The Anti-Nociceptive Effects of Nicotine in Humans: A Systematic Review and Meta-Analysis.

BACKGROUND: Pain can have a serious impact on a patient's physical, mental, and social health, often causing their quality of life to decline. Various nicotine dosage forms, such as nicotine patches and nasal spray, have been developed and used as analgesics in clinical settings. However, there is controversy over the anti-nociceptive effects of nicotine among different clinical trials. The purpose of this meta-analysis is to quantify the analgesic effect of nicotine patches, nicotine nasal spray, and tobacco smoking on pain in humans. METHODS: Relevant articles published in English prior to July 2023 were identified using the PubMed, Cochrane Library, and Embase online databases in accordance with PRISMA (2020) guidelines. Two reviewers independently screened and selected studies, extracted data, and assessed the quality of the included studies using version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2). RStudio was used for data synthesis, heterogeneity assessment, sensitivity analysis, publication bias assessment, trim-and-fill analyses, and generating forest plots. RESULTS: Sixteen eligible articles, including k = 5 studies of pain tolerance (n = 210), k = 5 studies of pain threshold (n = 210), and k = 12 studies of pain scores (N = 1249), were included for meta-analysis. Meta-analytic integration for pain threshold (Hedges' g = 0.28, 95% CI = 0-0.55, Z = 1.99, p = 0.05) and pain tolerance (Hedges' g = 0.32, 95% CI = 0.05-0.59, Z = 2.30, p = 0.02) revealed that nicotine administered via tobacco smoke generated acute analgesic effects to thermal stimuli. Meta-analytic integration for pain scores revealed that nicotine had a weak anti-nociceptive effect on postoperative pain of -0.37 (95% CI = -0.77 to 0.03, Z = -1.80) but with no statistical significance (p = 0.07). In addition, a limited number of included studies revealed that long-term smoking produced hyperalgesia that may be characterized as small to medium in magnitude (Hedges' g = 0.37, 95% CI = 0.29-0.64, Z = 5.33, p < 0.01). CONCLUSION: These results help to clarify the mixed outcomes of trials and may ultimately inform the treatment of pain. We observed that acute nicotine administration prolonged the laboratory-induced pain threshold and tolerance time and may mildly relieve postoperative pain. In addition, long-term tobacco smoking may have a nociceptive effect on different types of chronic pain. More research is needed to determine the anti-nociceptive effects of nicotine in humans, and to understand the optimal timing, dose, and method of delivery of nicotine.

Deep learning structural insights into heterotrimeric alternatively spliced P2X7 receptors.

P2X7 receptors (P2X7Rs) are membrane-bound ATP-gated ion channels that are composed of three subunits. Different subunit structures may be expressed due to alternative splicing of the P2RX7 gene, altering the receptor's function when combined with the wild-type P2X7A subunits. In this study, the application of the deep-learning method, AlphaFold2-Multimer (AF2M), for the generation of trimeric P2X7Rs was validated by comparing an AF2M-generated rat wild-type P2X7A receptor with a structure determined by cryogenic electron microscopy (cryo-EM) (Protein Data Bank Identification: 6U9V). The results suggested AF2M could firstly, accurately predict the structures of P2X7Rs and secondly, accurately identify the highest quality model through the ranking system. Subsequently, AF2M was used to generate models of heterotrimeric alternatively spliced P2X7Rs consisting of one or two wild-type P2X7A subunits in combination with one or two P2X7B, P2X7E, P2X7J, and P2X7L splice variant subunits. The top-ranking models were deemed valid based on AF2M's confidence measures, stability in molecular dynamics simulations, and consistent flexibility of the conserved regions between the models. The structure of the heterotrimeric receptors, which were missing key residues in the ATP binding sites and carboxyl terminal domains (CTDs) compared to the wild-type receptor, help to explain their observed functions. Overall, the models produced in this study (available as supplementary material) unlock the possibility of structure-based studies into the heterotrimeric P2X7Rs.

Combination of High-Resolution Structures for the B Cell Receptor and Co-Receptors Provides an Understanding of Their Interactions with Therapeutic Antibodies.

B cells are central to the adaptive immune response, providing long lasting immunity after infection. B cell activation is mediated by a cell surface B cell receptor (BCR) following recognition of an antigen. BCR signaling is modulated by several co-receptors including CD22 and a complex that contains CD19 and CD81. Aberrant signaling through the BCR and co-receptors promotes the pathogenesis of several B cell malignancies and autoimmune diseases. Treatment of these diseases has been revolutionized by the development of monoclonal antibodies that bind to B cell surface antigens, including the BCR and its co-receptors. However, malignant B cells can escape targeting by several mechanisms and until recently, rational design of antibodies has been limited by the lack of high-resolution structures of the BCR and its co-receptors. Herein we review recently determined cryo-electron microscopy (cryo-EM) and crystal structures of the BCR, CD22, CD19 and CD81 molecules. These structures provide further understanding of the mechanisms of current antibody therapies and provide scaffolds for development of engineered antibodies for treatment of B cell malignancies and autoimmune diseases.

Binding and Dynamics Demonstrate the Destabilization of Ligand Binding for the S688Y Mutation in the NMDA Receptor GluN1 Subunit.

Encephalopathies are brain dysfunctions that lead to cognitive, sensory, and motor development impairments. Recently, the identification of several mutations within the N-methyl-D-aspartate receptor (NMDAR) have been identified as significant in the etiology of this group of conditions. However, a complete understanding of the underlying molecular mechanism and changes to the receptor due to these mutations has been elusive. We studied the molecular mechanisms by which one of the first mutations within the NMDAR GluN1 ligand binding domain, Ser688Tyr, causes encephalopathies. We performed molecular docking, randomly seeded molecular dynamics simulations, and binding free energy calculations to determine the behavior of the two major co-agonists: glycine and D-serine, in both the wild-type and S688Y receptors. We observed that the Ser688Tyr mutation leads to the instability of both ligands within the ligand binding site due to structural changes associated with the mutation. The binding free energy for both ligands was significantly more unfavorable in the mutated receptor. These results explain previously observed in vitro electrophysiological data and provide detailed aspects of ligand association and its effects on receptor activity. Our study provides valuable insight into the consequences of mutations within the NMDAR GluN1 ligand binding domain.

Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs.

Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based methods. Ligand-based methods encompass techniques including pharmacophore modelling and quantitative structure activity relationships (QSARs), which use the relationship between biological activity and chemical structure to ascertain suitable lead molecules. In contrast, structure-based methods use information about the binding site architecture from an established protein structure to select suitable molecules for further investigation. In recent years, deep learning techniques have been applied in drug design and present an exciting addition to CADD workflows. Despite the difficulties associated with CNS drug discovery, advances towards new pharmaceutical treatments continue to be made, and CADD has supported these findings. This review explores various CADD techniques and discusses applications in CNS drug discovery from 2018 to November 2022.

GABAA receptors as targets for anaesthetics and analgesics and promising candidates to help treat coronavirus infections: A mini-review.

GABA is a major inhibitory neurotransmitter that regulates the balance between excitatory and inhibitory circuits in the human nervous system. The GABA receptors are divided into three main subtypes, GABAA , GABAB , and GABAC (also termed GABAA rho) receptors. GABAA receptors are pentameric ligand-gated ion channels widely expressed throughout the central and peripheral nervous system. The activation of GABAA receptors results in opening of an anion-selective channel that mainly gates chloride ions and allows them to flow into the neuron, causing hyperpolarization of the cell membrane that dampens neural excitability. This makes GABAA receptors critical anaesthetic and analgesic targets for existing as well as for the development of novel drugs. In this review, we first summarize the biochemical properties of GABAA receptors and the clinical anaesthetics and analgesics targeting the receptors. In a forward-looking section, we summarize the emerging role of GABAergic signalling in treatment of COVID-19 related infections. Finally, we discuss the opportunities arising from targeting specific and unique subunit interfaces for the development of novel anaesthetics and analgesics leading to more efficient therapies.

Alternatively Spliced Isoforms of the P2X7 Receptor: Structure, Function and Disease Associations.

The P2X7 receptor (P2X7R) is an ATP-gated membrane ion channel that is expressed by multiple cell types. Following activation by extracellular ATP, the P2X7R mediates a broad range of cellular responses including cytokine and chemokine release, cell survival and differentiation, the activation of transcription factors, and apoptosis. The P2X7R is made up of three P2X7 subunits that contain specific domains essential for the receptor's varied functions. Alternative splicing produces P2X7 isoforms that exclude one or more of these domains and assemble in combinations that alter P2X7R function. The modification of the structure and function of the P2X7R may adversely affect cellular responses to carcinogens and pathogens, and alternatively spliced (AS) P2X7 isoforms have been associated with several cancers. This review summarizes recent advances in understanding the structure and function of AS P2X7 isoforms and their associations with cancer and potential role in modulating the inflammatory response.

Novel methyllycaconitine analogues selective for the α4ß2 over α7 nicotinic acetylcholine receptors.

Analogues of methyllycaconitine (MLA) based on a (3-ethyl-9-methylidene-3-azabicyclo[3.3.1]nonan-1-yl)methanol template have been designed and synthesised that incorporate the modified ester sidechains distinct from that present in the natural product. Electrophysiology experiments using Xenopus oocytes expressing nicotinic acetylcholine receptors (nAChRs) revealed selected analogues served as non-competitive inhibitors that showed selectivity for the α4ß2 over α7 nAChR subtypes, and selectivity for the (α4)3(ß2)2 over (α4)2(ß2)3 stoichiometry. This study more clearly defines the biological effects of MLA analogues and identifies strategies for the development of MLA analogues as selective ligands for the α4ß2 nAChR subtype.

Synthetic Sansanmycin Analogues as Potent Mycobacterium tuberculosis Translocase I Inhibitors.

Herein, we report the design and synthesis of inhibitors of Mycobacterium tuberculosis (Mtb) phospho-MurNAc-pentapeptide translocase I (MurX), the first membrane-associated step of peptidoglycan synthesis, leveraging the privileged structure of the sansanmycin family of uridylpeptide natural products. A number of analogues bearing hydrophobic amide modifications to the pseudo-peptidic end of the natural product scaffold were generated that exhibited nanomolar inhibitory activity against Mtb MurX and potent activity against Mtb in vitro. We show that a lead analogue bearing an appended neopentylamide moiety possesses rapid antimycobacterial effects with a profile similar to the frontline tuberculosis drug isoniazid. This molecule was also capable of inhibiting Mtb growth in macrophages where mycobacteria reside in vivo and reduced mycobacterial burden in an in vivo zebrafish model of tuberculosis.

CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles.

MOTIVATION: Ether-a-go-go-related gene (hERG) channel blockade by small molecules is a big concern during drug development in the pharmaceutical industry. Blockade of hERG channels may cause prolonged QT intervals that potentially could lead to cardiotoxicity. Various in-silico techniques including deep learning models are widely used to screen out small molecules with potential hERG related toxicity. Most of the published deep learning methods utilize a single type of features which might restrict their performance. Methods based on more than one type of features such as DeepHIT struggle with the aggregation of extracted information. DeepHIT shows better performance when evaluated against one or two accuracy metrics such as negative predictive value (NPV) and sensitivity (SEN) but struggle when evaluated against others such as Matthew correlation coefficient (MCC), accuracy (ACC), positive predictive value (PPV) and specificity (SPE). Therefore, there is a need for a method that can efficiently aggregate information gathered from models based on different chemical representations and boost hERG toxicity prediction over a range of performance metrics. RESULTS: In this paper, we propose a deep learning framework based on step-wise training to predict hERG channel blocking activity of small molecules. Our approach utilizes five individual deep learning base models with their respective base features and a separate neural network to combine the outputs of the five base models. By using three external independent test sets with potency activity of IC50 at a threshold of 10 [Formula: see text]m, our method achieves better performance for a combination of classification metrics. We also investigate the effective aggregation of chemical information extracted for robust hERG activity prediction. In summary, CardioTox net can serve as a robust tool for screening small molecules for hERG channel blockade in drug discovery pipelines and performs better than previously reported methods on a range of classification metrics.

Delta-containing GABAA receptors in pain management: Promising targets for novel analgesics.

Communication between nerve cells depends on the balance between excitatory and inhibitory circuits. GABA, the major inhibitory neurotransmitter, regulates this balance and insufficient GABAergic activity is associated with numerous neuropathological disorders including pain. Of the various GABAA receptor subtypes, the δ-containing receptors are particularly interesting drug targets in management of chronic pain. These receptors are pentameric ligand-gated ion channels composed of α, ß and δ subunits and can be activated by ambient levels of GABA to generate tonic conductance. However, only a few ligands preferentially targeting δ-containing GABAA receptors have so far been identified, limiting both pharmacological understanding and drug-discovery efforts, and more importantly, understanding of how they affect pain pathways. Here, we systemically review and discuss the known drugs and ligands with analgesic potential targeting δ-containing GABAA receptors and further integrate the biochemical nature of the receptors with clinical perspectives in pain that might generate interest among researchers and clinical physicians to encourage analgesic discovery efforts leading to more efficient therapies.

Quantitative Toxicity Prediction via Meta Ensembling of Multitask Deep Learning Models.

Toxicity prediction using quantitative structure-activity relationship has achieved significant progress in recent years. However, most existing machine learning methods in toxicity prediction utilize only one type of feature representation and one type of neural network, which essentially restricts their performance. Moreover, methods that use more than one type of feature representation struggle with the aggregation of information captured within the features since they use predetermined aggregation formulas. In this paper, we propose a deep learning framework for quantitative toxicity prediction using five individual base deep learning models and their own base feature representations. We then propose to adopt a meta ensemble approach using another separate deep learning model to perform aggregation of the outputs of the individual base deep learning models. We train our deep learning models in a weighted multitask fashion combining four quantitative toxicity data sets of LD50, IGC50, LC50, and LC50-DM and minimizing the root-mean-square errors. Compared to the current state-of-the-art toxicity prediction method TopTox on LD50, IGC50, and LC50-DM, that is, three out of four data sets, our method, respectively, obtains 5.46, 16.67, and 6.34% better root-mean-square errors, 6.41, 11.80, and 12.16% better mean absolute errors, and 5.21, 7.36, and 2.54% better coefficients of determination. We named our method QuantitativeTox, and our implementation is available from the GitHub repository https://github.com/Abdulk084/QuantitativeTox.

Glutamate, d-(-)-2-Amino-5-Phosphonopentanoic Acid, and N-Methyl-d-Aspartate Do Not Directly Modulate Glycine Receptors.

Replication studies play an essential role in corroborating research findings and ensuring that subsequent experimental works are interpreted correctly. A previously published paper indicated that the neurotransmitter glutamate, along with the compounds N-methyl-d-aspartate (NMDA) and d-(-)-2-amino-5-phosphonopentanoic acid (AP5), acts as positive allosteric modulators of inhibitory glycine receptors. The paper further suggested that this form of modulation would play a role in setting the spinal inhibitory tone and influencing sensory signaling, as spillover of glutamate onto nearby glycinergic synapses would permit rapid crosstalk between excitatory and inhibitory synapses. Here, we attempted to replicate this finding in primary cultured spinal cord neurons, spinal cord slice, and Xenopus laevis oocytes expressing recombinant human glycine receptors. Despite extensive efforts, we were unable to reproduce the finding that glutamate, AP5, and NMDA positively modulate glycine receptor currents. We paid careful attention to critical aspects of the original study design and took into account receptor saturation and protocol deviations such as animal species. Finally, we explored possible explanations for the experimental discrepancy. We found that solution contamination with a high-affinity modulator such as zinc is most likely to account for the error, and we suggest methods for preventing this kind of misinterpretation in future studies aimed at characterizing high-affinity modulators of the glycine receptor. SIGNIFICANCE STATEMENT: A previous study indicates that glutamate spillover onto inhibitory synapses can directly interact with glycine receptors to enhance inhibitory signalling. This finding has important implications for baseline spinal transmission and may play a role when chronic pain develops. However, we failed to replicate the results and did not observe glutamate, d-(-)-2-amino-5-phosphonopentanoic acid, or N-methyl-d-aspartate modulation of native or recombinant glycine receptors. We ruled out various sources for the discrepancy and found that the most likely cause is solution contamination.

Heterologous expression of concatenated nicotinic ACh receptors: Pros and cons of subunit concatenation and recommendations for construct designs.

BACKGROUND AND PURPOSE: Concatenation of Cys-loop receptor subunits is a commonly used technique to ensure experimental control of receptor assembly. However, we recently demonstrated that widely used constructs did not lead to the expression of uniform pools of ternary and more complex receptors. The aim was therefore to identify viable strategies for designing concatenated constructs that would allow strict control of resultant receptor pools. EXPERIMENTAL APPROACH: Concatenated dimeric, tetrameric, and pentameric α4ß2-containing nicotinic ACh (nACh) receptor constructs were designed with successively shorter linker lengths and expressed in Xenopus laevis oocytes. Resulting receptor stoichiometries were investigated by functional analysis in two-electrode voltage-clamp experiments. Molecular dynamics simulations were performed to investigate potential effects of linkers on the 3D structure of concatemers. KEY RESULTS: Dimeric constructs were found to be unreliable and should be avoided for expression of ternary receptors. By introducing two short linkers, we obtained efficient expression of uniform receptor pools with tetrameric and pentameric constructs. However, linkers should not be excessively short as that introduces strain on the 3D structure of concatemers. CONCLUSION AND IMPLICATIONS: The data demonstrate that design of concatenated Cys-loop receptors requires a compromise between the desire for control of assembly and avoiding introduction of strain on the resulting protein. The overall best strategy was found to be pentameric constructs with carefully optimised linker lengths. Our findings will advance studies of ternary or more complex Cys-loop receptors as well as enabling detailed analysis of how pharmacological agents interact with stoichiometry-specific binding sites.

Structure-Based Discovery of Dual-Target Hits for Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptors: In Silico Studies and In Vitro Confirmation.

Despite extensive efforts in the development of drugs for complex neurodegenerative diseases, treatment often remains challenging or ineffective, and hence new treatment strategies are necessary. One approach is the design of multi-target drugs, which can potentially address the complex nature of disorders such as Alzheimer's disease. We report a method for high throughput virtual screening aimed at identifying new dual target hit molecules. One of the identified hits, N,N-dimethyl-1-(4-(3-methyl-[1,2,4]triazolo[4,3-a]pyrimidin-6-yl)phenyl)ethan-1-amine (Ý;mir-2), has dual-activity as an acetylcholinesterase (AChE) inhibitor and as an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist. Using computational chemistry methods, parallel and independent screening of a virtual compound library consisting of 3,848,234 drug-like and commercially available molecules from the ZINC15 database, resulted in an intersecting set of 57 compounds, that potentially possess activity at both of the two protein targets. Based on ligand efficiency as well as scaffold and molecular diversity, 16 of these compounds were purchased for in vitro validation by Ellman's method and two-electrode voltage-clamp electrophysiology. Ý;mir-2 was shown to exhibit the desired activity profile (AChE IC50 = 2.58 ± 0.96 µM; α7 nAChR activation = 7.0 ± 0.9% at 200 µM) making it the first reported compound with this particular profile and providing further evidence of the feasibility of in silico methods for the identification of novel multi-target hit molecules.

Synergistic effects of binary ionic liquid-solvent systems on enzymatic esterification of esculin.

This work established a binary ionic liquid-solvent system for effective enzymatic esterification of naturally occurring phenolic glycosides (flavonoids); which could result in a dramatic enhancement of Novozym 435-catalyzed esterification of esculin, demonstrating a great synergetic effect. In essence, [OMIM][BF4]-toluene and [TOMA][Tf2N]-hexane binary systems both served >90 mol% of conversions of esculin after 96 h of reaction at 60 °C. Typically, binary [TOMA][Tf2N]-hexane system enabled Novozym 435 with extremely high catalytic efficiency (kcat/Km = 17.57 × 10-2 (Ms)-1), which was 55-fold higher than that Novozym 435 exhibited in t-butanol solvent (one of the best solvent systems for esterification reactions). It was also found that the superiormatching in property and structure between IL and solvent was the decisive factor for the outperformance of [TOMA][Tf2N]-hexane binary system, in which [TOMA] and hexane facilitate the solubilization of esculin and fatty acids and [Tf2N]- anions and hexane offer protective effects for lipase at elevated temperatures.

Concatenated γ-aminobutyric acid type A receptors revisited: Finding order in chaos.

γ-aminobutyric acid type A receptors (GABAARs), the major inhibitory neurotransmitter receptors in the mammalian central nervous system, are arguably the most challenging member of the pentameric Cys-loop receptors to study due to their heteromeric structure. When two or more subunits are expressed together in heterologous systems, receptors of variable subunit type, ratio, and orientation can form, precluding accurate interpretation of data from functional studies. Subunit concatenation is a technique that involves the linking of individual subunits and in theory allows the precise control of the uniformity of expressed receptors. In reality, the resulting concatemers from widely used constructs are flexible in their orientation and may therefore assemble with themselves or free GABAAR subunits in unexpected ways. In this study, we examine functional responses of receptors from existing concatenated constructs and describe refinements necessary to allow expression of uniform receptor populations. We find that dimers from two commonly used concatenated constructs, ß-23-α and α-10-ß, assemble readily in both the clockwise and the counterclockwise orientations when coexpressed with free subunits. Furthermore, we show that concatemers formed from new tetrameric α-10-ß-α-ß and α-10-ß-α-γ constructs also assemble in both orientations with free subunits to give canonical αßγ receptors. To restrict linker flexibility, we systematically shorten linker lengths of dimeric and pentameric constructs and find optimized constructs that direct the assembly of GABAARs only in one orientation, thus eliminating the ambiguity associated with previously described concatemers. Based on our data, we revisit some noncanonical GABAAR configurations proposed in recent years and explain how the use of some concatenated constructs may have led to wrong conclusions. Our results help clarify current contradictions in the literature regarding GABAAR subunit stoichiometry and arrangement. The lessons learned from this study may guide future efforts in understanding other related heteromeric receptors.

Functional genomics of epilepsy-associated mutations in the GABAA receptor subunits reveal that one mutation impairs function and two are catastrophic.

A number of epilepsy-causing mutations have recently been identified in the genes of the α1, ß3, and γ2 subunits comprising the γ-aminobutyric acid type A (GABAA) receptor. These mutations are typically dominant, and in certain cases, such as the α1 and ß3 subunits, they may lead to a mix of receptors at the cell surface that contain no mutant subunits, a single mutated subunit, or two mutated subunits. To determine the effects of mutations in a single subunit or in two subunits on receptor activation, we created a concatenated protein assembly that links all five subunits of the α1ß3γ2 receptor and expresses them in the correct orientation. We created nine separate receptor variants with a single-mutant subunit and four receptors containing two subunits of the γ2R323Q, ß3D120N, ß3T157M, ß3Y302C, and ß3S254F epilepsy-causing mutations. We found that the singly mutated γ2R323Q subunit impairs GABA activation of the receptor by reducing GABA potency. A single ß3D120N, ß3T157M, or ß3Y302C mutation also substantially impaired receptor activation, and two copies of these mutants within a receptor were catastrophic. Of note, an effect of the ß3S254F mutation on GABA potency depended on the location of this mutant subunit within the receptor, possibly because of the membrane environment surrounding the transmembrane region of the receptor. Our results highlight that precise functional genomic analyses of GABAA receptor mutations using concatenated constructs can identify receptors with an intermediate phenotype that contribute to epileptic phenotypes and that are potential drug targets for precision medicine approaches.

Novel Approach for the Search for Chemical Scaffolds with Dual Activity with Acetylcholinesterase and the α7 Nicotinic Acetylcholine Receptor-A Perspective for the Treatment of Neurodegenerative Disorders.

Neurodegenerative disorders, including Alzheimer's disease, belong to the group of the most difficult and challenging conditions with very limited treatment options. Attempts to find new drugs in most cases fail at the clinical stage. New tactics to develop better drug candidates to manage these diseases are urgently needed. It is evident that better understanding of the neurodegeneration process is required and targeting multiple receptors may be essential. Herein, we present a novel approach, searching for dual active compounds interacting with acetylcholinesterase (AChE) and the α7 nicotinic acetylcholine receptor (nAChR) using computational chemistry methods including homology modelling and high throughput virtual screening. Activities of identified hits were evaluated at the two targets using the colorimetric method of Ellman and two-electrode voltage-clamp electrophysiology, respectively. Out of 87,250 compounds from a ZINC database of natural products and their derivatives, we identified two compounds, 8 and 9, with dual activity and balanced IC50 values of 10 and 5 µM at AChE, and 34 and 14 µM at α7 nAChR, respectively. This is the first report presenting successful use of virtual screening in finding compounds with dual mode of action inhibiting both the AChE enzyme and the α7 nAChR and shows that computational methods can be a valuable tool in the early lead discovery process.

Revisiting autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE) mutations in the nicotinic acetylcholine receptor reveal an increase in efficacy regardless of stochiometry.

Autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE) is a genetic form of epilepsy that is caused by mutations in several genes, including genes encoding for the α4 and ß2 subunits of the nicotinic acetylcholine (nACh) receptor. Pentameric α4ß2 nACh receptors are the most abundant nicotinic receptor in the mammalian brain and form two stoichiometries, the (α4)3(ß2)2 and (α4)2(ß2)3 receptors that differ in their physiological and pharmacological properties. The purpose of this study was to investigate how ADNFLE mutations ß2V287M, ß2V287L or α4T293I manifest themselves in different receptor stoichiometries. We expressed wild-type and mutant receptors in Xenopus oocytes and measured the response to ACh and other agonists at both receptor stoichiometries. For all three mutations, the efficacy of ACh at (α4)2(ß2)3 receptors was increased. At (α4)3(ß2)2 receptors, the efficacy of activation was increased both when two molecules of agonist, either ACh or the site-selective agonist sazetidine-A, were bound at the α4-ß2 interfaces, and when a third ACh molecule was bound at the α4-α4 site. Regardless of stoichiometry, the mutations increased the current elicited by low concentrations of ACh. Further, the smoking cessation agents, nicotine, varenicline and cytisine increased activation of mutant (α4)3(ß2)2 receptors, while only nicotine increased activation of mutant (α4)2(ß2)3 receptors. Chronic exposure of all agonists reduced ACh-activation levels at low and high ACh concentrations. From this, we concluded that mutations that cause ADNFLE manifest themselves in a change in efficacy regardless of the stoichiometry of the receptor.