ACS Chemical Neuroscience最新文献

Replacement of the phenolic hydroxy in 3-((1R,5S,9R)-2-phenethyl-9-vinyl-2-azabicyclo[3.3.1]nonan-5-yl)phenol (DC-1-76.2), a potent efficacious MOR agonist, with an amide bioisosteric moiety provided a MOR partial agonist with morphine-like potency in the forskolin-induced cAMP accumulation assay and in the [³⁵S]GTPγS functional assay. This amide, 5, had superior metabolic stability in comparison to its precursor in human and mouse liver microsomes. However, in an antinociception study, an assay of pain-depressed locomotion in mice, it was found to possess shorter antinociceptive activity than its precursor. The in vitro and in vivo data enabled the characterization of amide, 5, as a functionally selective, low-efficacy, and low-potency MOR agonist with a relatively short duration of action in vivo. Modification of the N-phenethyl substituent in DC-1-76.2 gave a number of highly interesting partial agonists and the unexpectedly potent antagonist, 17. The results of molecular docking and binding free energy calculations for DC-1-76.2 and 17 provided details about their receptor interactions and supported their functional roles. Several analogs synthesized were found to have sufficient potency in vitro to warrant further study.

Herein, we report the structure-activity relationship to develop novel tricyclic M₄ positive allosteric modulator scaffolds with improved pharmacological properties. This endeavor involved modifying a 5-amino-3,4-dimethylthieno[2,3-c]pyridazine-6-carboxamide core via a "tie-back" strategy to discover a novel tricyclic 3,4-dimethylpyrimido[4',5':4,5]thieno[2,3-c]pyridazine core. From this exercise, VU6008055/AF98943 was identified as a preclinical candidate, which displays low nanomolar potency against both human and rat M₄. Moreover, VU6008055 is highly brain penetrant, has an overall superior pharmacological and DMPK profile to previously reported M₄ PAMs, and demonstrates efficacy in preclinical models of antipsychotic-like activity.

Understanding the dynamics of Aβ aggregation is critical for elucidating Alzheimer's disease (AD) progression. This study extends our previous work on Aβ42 using fast photochemical oxidation of proteins (FPOP) and pulsed hydrogen-deuterium exchange and introduces mass spectrometry (MS)-based glycine ethyl ester (GEE) footprinting, combined with kinetic modeling, to characterize Aβ42 conformational changes and elucidate polymer populations along its aggregation pathways. We investigated Aβ42 conformational changes by analyzing three distinct peptide regions generated by Lys-N digestion, revealing three different views of the aggregation behaviors. The middle and C-terminal regions are identified as primary aggregation sites; in contrast, the N-terminal peptide exhibited only minor changes in GEE modification, supporting its limited involvement in intermolecular interactions during aggregation. Amino-acid-level analysis provided higher spatial resolution: D1 underwent relatively constant footprinting throughout aggregation, whereas E3/D7, E22, and D23 showed more substantial decreases in the level of modification, underscoring their critical roles in aggregation. By integrating these findings with kinetic modeling, we identified four predominant polymeric populations involved in Aβ1-42 aggregation. This study reports, for the first time, a stable, specific, and slow chemical footprinting approach to characterizing Aβ1-42 aggregation, offering new insights into Aβ1-42 polymerization dynamics and enhancing our understanding of its role in AD pathology. The solvent accessibility features of the six acidic amino acids and the C terminus calculated from the final, fibril state structure of Aβ42 are consistent with the footprinting results.

Parkinson's disease is one of the neuropathies characterized by accumulation of the α-synuclein protein, leading to motor dysfunction. Levodopa is the gold standard treatment; however, in long-term usage, it leads to levodopa-induced dyskinesia (LID). New therapeutic options are need of the hour to treat the α-synuclein-based neuropathies. The role of imbalance of neurotransmitters other than dopamine has been underestimated in α-synuclein-based neuropathies. Here, we explore the role of serotonin, epinephrine, and norepinephrine as a therapeutic moiety. For the efficient in vivo delivery, we use a DNA nanotechnology-based DNA tetrahedron that has shown the potential to cross the biological barriers. In this study, we explore the use of DNA nanodevices, particularly a DNA tetrahedron functionalized with neurotransmitters, as a novel therapeutic approach for MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine)-induced Parkinson's disease in a PC12 cellular system. We first establish the effect of these nanodevices on the clearance of the α-synuclein protein in cells. We follow the study by understanding the various cellular processes like ROS, iron accumulation, and lipid peroxidation. We also explore the effect of the neurotransmitter-loaded nanodevices in an in vivo zebrafish model. We show that neurotransmitter-loaded DNA nanocages can potentially clear the MPTP-induced α-synuclein aggregates in cells and in vivo. The findings of these works open up new avenues for use of DNA nanotechnology by functionalizing it with neurotransmitters for future therapeutics in treatment of neurodegenerative diseases such as Parkinson's disease.

Gut-brain axis, an intricate, two-way communication network between gut microorganisms and the central nervous system, plays a critical role in controlling brain function and thereby influencing mental health. Changes to this axis, frequently due to shifts in gut microbiota, can greatly affect brain function by hindering the creation of essential metabolites. This review examines new nutritional trends, including fermented foods and diets rich in prebiotics, that demonstrate the potential to improve microbial diversity and metabolic well-being. Although current studies emphasize possible advantages, most concentrate mainly on older populations, leaving research in younger groups limited. The field of nutritional psychiatry encounters difficulties due to the diversity in research methodologies and the intricacies of nutrient balance, potentially hindering prompt interventions. This review highlights the necessity for prolonged research to evaluate the effects of eating habits, especially regarding Western dietary patterns. Promising fields include the influence of the Mediterranean diet, the role of symbiotic and short-chain fatty acids (SCFAs), and the importance of high-fiber foods, polyphenols, and fruits and vegetables in enhancing mental health through gut-derived metabolites. We promote interdisciplinary methods that combine nutrition science, microbiology, and neurology to create tailored dietary recommendations focused on enhancing brain health.

Central nervous system (CNS) drugs have the highest clinical attrition, often due to CNS-related toxicities such as drug-induced seizures (DIS). Early prediction of DIS risk could reduce failure rates and optimize drug development by prioritizing testing in experimental models of DIS. Using seizure-relevant Adverse Outcome Pathways (AOPs) from various sources, we identified 67 seizure-associated protein targets. Biological activity data (EC₅₀, IC₅₀, K_i) for these targets were curated from ChEMBL, enabling development of ∼2000 regression and classification (random forest, support vector, XGBoost) models. Support vector regression (SVR) models achieved an average MAE of 0.54  ±  0.09 (-log M), while random forest classifiers yielded mean ROC AUC, accuracy, and recall of 0.88, 0.85, and 0.70, respectively (5-fold CV) across all targets. Multitarget XGBoost models concatenating ECFP6 fingerprints and target encodings (one-hot or ProtBERT) also demonstrated excellent overall performance, although their predictive accuracy was notably lower for leave-out sets compared to individual target-specific models. These models were used to predict activity for a seizure-liability data set with target-annotated DIS risk predictions. Overall, our findings support the utility of using target-specific machine-learning models for DIS prediction to aid in early toxicity testing prioritization and reduce CNS drug attrition.

The aggregation of misfolded proteins into β-sheet-rich fibrils constitutes a characteristic feature of neurodegenerative disorders and represents a therapeutic target. While cryo-electron microscopy has elucidated ordered binding patterns of small molecules on fibril surfaces, the mechanisms of ordered aggregate formation generally remain unclear. This study employs molecular dynamics (MD) simulations of the model ligand GTP-1 to examine fibril-templated ligand aggregation and elucidate the molecular determinants governing the aggregation process. Our results showed that in aqueous solution, GTP-1 molecules form dynamic clusters without preferential configurations, whereas tau fibril surfaces induce organized aggregation through protein-ligand hydrogen bonding and ligand-ligand π-π stacking interactions. 1000 independent 100 ns simulations were initiated from diverse ligand conformations to comprehensively sample the conformational landscape. Analysis of the MD trajectories revealed two distinct aggregation pathways. Starting from random initial configurations, on-pathway trajectories spontaneously sampled crystal-structure-like conformations during the simulation, and these conformations exhibited high kinetic stability after formation. In contrast, off-pathway trajectories were characterized by ligands adopting non-native binding geometries, with continuous interconversions between multiple disordered states. The conformational stability of on-pathway states was attributed to optimal surface complementarity and enhanced intermolecular interactions, while off-pathway configurations exhibited reduced structural order and increased conformational flexibility. Quantitative analysis demonstrated differential hydrogen-bonding patterns, with on-pathway aggregates forming 2.01 bonds per structure compared to 0.74 in off-pathway configurations. Energy decomposition identified protein-ligand interactions as the primary determinant of binding energetics, highlighting the direct influence of fibril surface properties on ligand aggregation. These findings provide a mechanistic basis for fibril-templated aggregation and offer a rational foundation for designing diagnostic agents targeting pathological protein fibrils in neurodegenerative diseases.

Alzheimer's disease (AD) is associated with synaptic and memory dysfunction. One of the hallmarks of AD is reactive astrogliosis, with reactive astrocytes surrounding amyloid plaques in the brain. Astrocytes have also been shown to be actively involved in disease progression, nevertheless, mechanistic information about their role in synaptic transmission during AD pathology is lacking. Astrocytes maintain synaptic transmission by taking up extracellular glutamate during synaptic activity through astrocytic glutamate transporter GLT-1, but its function has been difficult to measure in real-time in AD pathology. Here, we used an App knock-in AD model (App^NL-G-F) carrying the Swedish, Arctic and Beyreuther mutations associated with AD and exhibiting AD-like Aβ plaque deposition and memory impairment. Using immunohistochemistry, patch-clamp of astrocytes, and Western blot from tissue and FACS isolated synaptosomes, we found that App^NL-G-F mice at 6-8 months of age have astrocytes with clearly altered morphology compared to wild-type (WT). Moreover, astrocyte glutamate clearance function in App^NL-G-F mice, measured as electrophysiological recordings of glutamate transporter currents, was severely impaired compared to WT animals. The reduction of glutamate uptake by astrocytes cannot be explained by GLT-1 protein levels, which were unchanged in synaptosomes and hippocampus of App^NL-G-F mice. Our data suggest that astrocytic glutamate transporters are affected by excess Aβ42 in the brain contributing to synaptic dysfunction in the hippocampus. This data contributes to the notion of restoring astrocyte synaptic function as a potential therapeutic strategy to treat AD.

Here, the model of dissipative waveguide presents an axon where oscillations of ions generate electromagnetic waves that extend at the speed of light in a given medium. A transmission of spikes (wave packets) along axons is perfectly described by the Heaviside-Maxwell telegraph equations, and the instantaneous action potential at any point of the axon is the sum of waves running in opposite directions. Its speed can change in a wide range depending on the boundary conditions of the transmission line. The unmyelinated axon transmits information in the brain without the required precision and synchronization of oscillations owing to the frequency dispersion and disintegration of the action potential in the axon. Opposite, myelin sheaths around the axon increase the precision and synchronization of oscillations because their helical structure and aqueous layers reduce a distributed capacitance and transverse conductivity of the axon, increase its inductance due to the ionic conductivity in the spiral aqueous layer, and reduce a longitudinal resistance of the axon by the parallel conductivity of this multiple layer. Therefore, myelin sheaths transform the axon into an ideal transmission line and, with the help of a diffraction grating from Ranvier nodes, into an interference filter of the spike wave packet individualizing every neuron because spectral characteristics of its spikes are very sensitive to chemical and geometric changes of myelin sheaths that cannot be identical.