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Socała K, Jakubiec M, Abram M, Mlost J, Starowicz K, Kamiński RM, Ciepiela K, Andres-Mach M, Zagaja M, Metcalf CS, Zawadzki P, Wlaź P, Kamiński K. TRPV1 channel in the pathophysiology of epilepsy and its potential as a molecular target for the development of new antiseizure drug candidates. Prog Neurobiol 2024; 240:102634. [PMID: 38834133 DOI: 10.1016/j.pneurobio.2024.102634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 04/26/2024] [Accepted: 05/28/2024] [Indexed: 06/06/2024]
Abstract
Identification of transient receptor potential cation channel, subfamily V member 1 (TRPV1), also known as capsaicin receptor, in 1997 was a milestone achievement in the research on temperature sensation and pain signalling. Very soon after it became evident that TRPV1 is implicated in a wide array of physiological processes in different peripheral tissues, as well as in the central nervous system, and thereby could be involved in the pathophysiology of numerous diseases. Increasing evidence suggests that modulation of TRPV1 may also affect seizure susceptibility and epilepsy. This channel is localized in brain regions associated with seizures and epilepsy, and its overexpression was found both in animal models of seizures and in brain samples from epileptic patients. Moreover, modulation of TRPV1 on non-neuronal cells (microglia, astrocytes, and/or peripheral immune cells) may have an impact on the neuroinflammatory processes that play a role in epilepsy and epileptogenesis. In this paper, we provide a comprehensive and critical overview of currently available data on TRPV1 as a possible molecular target for epilepsy management, trying to identify research gaps and future directions. Overall, several converging lines of evidence implicate TRPV1 channel as a potentially attractive target in epilepsy research but more studies are needed to exploit the possible role of TRPV1 in seizures/epilepsy and to evaluate the value of TRPV1 ligands as candidates for new antiseizure drugs.
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Affiliation(s)
- Katarzyna Socała
- Department of Animal Physiology and Pharmacology, Institute of Biological Sciences, Maria Curie-Skłodowska University, Akademicka 19, Lublin PL 20-033, Poland.
| | - Marcin Jakubiec
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland
| | - Michał Abram
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland
| | - Jakub Mlost
- Department of Neurochemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, Cracow PL 31-343, Poland
| | - Katarzyna Starowicz
- Department of Neurochemistry, Maj Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, Cracow PL 31-343, Poland
| | - Rafał M Kamiński
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland
| | - Katarzyna Ciepiela
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland; Selvita S.A., Bobrzyńskiego 14, Cracow PL 30-348, Poland
| | - Marta Andres-Mach
- Department of Experimental Pharmacology, Institute of Rural Health, Jaczewskiego 2, Lublin PL 20-090, Poland
| | - Mirosław Zagaja
- Department of Experimental Pharmacology, Institute of Rural Health, Jaczewskiego 2, Lublin PL 20-090, Poland
| | - Cameron S Metcalf
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT 84112, USA
| | - Przemysław Zawadzki
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland
| | - Piotr Wlaź
- Department of Animal Physiology and Pharmacology, Institute of Biological Sciences, Maria Curie-Skłodowska University, Akademicka 19, Lublin PL 20-033, Poland
| | - Krzysztof Kamiński
- Department of Medicinal Chemistry, Faculty of Pharmacy, Jagiellonian University Medical College, Medyczna 9, Cracow PL 30-688, Poland
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Bano A, Garg A, Mumtaz, Nidhi, Ashif Khan M. The anti-seizure potential of cysteine leukotriene receptor antagonists: A systematic review of animal studies. Epilepsy Res 2024; 200:107305. [PMID: 38325237 DOI: 10.1016/j.eplepsyres.2024.107305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 12/12/2023] [Accepted: 01/12/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND Emerging literature has suggested the antiepileptic activity of cysteine leukotriene receptor (CysLTR) antagonists in experimental animals of epilepsy. Leukotrienes are substances that cause inflammation and affect brain activity, blood flow, oxidation, and inflammation in the brain. These processes are related to epilepsy and its complications. CysLTR antagonists are drugs that prevent leukotrienes from working. They may be useful for treating epilepsy, especially for people who do not respond to other drugs. Therefore, the current study aims to systematically review the potential anti-seizure effect of CysLTR antagonists in experimental studies. METHOD We systematically reviewed the online databases using online databases such as Google Scholar, science direct, and PubMed until December 2022 to identify experimental studies assessing the anti-seizure activity of CysLTR antagonists. The Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) was used to evaluate the risk of bias (RoB) of the included studies. RESULTS Initially we identified 3823 studies. After screening using inclusion and exclusion criteria, 8 studies were finally included in the current study. All included studies, reported that CysLTR antagonists reduced the intensity of seizures in animal models of epilepsy. CONCLUSION In conclusion, CysLTR antagonists could be a potential therapeutic approach for the treatment of epilepsy. However, further preclinical and clinical studies are required to confirm their efficacy, safety, and mechanism of anti-seizure activity.
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Affiliation(s)
- Aysha Bano
- Department of Translational and Clinical Research, School of Chemical and Life Sciences, Jamia Hamdard New Delhi, 110062, India
| | - Aakriti Garg
- Department of Translational and Clinical Research, School of Chemical and Life Sciences, Jamia Hamdard New Delhi, 110062, India; Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi 110062, India
| | - Mumtaz
- Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi 110062, India
| | - Nidhi
- Department of Translational and Clinical Research, School of Chemical and Life Sciences, Jamia Hamdard New Delhi, 110062, India
| | - Mohd Ashif Khan
- Department of Translational and Clinical Research, School of Chemical and Life Sciences, Jamia Hamdard New Delhi, 110062, India.
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Melancon K, Pliushcheuskaya P, Meiler J, Künze G. Targeting ion channels with ultra-large library screening for hit discovery. Front Mol Neurosci 2024; 16:1336004. [PMID: 38249296 PMCID: PMC10796734 DOI: 10.3389/fnmol.2023.1336004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 12/05/2023] [Indexed: 01/23/2024] Open
Abstract
Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.
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Affiliation(s)
- Kortney Melancon
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- Center for Structural Biology, Vanderbilt University, Nashville, TN, United States
| | | | - Jens Meiler
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- Center for Structural Biology, Vanderbilt University, Nashville, TN, United States
- Medical Faculty, Institute for Drug Discovery, Leipzig University, Leipzig, Germany
- Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Leipzig, Germany
| | - Georg Künze
- Medical Faculty, Institute for Drug Discovery, Leipzig University, Leipzig, Germany
- Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Leipzig, Germany
- Interdisciplinary Center for Bioinformatics, Leipzig University, Leipzig, Germany
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Llanos MA, Enrique N, Esteban-López V, Scioli-Montoto S, Sánchez-Benito D, Ruiz ME, Milesi V, López DE, Talevi A, Martín P, Gavernet L. A Combined Ligand- and Structure-Based Virtual Screening To Identify Novel NaV1.2 Blockers: In Vitro Patch Clamp Validation and In Vivo Anticonvulsant Activity. J Chem Inf Model 2023; 63:7083-7096. [PMID: 37917937 DOI: 10.1021/acs.jcim.3c00645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023]
Abstract
Epilepsy is a neurological disorder characterized by recurrent seizures that arise from abnormal electrical activity in the brain. Voltage-gated sodium channels (NaVs), responsible for the initiation and propagation of action potentials in neurons, play a critical role in the pathogenesis of epilepsy. This study sought to discover potential anticonvulsant compounds that interact with NaVs, specifically, the brain subtype hNaV1.2. A ligand-based QSAR model and a docking model were constructed, validated, and applied in a parallel virtual screening over the DrugBank database. Montelukast, Novobiocin, and Cinnarizine were selected for in vitro testing, using the patch-clamp technique, and all of them proved to inhibit hNaV1.2 channels heterologously expressed in HEK293 cells. Two hits were evaluated in the GASH/Sal model of audiogenic seizures and demonstrated promising activity, reducing the severity of sound-induced seizures at the doses tested. The combination of ligand- and structure-based models presents a valuable approach for identifying potential NaV inhibitors. These findings may provide a basis for further research into the development of new antiseizure drugs for the treatment of epilepsy.
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Affiliation(s)
- Manuel A Llanos
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata B1900ADU, Argentina
| | - Nicolás Enrique
- Facultad de Ciencias Exactas, Departamento de Ciencias Biológicas, Instituto de Estudios Inmunológicos y Fisiopatológicos (IIFP), UNLP, CONICET, asociado CIC PBA, La Plata B1900BJW, Buenos Aires, Argentina
| | - Vega Esteban-López
- Institute for Neuroscience of Castilla y León (INCyL), University of Salamanca, Salamanca 37008, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca 37007, Spain
| | - Sebastian Scioli-Montoto
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata B1900ADU, Argentina
| | - David Sánchez-Benito
- Institute for Neuroscience of Castilla y León (INCyL), University of Salamanca, Salamanca 37008, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca 37007, Spain
| | - María E Ruiz
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata B1900ADU, Argentina
| | - Veronica Milesi
- Facultad de Ciencias Exactas, Departamento de Ciencias Biológicas, Instituto de Estudios Inmunológicos y Fisiopatológicos (IIFP), UNLP, CONICET, asociado CIC PBA, La Plata B1900BJW, Buenos Aires, Argentina
| | - Dolores E López
- Institute for Neuroscience of Castilla y León (INCyL), University of Salamanca, Salamanca 37008, Spain
- Institute for Biomedical Research of Salamanca (IBSAL), Salamanca 37007, Spain
| | - Alan Talevi
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata B1900ADU, Argentina
| | - Pedro Martín
- Facultad de Ciencias Exactas, Departamento de Ciencias Biológicas, Instituto de Estudios Inmunológicos y Fisiopatológicos (IIFP), UNLP, CONICET, asociado CIC PBA, La Plata B1900BJW, Buenos Aires, Argentina
| | - Luciana Gavernet
- Laboratory of Bioactive Compounds Research and Development (LIDeB), Department of Biological Sciences, Faculty of Exact Sciences, National University of La Plata (UNLP), La Plata B1900ADU, Argentina
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Wei X, Yang Q, Yang Z, Huang T, Yang H, Wang L, Pan L, Ding J. Discovery of novel TRPV1 modulators through machine learning-based molecular docking and molecular similarity searching. Chem Biol Drug Des 2023; 102:409-423. [PMID: 37489095 DOI: 10.1111/cbdd.14270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 05/04/2023] [Accepted: 05/09/2023] [Indexed: 07/26/2023]
Abstract
The transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pain caused by various factors and have curative effects in various diseases, such as itch, cancer, and cardiovascular diseases. Therefore, the development of TRPV1 channel modulators is of great importance. In this study, the structure-based virtual screening and ligand-based virtual screening methods were used to screen compound databases respectively. In the structure-based virtual screening route, a full-length human TRPV1 protein was first constructed, three molecular docking methods with different precisions were performed based on the hTRPV1 structure, and a machine learning-based rescoring model by the XGBoost algorithm was constructed to enrich active compounds. In the ligand-based virtual screening route, the ROCS program was used for 3D shape similarity searching and the EON program was used for electrostatic similarity searching. Final 77 compounds were selected from two routes for in vitro assays. The results showed that 8 of them were identified as active compounds, including three hits with IC50 values close to capsazepine. In addition, one hit is a partial agonist with both agonistic and antagonistic activity. The mechanisms of some active compounds were investigated by molecular dynamics simulation, which explained their agonism or antagonism.
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Affiliation(s)
- Xinmiao Wei
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
| | - Qifan Yang
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
| | - Zhijiang Yang
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
| | - Tengxin Huang
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
- School of Physics and Electronic Engineering, Sichuan University of Science & Engineering, Zigong, China
| | - Hang Yang
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
- School of Physics and Electronic Engineering, Sichuan University of Science & Engineering, Zigong, China
| | - Liangliang Wang
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
| | - Li Pan
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
| | - Junjie Ding
- State Key Laboratory of NBC Protection for Civilian, Beijing, China
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Pliushcheuskaya P, Künze G. Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels. Int J Mol Sci 2023; 24:ijms24119226. [PMID: 37298178 DOI: 10.3390/ijms24119226] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/16/2023] [Accepted: 05/22/2023] [Indexed: 06/12/2023] Open
Abstract
Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.
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Affiliation(s)
- Palina Pliushcheuskaya
- Institute for Drug Discovery, Medical Faculty, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany
| | - Georg Künze
- Institute for Drug Discovery, Medical Faculty, University of Leipzig, Brüderstr. 34, D-04103 Leipzig, Germany
- Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany
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Wang Y. Multidisciplinary Advances Address the Challenges in Developing Drugs against Transient Receptor Potential Channels to Treat Metabolic Disorders. ChemMedChem 2023; 18:e202200562. [PMID: 36530131 DOI: 10.1002/cmdc.202200562] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/01/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022]
Abstract
Transient receptor potential (TRP) channels are cation channels that regulate key physiological and pathological processes in response to a broad range of stimuli. Moreover, they systemically regulate the release of hormones, metabolic homeostasis, and complications of diabetes, which positions them as promising therapeutic targets to combat metabolic disorders. Nevertheless, there are significant challenges in the design of TRP ligands with high potency and durability. Herein we summarize the four challenges as hydrophobicity, selectivity, mono-target therapy, and interspecies discrepancy. We present 1134 TRP ligands with diversified modes of TRP-ligand interaction and provide a detailed discussion of the latest strategies, especially cryogenic electron microscopy (cryo-EM) and computational methods. We propose solutions to address the challenges with a critical analysis of advances in membrane partitioning, polypharmacology, biased agonism, and biochemical screening of transcriptional modulators. They are fueled by the breakthrough from cryo-EM, chemoinformatics and bioinformatics. The discussion is aimed to shed new light on designing next-generation drugs to treat obesity, diabetes and its complications, with optimal hydrophobicity, higher mode selectivity, multi-targeting and consistent activities between human and rodents.
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Affiliation(s)
- Yibing Wang
- School of Kinesiology, Shanghai University of Sport, Shanghai, 200438, P. R. China.,Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, Shanghai, 200438, P. R. China
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Blanes-Mira C, Fernández-Aguado P, de Andrés-López J, Fernández-Carvajal A, Ferrer-Montiel A, Fernández-Ballester G. Comprehensive Survey of Consensus Docking for High-Throughput Virtual Screening. Molecules 2022; 28:molecules28010175. [PMID: 36615367 PMCID: PMC9821981 DOI: 10.3390/molecules28010175] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 12/28/2022] Open
Abstract
The rapid advances of 3D techniques for the structural determination of proteins and the development of numerous computational methods and strategies have led to identifying highly active compounds in computer drug design. Molecular docking is a method widely used in high-throughput virtual screening campaigns to filter potential ligands targeted to proteins. A great variety of docking programs are currently available, which differ in the algorithms and approaches used to predict the binding mode and the affinity of the ligand. All programs heavily rely on scoring functions to accurately predict ligand binding affinity, and despite differences in performance, none of these docking programs is preferable to the others. To overcome this problem, consensus scoring methods improve the outcome of virtual screening by averaging the rank or score of individual molecules obtained from different docking programs. The successful application of consensus docking in high-throughput virtual screening highlights the need to optimize the predictive power of molecular docking methods.
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