 1,2-rasagiline carbamates.International journal of molecular sciences · 2014Article
- Computational methods in drug discovery.Pharmacological reviews · 2014Review
- Model for high-throughput screening of multitarget drugs in chemical neurosciences: synthesis, assay, and theoretic study of rasagiline carbamates.ACS chemical neuroscience · 2013Article
- Modulation of pyramidal cell output in the medial prefrontal cortex by mGluR5 interacting with CB1.Neuropharmacology · 2013Article
- Benchmarking ligand-based virtual High-Throughput Screening with the PubChem database.Molecules (Basel, Switzerland) · 2013Article
- Iterative experimental and virtual high-throughput screening identifies metabotropic glutamate receptor subtype 4 positive allosteric modulators.Journal of molecular modeling · 2012Article
- BCL::EMAS--enantioselective molecular asymmetry descriptor for 3D-QSAR.Molecules (Basel, Switzerland) · 2012Article
- Article
- Special issue on the pharmacology and medicinal chemistry of allosteric modulators of metabotropic glutamate receptors (mGluRs).ACS chemical neuroscience · 2011Article
- bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.IEEE ... International Conference on Computational Advances in Bio and Medical Sciences : [proceedings]. IEEE International Conference on Computational Advances in Bio and Medical Sciences · 2011Article
- 3D-QSAR CoMFA study of benzoxazepine derivatives as mGluR5 positive allosteric modulators.Bioorganic & medicinal chemistry letters · 2010Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
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 approximately 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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.