Abstract:The metabotropic glutamate subtype 1 (mGluR1), a member of the metabotropic glutamate receptors, is a therapeutic target for neurological disorders. However, due to the lower subtype selectivity of mGluR1 orthosteric compounds, a new targeted strategy, known as allosteric modulators research, is needed for the treatment of mGluR1-related diseases. Recently, the structure of the seven-transmembrane domain (7TMD) of mGluR1 has been solved, which reveals the binding site of allosteric modulators and provides an opportunity for future subtype-selectivity drug design. In this study, a series of computer-aided drug design methods were utilized to discover potential mGluR1 negative allosteric modulators (NAMs). Pharmacophore models were constructed based on three different structure types of mGluR1 NAMs. After validation using the built-in parameters and test set, the optimal pharmacophore model of each structure type was selected and utilized as a query to screen the Traditional Chinese Medicine Database (TCMD). Then, three different hit lists of compounds were obtained. Molecular docking was used based on the latest crystal structure of mGluR1-7TMD to further filter these hits. As a compound with high QFIT and LibDock Score was preferred, a total of 30 compounds were retained. MD simulation was utilized to confirm the stability of potential compounds binding. From the computational results, OPEN ACCESSMolecules 2015, 20 12770 thesinine-4ʹ-O-β-D-glucoside, nigrolineaxanthone-P and nodakenin might exhibit negative allosteric moderating effects on mGluR1. This paper indicates the applicability of molecular simulation technologies for discovering potential natural mGluR1 NAMs from Chinese herbs.

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P2Y 12 , a member of the G-protein-coupled receptors, is associated with abnormal platelet aggregation, a condition that contributes to thrombus formation. As receptor antagonists are effective solutions for anti-thrombus, the P2Y 12 receptor is a popular drug target. After the recent resolution of the P2Y 12 receptor's crystal structure, pharmacophore modeling and docking were combined to discover potential natural antagonists. Various approaches were used for the validation of the pharmacophore models and the optimization of docking algorithms. Hypo18, which was generated by 24 known antagonists, was determined to be the best hypothesis and is comprised of one ring aromatic, one hydrogen bond acceptor, one exclude volume, and three hydrophobic features. Hypo18 was thus utilized to screen TCMD (version 2009) to identify any potential active compounds, which then resulted in a hit list of 121 compounds with drug-likeness analysis. In addition, docking was used to refine the pharmacophorebased screening results as a cross-linking method. Then, the top 20 compounds with high docking scores were reserved. This paper provides a reliable source for discovering natural P2Y 12 receptor antagonists from traditional Chinese herbs.Résumé : Le récepteur P2Y 12 , membre de la famille des récepteurs couplés aux protéines G, est associé à des anomalies de l'agrégation plaquettaire, un trouble qui contribue à la formation de thrombus. Comme les antagonistes du récepteur P2Y 12 représentent des solutions anti-thrombus efficaces, ce récepteur constitue une cible thérapeutique privilégiée. À la suite de la récente résolution de la structure cristalline du récepteur P2Y 12 , des études de modélisation et de simulation d'amarrage du pharmacophore ont été combinées en vue de découvrir d'éventuels antagonistes naturels. Diverses approches dont le but était de valider les modèles moléculaires du pharmacophore et d'optimiser les algorithmes d'amarrage ont été utilisées. Le modèle Hypo18, généré à partir de 24 antagonistes connus, a été retenu comme la meilleure hypothèse et comprend un noyau aromatique, un accepteur de liaison hydrogène, un volume exclu et trois surfaces hydrophobes. Nous avons donc utilisé le modèle Hypo18 aux fins du criblage de la base de données de la médecine traditionnelle chinoise, la TCMD (version 2009), dans le but de trouver d'éventuels composés actifs. Cette opération a permis de dresser une liste de 121 composés dont le profil présente une possible activité pharmacologique. Puis, les résultats de criblage du pharmacophore ont été raffinés au moyen de la simulation d'amarrage moléculaire utilisée comme méthode de réticulation. Par la suite, les 20 composés présentant les meilleurs résultats d'arrimage ont été retenus. Cet article constitue une source fiable dans le processus de recherche d'antagonistes naturels du récepteur P2Y 12 à partir de plantes médicinales chinoises. [Traduit par la Rédaction] Mots-clés : antagonistes du récepteur P2Y12, modélisation du pharmacophore, amarrage, criblage virtuel, médecin...

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The blood–brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB prior to their target site, so the prediction research on BBB permeability is a fundamental and significant research direction in neuropharmacology. In this study, we combed through the available data and then with the help of support vector machine (SVM), we established an experiment process for discovering potential CNS compounds and investigating the mechanisms of BBB permeability of them to advance the research in this field four types of prediction models, referring to CNS activity, BBB permeability, passive diffusion and efflux transport, were obtained in the experiment process. The first two models were used to discover compounds which may have CNS activity and also cross the BBB at the same time; the latter two were used to elucidate the mechanism of BBB permeability of those compounds. Three optimization parameter methods, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), were used to optimize the SVM models. Then, four optimal models were selected with excellent evaluation indexes (the accuracy, sensitivity and specificity of each model were all above 85%). Furthermore, discrimination models were utilized to study the BBB properties of the known CNS activity compounds in Chinese herbs and this may guide the CNS drug development. With the relatively systematic and quick approach, the application rationality of traditional Chinese medicines for treating nervous system disease in the clinical practice will be improved.