From structure to clinic: Design of a muscarinic M1 receptor agonist with potential to treatment of Alzheimer's disease.

Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic.

Differential GLP-1R Binding and Activation by Peptide and Non-peptide Agonists.

Peptide drugs targeting class B1 G-protein-coupled receptors (GPCRs) can treat multiple diseases; however, there remains substantial interest in the development of orally delivered non-peptide drugs. Here, we reveal unexpected overlap between signaling and regulation of the glucagon-like peptide-1 (GLP-1) receptor by the non-peptide agonist PF 06882961 and GLP-1 that was not observed for another compound, CHU-128. Compounds from these patent series, including PF 06882961, are currently in clinical trials for treatment of type 2 diabetes. High-resolution cryoelectron microscopy (cryo-EM) structures reveal that the binding sites for PF 06882961 and GLP-1 substantially overlap, whereas CHU-128 adopts a unique binding mode with a more open receptor conformation at the extracellular face. Structural differences involving extensive water-mediated hydrogen bond networks could be correlated to functional data to understand how PF 06882961, but not CHU-128, can closely mimic the pharmacological properties of GLP-1. These findings will facilitate rational structure-based discovery of non-peptide agonists targeting class B GPCRs.

Binding of SEP-363856 within TAAR1 and the 5HT1A receptor: implications for the design of novel antipsychotic drugs.

Current medications for schizophrenia typically modulate dopaminergic neurotransmission. While affecting positive symptoms, antipsychotic drugs have little clinical effect on negative symptoms and cognitive impairment. Moreover, newer 'atypical' antipsychotic drugs also have significant metabolic adverse-effects. The recent positive clinical trial of the novel drug candidate SEP-363856, which targets non-dopamine receptors (trace amine-associated receptor and the 5HT1A receptor), is a potentially promising development for the management of schizophrenia. In this perspective, we briefly overview the role of TAAR1 and the 5HT1A receptor in schizophrenia and explore the specific binding characteristics of SEP-363856 at these receptors. Molecular dynamics simulations (MDS) indicate that SEP-363856 interacts with a small, common set of conserved residues within the TAAR1 and 5HT1A ligand-binding domain. The primary interaction of SEP-363856 involves binding to the negatively charged aspartate residue (Asp1033.32, TAAR1; Asp1163.32, 5HT1A). In general, the binding of SEP-363856 within TAAR1 involves a greater number of aromatic contacts compared to 5HT1A. MDS provides important insights into the molecular basis of binding site interactions of SEP-363856 with TAAR1 and the 5HT1A receptor, which will be beneficial for understanding the pharmacological uniqueness of SEP-363856 and for the design of novel drug candidates for these newly targeted receptors in the treatment of schizophrenia and related disorders.

Structure-based development of a subtype-selective orexin 1 receptor antagonist.

Orexins are neuropeptides that activate the rhodopsin-like G protein-coupled receptors OX1R and OX2R. The orexin system plays an important role in the regulation of the sleep-wake cycle and the regulation of feeding and emotions. The nonselective orexin receptor antagonist suvorexant has been the first drug on the market targeting the orexin system and is prescribed for the treatment of insomnia. Subtype-selective OX1R antagonists are valuable tools to further investigate the functions and physiological role of the OX1R in vivo and promising lead compounds for the treatment of drug addiction, anxiety, pain or obesity. Starting from the OX1R and OX2R crystal structures bound to suvorexant, we exploited a single amino acid difference in the orthosteric binding site by using molecular docking and structure-based drug design to optimize ligand interactions with the OX1R while introducing repulsive interactions with the OX2R. A newly established enantiospecific synthesis provided ligands showing up to 75-fold selectivity for the OX1R over the OX2R subtype. The structure of a new OX1R antagonist with subnanomolar affinity (JH112) was determined by crystallography in complex with the OX1R and corresponded closely to the docking-predicted geometry. JH112 exhibits high selectivity over a panel of different GPCRs, is able to cross the blood-brain barrier and acts as slowly diffusing and insurmountable antagonist for Gq protein activation and in particular ß-arrestin-2 recruitment at OX1R. This study demonstrates the potential of structure-based drug design to develop more subtype-selective GPCR ligands with potentially reduced side effects and provides an attractive probe molecule and lead compound.

Multipathway In Vitro Pharmacological Characterization of Specialized Proresolving G Protein-Coupled Receptors.

Specialized proresolving mediators (SPMs) and their cognate G protein-coupled receptors are implicated in autoimmune disorders, including chronic inflammation, rheumatoid arthritis, systemic scleroderma, and lupus erythematosus. To date, six G protein-coupled receptors (GPCRs) have been paired with numerous endogenous and synthetic ligands. However, the function and downstream signaling of these receptors remains unclear. To address this knowledge gap, we systematically expressed each receptor in a human embryonic kindney 293 (HEK293)-Flp-In-CD8a-FLAG cell system. Each receptor was pharmacologically characterized with both synthetic and putative endogenous ligands across different signaling assays, covering both G protein-dependent (Gs, Gi, and Gq) and independent mechanisms (ß-arrestin2 recruitment). Three orphan GPCRs previously identified as SPM receptors (GPR 18, GPR32 and GPR37) failed to express in HEK 293 cells. Although we were unsuccessful in identifying an endogenous ligand for formyl peptide receptor 2 (FPR2)/lipoxin A4 receptor (ALX), with only a modest response to N-formylmethionine-leucyl-phenylalanine (fMLP), we did reveal clear signaling bias away from extracelluar signal-related kinase (ERK) 1/2 phosphorylation for the clinically tested agonist N-(2-{[4-(1,1-difluoroethyl)-1,3-oxazol-2-yl]methyl}-2H-1,2,3-triazol-4-yl)-2-methyl-5-(3-methylphenyl)-1,3-oxazole-4-carboxamide (ACT-389949), adding further evidence for its poor efficacy in two phase I studies. We also identified neuroprotectin D1 as a new leukotriene B4 receptor 1 (BLT1) agonist, implying an alternative target for the neuroprotective effects of the ligand. We confirmed activity for resolvin E1 (RvE1) at BLT1 but failed to observe any response at the chemerin1 receptor. This study provides some much-needed clarity around published receptor-ligand pairings but indicates that the expression and function of these SPM GPCRs remains very much context-dependent. In addition, the identification of signaling bias at FPR2/ALX may assist in guiding design of new FPR2/ALX agonists for the treatment of autoimmune disorders. SIGNIFICANCE STATEMENT: To our knowledge, this is the first study to comprehensibly show how several natural mediators and synthetic ligands signal through three specialized proresolving mediator GPCRs using multiple ligands from different classes across four-six endpoint signaling assays. This study discovers new ligand pairings, refutes others, reveals poly-pharmacology, and identifies biased agonism in formyl peptide receptor 2/lipoxin A4 receptor pharmacology. This study highlights the potential of these receptors in treating specific autoimmune diseases, including rheumatoid arthritis, systemic scleroderma, and systemic lupus erythematosus.

Crystal structure of the M5 muscarinic acetylcholine receptor.

The human M5 muscarinic acetylcholine receptor (mAChR) has recently emerged as an exciting therapeutic target for treating a range of disorders, including drug addiction. However, a lack of structural information for this receptor subtype has limited further drug development and validation. Here we report a high-resolution crystal structure of the human M5 mAChR bound to the clinically used inverse agonist, tiotropium. This structure allowed for a comparison across all 5 mAChR family members that revealed important differences in both orthosteric and allosteric sites that could inform the rational design of selective ligands. These structural studies, together with chimeric swaps between the extracellular regions of the M2 and M5 mAChRs, provided structural insight into kinetic selectivity, where ligands show differential residency times between related family members. Collectively, our study provides important insights into the nature of orthosteric and allosteric ligand interaction across the mAChR family that could be exploited for the design of selective drugs.

HARVESTMAN: a framework for hierarchical feature learning and selection from whole genome sequencing data.

BACKGROUND: Supervised learning from high-throughput sequencing data presents many challenges. For one, the curse of dimensionality often leads to overfitting as well as issues with scalability. This can bring about inaccurate models or those that require extensive compute time and resources. Additionally, variant calls may not be the optimal encoding for a given learning task, which also contributes to poor predictive capabilities. To address these issues, we present HARVESTMAN, a method that takes advantage of hierarchical relationships among the possible biological interpretations and representations of genomic variants to perform automatic feature learning, feature selection, and model building. RESULTS: We demonstrate that HARVESTMAN scales to thousands of genomes comprising more than 84 million variants by processing phase 3 data from the 1000 Genomes Project, one of the largest publicly available collection of whole genome sequences. Using breast cancer data from The Cancer Genome Atlas, we show that HARVESTMAN selects a rich combination of representations that are adapted to the learning task, and performs better than a binary representation of SNPs alone. We compare HARVESTMAN to existing feature selection methods and demonstrate that our method is more parsimonious-it selects smaller and less redundant feature subsets while maintaining accuracy of the resulting classifier. CONCLUSION: HARVESTMAN is a hierarchical feature selection approach for supervised model building from variant call data. By building a knowledge graph over genomic variants and solving an integer linear program , HARVESTMAN automatically and optimally finds the right encoding for genomic variants. Compared to other hierarchical feature selection methods, HARVESTMAN is faster and selects features more parsimoniously.

Cryo-EM structure of the dual incretin receptor agonist, peptide-19, in complex with the glucagon-like peptide-1 receptor.

Dual agonists that can activate both the glucagon-like peptide-1 receptor (GLP-1R) and the gastric inhibitory polypeptide receptor (GIPR) have demonstrated high efficacy for the treatment of metabolic disease. Peptide-19 is a prototypical dual agonist that has high potency at both GLP-1R and GIPR but has a distinct signalling profile relative to the native peptides at the cognate receptors. In this study, we solved the structure of peptide-19 bound to the GLP-1R in complex with Gs protein, and compared the structure and dynamics of this complex to that of published structures of GLP-1R:Gs in complex with other receptor agonists. Unlike other peptide-bound receptor complexes, peptide-19:GLP-1R:Gs demonstrated a more open binding pocket where transmembrane domain (TM) 6, TM7 and the interconnecting extracellular loop 3 (ECL3) were located away from the peptide, with no interactions between peptide-19 and TM6/ECL3. Analysis of conformational variance of the complex revealed that peptide-19 was highly dynamic and underwent binding and unbinding motions facilitated by the more open TM binding pocket. Both the consensus structure of the GLP-1R complex with peptide-19 and the dynamics of this complex were distinct from previously described GLP-1R structures providing unique insights into the mode of GLP-1R activation by this dual agonist.

G Protein-Coupled Receptors Targeting Insulin Resistance, Obesity, and Type 2 Diabetes Mellitus.

G protein-coupled receptors (GPCRs) continue to be important discovery targets for the treatment of type 2 diabetes mellitus (T2DM). Many GPCRs are directly involved in the development of insulin resistance and ß-cell dysfunction, and in the etiology of inflammation that can lead to obesity-induced T2DM. This review summarizes the current literature describing a number of well-validated GPCR targets, but also outlines several new and promising targets for drug discovery. We highlight the importance of understanding the role of these receptors in the disease pathology, and their basic pharmacology, which will pave the way to the development of novel pharmacological probes that will enable these targets to fulfill their promise for the treatment of these metabolic disorders.

Bitopic Binding Mode of an M1 Muscarinic Acetylcholine Receptor Agonist Associated with Adverse Clinical Trial Outcomes.

The realization of the therapeutic potential of targeting the M1 muscarinic acetylcholine receptor (mAChR) for the treatment of cognitive decline in Alzheimer's disease has prompted the discovery of M1 mAChR ligands showing efficacy in alleviating cognitive dysfunction in both rodents and humans. Among these is GSK1034702 (7-fluoro-5-methyl-3-[1-(oxan-4-yl)piperidin-4-yl]-1H-benzimidazol-2-one), described previously as a potent M1 receptor allosteric agonist, which showed procognitive effects in rodents and improved immediate memory in a clinical nicotine withdrawal test but induced significant side effects. Here we provide evidence using ligand binding, chemical biology and functional assays to establish that rather than the allosteric mechanism claimed, GSK1034702 interacts in a bitopic manner at the M1 mAChR such that it can concomitantly span both the orthosteric and an allosteric binding site. The bitopic nature of GSK1034702, together with the intrinsic agonist activity and a lack of muscarinic receptor subtype selectivity reported here, all likely contribute to the adverse effects of this molecule in clinical trials. Although they impart beneficial effects on learning and memory, we conclude that these properties are undesirable in a clinical candidate due to the likelihood of adverse side effects. Rather, our data support the notion that "pure" positive allosteric modulators showing selectivity for the M1 mAChR with low levels of intrinsic activity would be preferable to provide clinical efficacy with low adverse responses.

Dynamic allostery governs cyclophilin A-HIV capsid interplay.

Host factor protein Cyclophilin A (CypA) regulates HIV-1 viral infectivity through direct interactions with the viral capsid, by an unknown mechanism. CypA can either promote or inhibit viral infection, depending on host cell type and HIV-1 capsid (CA) protein sequence. We have examined the role of conformational dynamics on the nanosecond to millisecond timescale in HIV-1 CA assemblies in the escape from CypA dependence, by magic-angle spinning (MAS) NMR and molecular dynamics (MD). Through the analysis of backbone (1)H-(15)N and (1)H-(13)C dipolar tensors and peak intensities from 3D MAS NMR spectra of wild-type and the A92E and G94D CypA escape mutants, we demonstrate that assembled CA is dynamic, particularly in loop regions. The CypA loop in assembled wild-type CA from two strains exhibits unprecedented mobility on the nanosecond to microsecond timescales, and the experimental NMR dipolar order parameters are in quantitative agreement with those calculated from MD trajectories. Remarkably, the CypA loop dynamics of wild-type CA HXB2 assembly is significantly attenuated upon CypA binding, and the dynamics profiles of the A92E and G94D CypA escape mutants closely resemble that of wild-type CA assembly in complex with CypA. These results suggest that CypA loop dynamics is a determining factor in HIV-1's escape from CypA dependence.

Isoform-Specific Biased Agonism of Histamine H3 Receptor Agonists.

The human histamine H3 receptor (hH3R) is subject to extensive gene splicing that gives rise to a large number of functional and nonfunctional isoforms. Despite the general acceptance that G protein-coupled receptors can adopt different ligand-induced conformations that give rise to biased signaling, this has not been studied for the H3R; further, it is unknown whether splice variants of the same receptor engender the same or differential biased signaling. Herein, we profiled the pharmacology of histamine receptor agonists at the two most abundant hH3R splice variants (hH3R445 and hH3R365) across seven signaling endpoints. Both isoforms engender biased signaling, notably for 4-[3-(benzyloxy)propyl]-1H-imidazole (proxyfan) [e.g., strong bias toward phosphorylation of glycogen synthase kinase 3ß (GSK3ß) via the full-length receptor] and its congener 3-(1H-imidazol-4-yl)propyl-(4-iodophenyl)-methyl ether (iodoproxyfan), which are strongly consistent with the former's designation as a "protean" agonist. The 80 amino acid IL3 deleted isoform hH3R365 is more permissive in its signaling than hH3R445: 2-(1H-imidazol-5-yl)ethyl imidothiocarbamate (imetit), proxyfan, and iodoproxyfan were all markedly biased away from calcium signaling, and principal component analysis of the full data set revealed divergent profiles for all five agonists. However, most interesting was the identification of differential biased signaling between the two isoforms. Strikingly, hH3R365 was completely unable to stimulate GSK3ß phosphorylation, an endpoint robustly activated by the full-length receptor. To the best of our knowledge, this is the first quantitative example of differential biased signaling via isoforms of the same G protein-coupled receptor that are simultaneously expressed in vivo and gives rise to the possibility of selective pharmacological targeting of individual receptor splice variants.

High throughput, quantitative analysis of human osteoclast differentiation and activity.

Osteoclasts are multinuclear cells that degrade bone under both physiological and pathophysiological conditions. Osteoclasts are therefore a major target of osteoporosis therapeutics aimed at preserving bone. Consequently, analytical methods for osteoclast activity are useful for the development of novel biomarkers and/or pharmacological agents for the treatment of osteoporosis. The nucleation state of an osteoclast is indicative of its maturation and activity. To date, activity is routinely measured at the population level with only approximate consideration of the nucleation state (an 'osteoclast population' is typically defined as cells with ≥3 nuclei). Using a fluorescent substrate for tartrate-resistant acid phosphatase (TRAP), a routinely used marker of osteoclast activity, we developed a multi-labelled imaging method for quantitative measurement of osteoclast TRAP activity at the single cell level. Automated image analysis enables interrogation of large osteoclast populations in a high throughput manner using open source software. Using this methodology, we investigated the effects of receptor activator of nuclear factor kappa-B ligand (RANK-L) on osteoclast maturation and activity and demonstrated that TRAP activity directly correlates with osteoclast maturity (i.e. nuclei number). This method can be applied to high throughput screening of osteoclast-targeting compounds to determine changes in maturation and activity.

Agonist-bound adenosine A2A receptor structures reveal common features of GPCR activation.

Adenosine receptors and ß-adrenoceptors are G-protein-coupled receptors (GPCRs) that activate intracellular G proteins on binding the agonists adenosine or noradrenaline, respectively. GPCRs have similar structures consisting of seven transmembrane helices that contain well-conserved sequence motifs, indicating that they are probably activated by a common mechanism. Recent structures of ß-adrenoceptors highlight residues in transmembrane region 5 that initially bind specifically to agonists rather than to antagonists, indicating that these residues have an important role in agonist-induced activation of receptors. Here we present two crystal structures of the thermostabilized human adenosine A(2A) receptor (A(2A)R-GL31) bound to its endogenous agonist adenosine and the synthetic agonist NECA. The structures represent an intermediate conformation between the inactive and active states, because they share all the features of GPCRs that are thought to be in a fully activated state, except that the cytoplasmic end of transmembrane helix 6 partially occludes the G-protein-binding site. The adenine substituent of the agonists binds in a similar fashion to the chemically related region of the inverse agonist ZM241385 (ref. 8). Both agonists contain a ribose group, not found in ZM241385, which extends deep into the ligand-binding pocket where it makes polar interactions with conserved residues in H7 (Ser 277(7.42) and His 278(7.43); superscripts refer to Ballesteros-Weinstein numbering) and non-polar interactions with residues in H3. In contrast, the inverse agonist ZM241385 does not interact with any of these residues and comparison with the agonist-bound structures indicates that ZM241385 sterically prevents the conformational change in H5 and therefore it acts as an inverse agonist. Comparison of the agonist-bound structures of A(2A)R with the agonist-bound structures of ß-adrenoceptors indicates that the contraction of the ligand-binding pocket caused by the inward motion of helices 3, 5 and 7 may be a common feature in the activation of all GPCRs.

International Union of Basic and Clinical Pharmacology. XC. multisite pharmacology: recommendations for the nomenclature of receptor allosterism and allosteric ligands.

Allosteric interactions play vital roles in metabolic processes and signal transduction and, more recently, have become the focus of numerous pharmacological studies because of the potential for discovering more target-selective chemical probes and therapeutic agents. In addition to classic early studies on enzymes, there are now examples of small molecule allosteric modulators for all superfamilies of receptors encoded by the genome, including ligand- and voltage-gated ion channels, G protein-coupled receptors, nuclear hormone receptors, and receptor tyrosine kinases. As a consequence, a vast array of pharmacologic behaviors has been ascribed to allosteric ligands that can vary in a target-, ligand-, and cell-/tissue-dependent manner. The current article presents an overview of allostery as applied to receptor families and approaches for detecting and validating allosteric interactions and gives recommendations for the nomenclature of allosteric ligands and their properties.

Molecular Mechanisms of Action of M5 Muscarinic Acetylcholine Receptor Allosteric Modulators.

Recently, the first subtype-selective allosteric modulators of the M5 muscarinic acetylcholine receptor (mAChR) have been described, but their molecular mechanisms of action remain unknown. Using radioligand-binding and functional assays of inositol phosphate (IP) accumulation and Ca(2+) mobilization in a recombinant cell line stably expressing the human M5 mAChR, we investigated the effects of the positive allosteric modulator (PAM), ML380, and negative allosteric modulator, ML375. In functional assays, ML380 caused robust enhancements in the potency of the full agonists, acetylcholine (ACh), carbachol, and oxotremorine-M, while significantly increasing the maximal response to the partial agonist, pilocarpine. ML380 also demonstrated direct allosteric agonist activity. In contrast, ML375 displayed negative cooperativity with each of the agonists in a manner that varied with the pathway investigated and progressively reduced the maximal pilocarpine response. Radioligand-binding affinity cooperativity estimates were consistent with values derived from functional assays in some instances but not others, suggesting additional allosteric effects on orthosteric ligand efficacy. For ML375 this was confirmed in IP assays performed after reduction of receptor reserve by the alkylating agent, phenoxybenzamine, as it reduced the maximal ACh response. In contrast, ML380 enhanced only ACh potency after receptor alkylation, with no effect on maximal response, consistent with studies of the M1 mAChR with the prototypical PAM, BQZ12. Interaction studies between ML380 and ML375 also indicated that they most likely used an overlapping allosteric site. Our findings indicate that novel small-molecule modulators of the M5 mAChR display mixed mechanisms of action compared with previously characterized modulators of other mAChRs.

HIV-1 Capsid Function Is Regulated by Dynamics: Quantitative Atomic-Resolution Insights by Integrating Magic-Angle-Spinning NMR, QM/MM, and MD.

HIV-1 CA capsid protein possesses intrinsic conformational flexibility, which is essential for its assembly into conical capsids and interactions with host factors. CA is dynamic in the assembled capsid, and residues in functionally important regions of the protein undergo motions spanning many decades of time scales. Chemical shift anisotropy (CSA) tensors, recorded in magic-angle-spinning NMR experiments, provide direct residue-specific probes of motions on nano- to microsecond time scales. We combined NMR, MD, and density-functional-theory calculations, to gain quantitative understanding of internal backbone dynamics in CA assemblies, and we found that the dynamically averaged 15N CSA tensors calculated by this joined protocol are in remarkable agreement with experiment. Thus, quantitative atomic-level understanding of the relationships between CSA tensors, local backbone structure, and motions in CA assemblies is achieved, demonstrating the power of integrating NMR experimental data and theory for characterizing atomic-resolution dynamics in biological systems.

Positive Allosteric Modulation of the Muscarinic M1 Receptor Improves Efficacy of Antipsychotics in Mouse Glutamatergic Deficit Models of Behavior.

Current antipsychotics are effective in treating the positive symptoms associated with schizophrenia, but they remain suboptimal in targeting cognitive dysfunction. Recent studies have suggested that positive allosteric modulation of the M1 muscarinic acetylcholine receptor (mAChR) may provide a novel means of improving cognition. However, very little is known about the potential of combination therapies in extending coverage across schizophrenic symptom domains. This study investigated the effect of the M1 mAChR positive allosteric modulator BQCA [1-(4-methoxybenzyl)-4-oxo-1,4-dihydroquinoline-3-carboxylic acid], alone or in combination with haloperidol (a first-generation antipsychotic), clozapine (a second-generation atypical antipsychotic), or aripiprazole (a third-generation atypical antipsychotic), in reversing deficits in sensorimotor gating and spatial memory induced by the N-methyl-d-aspartate receptor antagonist, MK-801 [(5R,10S)-(+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine]. Sensorimotor gating and spatial memory induction are two models that represent aspects of schizophrenia modeled in rodents. In prepulse inhibition (an operational measure of sensorimotor gating), BQCA alone had minimal effects but exhibited different levels of efficacy in reversing MK-801-induced prepulse inhibition disruptions when combined with a subeffective dose of each of the three (currently prescribed) antipsychotics. Furthermore, the combined effect of BQCA and clozapine was absent in M1-/- mice. Interestingly, although BQCA alone had no effect in reversing MK-801-induced memory impairments in a Y-maze spatial test, we observed a reversal upon the combination of BQCA with atypical antipsychotics, but not with haloperidol. These findings provide proof of concept that a judicious combination of existing antipsychotics with a selective M1 mAChR positive allosteric modulator can extend antipsychotic efficacy in glutamatergic deficit models of behavior.

Automated parameter estimation for biological models using Bayesian statistical model checking.

BACKGROUND: Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. RESULTS: Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. CONCLUSIONS: We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.