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

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 (EC50 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 EC50, 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.

Computational Methods in Drug Discovery

“…In a separate study, Mueller et al (2010) used a similar approach to identify negative allosteric modulators for mGlu5. Rodriguez et al (2010) previously performed a traditional HTS screen of 160,000 compounds for allosteric modulators of mGlu5 and found 624 antagonists.…”

“…Thus, the ratio of data points versus degrees of freedom increases, leading to models of increased predictive power. Techniques that have proven successful in QSAR modeling include selecting features by measures such as information gain (Kent, 1983) and F-score , sequential feature forward selection or feature backward elimination (Mao, 2004), genetic algorithm (Davis, 1991;Goodarzi et al, 2009), swarm optimization (Goodarzi et al, 2009), and input sensitivity analysis (Mueller et al, 2010).…”

“…Next, the influence of each feature on the model output is determined: Each feature x i is perturbed, and the change in output y is computed. This procedure numerically estimates the partial derivative of the output with respect to each input, a measure that is effective in selecting optimal descriptor sets (Mueller et al, 2010).…”

Model for High-Throughput Screening of Multitarget Drugs in Chemical Neurosciences: Synthesis, Assay, and Theoretic Study of Rasagiline Carbamates

“…11 Unfortunately, most current QSAR techniques can predict the probable result of one drug in one specific assay. Nevertheless, recently developed multitarget/multiplexing QSAR models (mt-QSAR/ mx-QSAR) may become a useful tool in this regard.…”

Special Issue on the Pharmacology and Medicinal Chemistry of Allosteric Modulators of Metabotropic Glutamate Receptors (mGluRs)

“…Since the discovery and cloning in the late 1980s, eight mGlu receptor subtypes have been identified and divided into three groups: group I includes mGlu 1 and mGlu 5 , group II includes mGlu 2 and mGlu 3 , and group III consists of mGlu 4 , mGlu 6 , mGlu 7 , and mGlu 8 . 1 Targeting the orthosteric (glutamate binding site) has proven challenging to impossible for most mGluR subtypes, as ligands lack subtype selectivity and possess unfavorable physiochemical and DMPK properties.…”