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Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we performed comparative studies between deep neural networks (DNN) and other ligand-based virtual screening (LBVS) methods to demonstrate that DNN and random forest (RF) were superior in hit prediction efficiency. By using DNN, several triple-negative breast cancer (TNBC) inhibitors were identified as potent hits from a screening of an in-house database of 165,000 compounds. In broadening the application of this method, we harnessed the predictive properties of trained model in the discovery of G protein-coupled receptor (GPCR) agonist, by which computational structure-based design of molecules could be greatly hindered by lack of structural information. Notably, a potent (~ 500 nM) mu-opioid receptor (MOR) agonist was identified as a hit from a small-size training set of 63 compounds. Our results show that DNN could be an efficient module in hit prediction and provide experimental evidence that machine learning could identify potent hits in silico from a limited training set. [ABSTRACT FROM AUTHOR]

Morphine is a unique opioid analgesic that activates the mu-opioid receptor (MOR) without efficiently promoting its endocytosis that may underlie side effects. Our objective was to discover a novel enhancer of ligand-induced MOR endocytosis and determine its effects on analgesia, tolerance and dependence. We used high-throughput screening to identify convallatoxin as an enhancer of ligand-induced MOR endocytosis with high potency and efficacy. Treatment of cells with convallatoxin enhanced morphine-induced MOR endocytosis through an adaptor protein 2 (AP2)/clathrin-dependent mechanism, attenuated morphine-induced phosphorylation of MOR, and diminished desensitization of membrane hyperpolarization. Furthermore, co-treatment with chronic convallatoxin reduced morphine tolerance in animal models of acute thermal pain and chronic inflammatory pain. Acute convallatoxin administration reversed morphine tolerance and dependence in morphine-tolerant mice. These findings suggest convallatoxin are potentially therapeutic for morphine side effects and open a new avenue to study MOR trafficking. [ABSTRACT FROM AUTHOR]