Toward activated homology models of the human M1 muscarinic acetylcholine receptor

Comprehensive review on the interaction between natural compounds and brain receptors: Benefits and toxicity

Given their therapeutic activity, natural products have been used in traditional medicines throughout the centuries. The growing interest of the scientific community in phytopharmaceuticals, and more recently in marine products, has resulted in a significant number of research efforts towards understanding their effect in the treatment of neurodegenerative diseases, such as Alzheimer's (AD), Parkinson (PD) and Huntington (HD). Several studies have shown that many of the primary and secondary metabolites of plants, marine organisms and others, have high affinities for various brain receptors and may play a crucial role in the treatment of diseases affecting the central nervous system (CNS) in mammalians. Actually, such compounds may act on the brain receptors either by agonism, antagonism, allosteric modulation or other type of activity aimed at enhancing a certain effect. The current manuscript comprehensively reviews the state of the art on the interactions between natural compounds and brain receptors. This information is of foremost importance when it is intended to investigate and develop cutting-edge drugs, more effective and with alternative mechanisms of action to the conventional drugs presently used for the treatment of neurodegenerative diseases. Thus, we reviewed the effect of 173 natural products on neurotransmitter receptors, diabetes related receptors, neurotrophic factor related receptors, immune system related receptors, oxidative stress related receptors, transcription factors regulating gene expression related receptors and blood-brain barrier receptors.

Ligand Binding Pathways of Clozapine and Haloperidol in the Dopamine D2 and D3 Receptors

The binding of a small molecule ligand to its protein target is most often characterized by binding affinity and is typically viewed as an on/off switch. The more complex reality is that binding involves the ligand passing through a series of intermediate states between the solution phase and the fully bound pose. We have performed a set of 29 unbiased molecular dynamics simulations to model the binding pathways of the dopamine receptor antagonists clozapine and haloperidol binding to the D2 and D3 dopamine receptors. Through these simulations we have captured the binding pathways of clozapine and haloperidol from the extracellular vestibule to the orthosteric binding site and thereby, we also predict the bound pose of each ligand. These are the first long time scale simulations of haloperidol or clozapine binding to dopamine receptors. From these simulations, we have identified several important stages in the binding pathway, including the involvement of Tyr7.35 in a "handover" mechanism that transfers the ligand between the extracellular vestibule and Asp3.32. We have also performed interaction and cluster analyses to determine differences in binding pathways between the D2 and D3 receptors and identified metastable states that may be of use in drug design.

In Silico and In Vitro Analysis of Bacoside A Aglycones and Its Derivatives as the Constituents Responsible for the Cognitive Effects of Bacopa monnieri

Bacopa monnieri has been used in Ayurvedic medicine to improve memory and cognition. The active constituent responsible for its pharmacological effects is bacoside A, a mixture of dammarane-type triterpenoid saponins containing sugar chains linked to a steroid aglycone skeleton. Triterpenoid saponins have been reported to be transformed in vivo to metabolites that give better biological activity and pharmacokinetic characteristics. Thus, the activities of the parent compounds (bacosides), aglycones (jujubogenin and pseudojujubogenin) and their derivatives (ebelin lactone and bacogenin A1) were compared using a combination of in silico and in vitro screening methods. The compounds were docked into 5-HT1A, 5-HT2A, D1, D2, M1 receptors and acetylcholinesterase (AChE) using AutoDock and their central nervous system (CNS) drug-like properties were determined using Discovery Studio molecular properties and ADMET descriptors. The compounds were screened in vitro using radioligand receptor binding and AChE inhibition assays. In silico studies showed that the parent bacosides were not able to dock into the chosen CNS targets and had poor molecular properties as a CNS drug. In contrast, the aglycones and their derivatives showed better binding affinity and good CNS drug-like properties, were well absorbed through the intestines and had good blood brain barrier (BBB) penetration. Among the compounds tested in vitro, ebelin lactone showed binding affinity towards M1 (Ki = 0.45 μM) and 5-HT2A (4.21 μM) receptors. Bacoside A and bacopaside X (9.06 μM) showed binding affinity towards the D1 receptor. None of the compounds showed any inhibitory activity against AChE. Since the stimulation of M1 and 5-HT2A receptors has been implicated in memory and cognition and ebelin lactone was shown to have the strongest binding energy, highest BBB penetration and binding affinity towards M1 and 5-HT2A receptors, we suggest that B. monnieri constituents may be transformed in vivo to the active form before exerting their pharmacological activity.

Docking and Virtual Screening Strategies for GPCR Drug Discovery

Progress in structure determination of G protein-coupled receptors (GPCRs) has made it possible to apply structure-based drug design (SBDD) methods to this pharmaceutically important target class. The quality of GPCR structures available for SBDD projects fall on a spectrum ranging from high resolution crystal structures (<2 Å), where all water molecules in the binding pocket are resolved, to lower resolution (>3 Å) where some protein residues are not resolved, and finally to homology models that are built using distantly related templates. Each GPCR project involves a distinct set of opportunities and challenges, and requires different approaches to model the interaction between the receptor and the ligands. In this review we will discuss docking and virtual screening to GPCRs, and highlight several refinement and post-processing steps that can be used to improve the accuracy of these calculations. Several examples are discussed that illustrate specific steps that can be taken to improve upon the docking and virtual screening accuracy. While GPCRs are a unique target class, many of the methods and strategies outlined in this review are general and therefore applicable to other protein families.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

Flavonoids with M1 muscarinic acetylcholine receptor binding activity

Muscarinic acetylcholine receptor-active compounds have potential for the treatment of Alzheimer’s disease. In this study, a series of natural and synthetic flavones and flavonols was assayed in vitro for their ability to inhibit radioligand binding at human cloned M₁ muscarinic receptors. Several compounds were found to possess competitive binding affinity (K_i = 40–110 µM), comparable to that of acetylcholine (K_i = 59 µM). Despite the fact that these compounds lack a positively-charged ammonium group under physiological conditions, molecular modelling studies suggested that they bind to the orthosteric site of the receptor, mainly through non-polar interactions.

Homology modeling of human muscarinic acetylcholine receptors

We have developed homology models of the acetylcholine muscarinic receptors M₁R-M₅R, based on the β₂-adrenergic receptor crystal as the template. This is the first report of homology modeling of all five subtypes of acetylcholine muscarinic receptors with binding sites optimized for ligand binding. The models were evaluated for their ability to discriminate between muscarinic antagonists and decoy compounds using virtual screening using enrichment factors, area under the ROC curve (AUC), and an early enrichment measure, LogAUC. The models produce rational binding modes of docked ligands as well as good enrichment capacity when tested against property-matched decoy libraries, which demonstrates their unbiased predictive ability. To test the relative effects of homology model template selection and the binding site optimization procedure, we generated and evaluated a naïve M₂R model, using the M₃R crystal structure as a template. Our results confirm previous findings that binding site optimization using ligand(s) active at a particular receptor, i.e. including functional knowledge into the model building process, has a more pronounced effect on model quality than target-template sequence similarity. The optimized M₁R-M₅R homology models are made available as part of the Supporting Information to allow researchers to use these structures, compare them to their own results, and thus advance the development of better modeling approaches.