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Ogwu MC, Malík M, Tlustoš P, Patočka J. The psychostimulant drug, fenethylline (captagon): Health risks, addiction and the global impact of illicit trade. DRUG AND ALCOHOL DEPENDENCE REPORTS 2025; 15:100323. [PMID: 40151181 PMCID: PMC11946500 DOI: 10.1016/j.dadr.2025.100323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 02/26/2025] [Accepted: 02/26/2025] [Indexed: 03/29/2025]
Abstract
Fenethylline (street name, captagon) is a synthetic amphetamine-type stimulant that is emerging as a significant public health and security concern, particularly in the Middle East. This systematic review synthesizes original research articles, epidemiological studies, systematic reviews, policy analyses, and case reports to provide a comprehensive analysis of fenethylline's health impacts, addiction potential, and dynamics of illicit trade. Initially developed for therapeutic use, fenethylline illicit production and use have escalated, raising concern about its physiological, psychological, and socio-economic impacts. This stimulant profoundly affects the central nervous system, enhancing wakefulness, concentration, and physical stamina while inducing euphoria. These effects come at the cost of serious adverse health outcomes, particularly with prolonged or heavy use, including cardiovascular complications, neurological damage, and addiction. The dependence-forming nature of captagon contributes to escalating substance use disorders, impacting healthcare systems. Beyond its biomedical implications, fenethylline trafficking has become a global issue, with supply chains deeply intertwined with politically unstable regions where illicit economies thrive. The geopolitical dimensions of captagon's trade amplify its global security threat, influencing international relations and regional stability. This paper underscores the urgent need for systematic data collection and coordinated efforts to regulate illicit fenethylline production and distribution. Strategies such as improved surveillance, public health interventions, and international cooperation are essential to mitigate its escalating risks. Addressing this issue requires a multidisciplinary approach, integrating public health, law enforcement, and policy development to curb its impact on global health and security.
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Affiliation(s)
- Matthew Chidozie Ogwu
- Goodnight Family Department of Sustainable Development, Appalachian State University, 212 Living Learning Center, 305 Bodenheimer Drive, Boone, NC 28608, United States
| | - Matěj Malík
- Department of Agroenvironmental Chemistry and Plant Nutrition, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, Suchdol, Praha 165 00, Czech Republic
| | - Pavel Tlustoš
- Department of Agroenvironmental Chemistry and Plant Nutrition, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamýcká 129, Suchdol, Praha 165 00, Czech Republic
| | - Jiří Patočka
- Department of Radiology, Toxicology and Civil Protection, Faculty of Health and Social Studies, University of South Bohemia, J. Boreckého 1167/27, České Budějovice 370 11, Czech Republic
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2
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Shehata SA, Abd El-Fadeal NM, Fattah IOA, Hagras AM, Mostafa EMA, Abdel-Daim MM, Abdelshakour MA, Kolieb E, Abdelmaogood AKK, Rabee YM, Abdelrahman KM. Synergistic cardiotoxic effects of captagon and azithromycin in rat via oxidative stress, apoptosis and upregulation of the PI3K/AKT/NF-kB pathway. Toxicol Lett 2025; 408:77-94. [PMID: 40246213 DOI: 10.1016/j.toxlet.2025.04.002] [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: 12/03/2024] [Revised: 03/05/2025] [Accepted: 04/14/2025] [Indexed: 04/19/2025]
Abstract
Fenethylline (Captagon) is a blend of amphetamine and theophylline that functions as a stimulant, while azithromycin (AZ) is a commonly prescribed macrolide antibiotic. The co-usage of illicit substances and therapeutic drugs can result in substantial health risk especially cardiotoxicity. This study aimed to assess cardiotoxicity effects of Captagon (Capta) and Azithromycin/Captagon interaction in adult male rats. Forty-two animals were assigned into 6 groups: Group I (Control) and group II (AZ (30 mg/kg/day) starting from the 14th day of the experiment and for 2 weeks. Group III (Capta10 mg/kg/day), group IV (Capta20 mg/kg/day), group V (AZ+Capta10) and group VI (AZ+Capta20) daily 28 days. Electrocardiogram (ECG), cardiac enzymes, oxidative stress markers, inflammatory genes expression, histopathological and immunohistochemical changes were assessed. Administration of AZ and Capta alone or in combination cause cardiotoxicity. This was indicated by elevated LDH and CTNI levels, ECG changes as increased HR, prolonged QT interval and elevated ST segment accompanied by cardiac histopathological changes. There was a significant reduction in antioxidants SOD, GSH, TAC, and catalase, alongside a significant rise in oxidative stress MDA and NO. Significant rise of ERK, TNF-α, NF-ҡB, PI3K/AKT, Il-1β and IL-6, in both the Capta20 and AZ+Capta groups in dose dependent manner. The Coadministration of AZ and Capta20 produced intense immunoexpression of caspase-3 and BAX and wide areas of negative reactivity for Bcl-2. Coadministration of AZ and Capta induced cardiotoxicity through oxidative stress, inflammation, and apoptosis pathways. It is important to educate healthcare providers and patients about the potential harmful interactions.
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Affiliation(s)
- Shaimaa A Shehata
- Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Noha M Abd El-Fadeal
- Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt; Biochemistry Department, Ibn Sina National College for Medical Studies, Jeddah 22421, Saudi Arabia; Oncology Diagnostic Unit, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Islam Omar Abdel Fattah
- Department of Human Anatomy and Embryology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Abeer M Hagras
- Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Enas M A Mostafa
- Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Mohamed M Abdel-Daim
- Department of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College, P.O. Box 6231, Jeddah 21442, Saudi Arabia; Pharmacology Department, Faculty of Veterinary Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Mohamed A Abdelshakour
- Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Sohag University, Sohag 82524, Egypt.
| | - Eman Kolieb
- Physiology Department, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Asmaa K K Abdelmaogood
- Department of Clinical and Chemical pathology، Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
| | - Youssef M Rabee
- Department of Cardiology، Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt
| | - Khadiga M Abdelrahman
- Department of Forensic Medicine and Clinical Toxicology, Faculty of Medicine, Suez Canal University, Ismailia 41522, Egypt.
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Sun ZY, Liang T, Zhang Y, Hou G, Chu X, Hou JZ, Li W, Xie XQ, Feng Z. Structural insight into CD20/CD3-bispecific antibodies by molecular modeling. Comput Biol Med 2025; 185:109497. [PMID: 39674067 DOI: 10.1016/j.compbiomed.2024.109497] [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: 07/30/2024] [Revised: 11/09/2024] [Accepted: 11/26/2024] [Indexed: 12/16/2024]
Abstract
Non-Hodgkin's Lymphoma (NHL) remains a significant challenge in hematology, with chemotherapy and radiation therapy as conventional treatment options, albeit with limitations such as adverse effects. Immunotherapy, particularly bispecific antibodies (BsAbs) T cell engagers (TCEs), has emerged as a promising approach. Despite their potential, TCEs pose challenges, including adverse events like cytokine release syndrome. Understanding the structural details of TCEs and their interactions with target proteins is crucial for optimizing their therapeutic efficacy and toxicity. In this study, we further developed our protocol MCCS-Docker for protein-protein interactions and applied it to investigate the structural intricacies of CD3 interactions with therapeutic antibodies such as OKT3, UCHT1, Mosunetuzumab, Odronextumab, Glofitamab, and Epcoritamab using computational modeling techniques. Our analysis not only approved the effectiveness of our updated MCCS-Docker protocol but also revealed detailed binding interactions between the BsAbs and CD3, elucidating key residues of Tyrosine and Asparagine in the antibodies involved in the binding interface. Molecular dynamics simulations validated the stability of these interactions over time, confirming the reliability of the binding poses generated from docking studies. Overall, our study offered a novel method to predict critical residues in protein-protein interactions and enhanced the understanding of the structural determinants governing BsAb interactions with target proteins, offering valuable insights for designing and optimizing immunotherapeutic agents for NHL and related hematologic malignancies.
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Affiliation(s)
- Ze-Yu Sun
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - Tianjian Liang
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - Yiyang Zhang
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - GanQian Hou
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - Xiaojie Chu
- Department of Medicine, Center for Antibody Therapeutics, Division of Infectious Diseases, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Jing-Zhou Hou
- University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, PA15232, United States.
| | - Wei Li
- Department of Medicine, Center for Antibody Therapeutics, Division of Infectious Diseases, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
| | - Zhiwei Feng
- Department of Pharmaceutical Sciences, Computational Chemical Genomics Screening Center, and Pharmacometrics & System Pharmacology PharmacoAnalytics, School of Pharmacy, National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, PA 15261, United States.
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Byrska B, Stanaszek R. Chemical composition of Ecstasy tablets seized in Poland between 2005 and 2020. Forensic Toxicol 2025; 43:22-32. [PMID: 39017813 DOI: 10.1007/s11419-024-00691-3] [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: 12/11/2023] [Accepted: 05/30/2024] [Indexed: 07/18/2024]
Abstract
PURPOSE The most commonly associated substance found in Ecstasy tablets is MDMA (3,4-methylenedioxymethamphetamine). In our study, we showed how the composition of psychoactive ingredients in Ecstasy tablets seized on the drug market in Poland has changed in the years 2005-2020. METHODS The study material consisted of nearly 20,000 single Ecstasy tablets seized by representatives of law enforcement (the police, prosecutors) from 2005 to 2020 and analysed by the Institute of Forensic Research, Krakow, Poland. The analysis of the tablets was carried out by gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography with diode array detection (HPLC-DAD) and ultra-high-performance liquid chromatography with photodiode array detection (UHPLC-PDA). RESULTS Currently, new types of MDMA tablets are introduced onto the market, available in various colours and shapes. Our study showed that tablets sold on the street as Ecstasy have variable purity and sometimes contain little or no MDMA. The mean content of MDMA in one tablet seized in 2005-2011 decreased from 90 to 50 mg. In 2013, Ecstasy tablets with a very high MDMA content (average 195 mg per tablet) appeared on the market, but in the next 2 years, the MDMA content decreased again. From 2016, the average MDMA content began to rise again, ranging from 60 to 280 mg. CONCLUSION Tablets sold as Ecstasy also contained completely different psychoactive substances, including new psychoactive substances (NPS) (found in almost 20% of all examined tablets sold as Ecstasy) belonging to different chemical groups or their dangerous combinations (i.e. phenylethylamines, piperazines, tryptamines, cathinones, arylalkylamines, arylcyclohexylamines and piperidines). Such a large variety of psychoactive substances in Ecstasy tablets is associated with a high risk for users unaware of their composition.
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Affiliation(s)
- Bogumiła Byrska
- Professor Jan Sehn Institute of Forensic Research, Krakow, Poland.
| | - Roman Stanaszek
- Professor Jan Sehn Institute of Forensic Research, Krakow, Poland
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Fong S, Carollo A, Rossato A, Prevete E, Esposito G, Corazza O. Captagon: A comprehensive bibliometric analysis (1962-2024) of its global impact, health and mortality risks. Saudi Pharm J 2024; 32:102188. [PMID: 39512334 PMCID: PMC11541700 DOI: 10.1016/j.jsps.2024.102188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 10/14/2024] [Indexed: 11/15/2024] Open
Abstract
Captagon is a synthetic stimulant combining amphetamine and theophylline. Initially introduced in 1961 as a treatment for hyperactivity, depression, and narcolepsy, Captagon was later classified as a Schedule 1 controlled substance due to its addictive and hallucinogenic properties. Despite its global prohibition in 1986, the trade of counterfeit products is widespread, especially in south-east Europe and far-east Asia, with its production being on the rise in Middle Eastern regions. This paper presents a quantitative data-driven bibliometric analysis of the existing literature on Captagon up to July 2024. It aims to delineate the structure and development of knowledge surrounding the substance, including key contributing countries, authors, prominent sources, and recurring thematic keywords. The quantitative and data-driven results were then used to guide the narrative discussion on Captagon. Findings indicate that current research predominantly focuses on Captagon's use and impact in conflict zones, often exploring its interaction with other substances used by civilians and militias. Results also show a growing trend in Captagon research, with Saudi Arabia, Jordan, and Iraq emerging as main contributors to the literature. Despite the attention in specific regions, a considerable gap remains in understanding the mechanisms of action of Captagon (particularly regarding its metabolism, toxicology, mortality risk), and in developing protocols for its discontinuation. Additionally, the drug's inconsistent composition requires further analyses to better predict risks and establish effective management strategies. Addressing these gaps will be crucial for the development of novel interventions and policies to mitigate the adverse effects of Captagon and improve public health systems worldwide.
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Affiliation(s)
- Seraphina Fong
- Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
| | - Alessandro Carollo
- Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
| | - Andrea Rossato
- Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
| | - Elisabeth Prevete
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Gianluca Esposito
- Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
| | - Ornella Corazza
- Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom
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Abdulfattah S, Ahmad AR, Kitaneh R, Alsharaydeh T, Almudallal F, Alzoubi R, Abbadi R, Haddad TA, Wazaify M, Alkayed Z, Bani Mustafa R, Tetrault JM. Nonmedical Use of Stimulants Among Students in Jordan: A Nationwide Study. J Addict Med 2024; 18:443-450. [PMID: 38587298 DOI: 10.1097/adm.0000000000001308] [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: 04/09/2024]
Abstract
OBJECTIVES Nonmedical use (NMU) of stimulants is an increasingly common phenomenon worldwide. Motivated by enhancing academic performance, peer pressure, and seeking pleasure, students in the Middle East are thought to be a high-risk population. This is especially important in times when the political instability in the region facilitates the production and trafficking of such substances. This study aimed to unveil the burden of NMU of stimulants and examine associated correlates among senior high school and university students in Jordan. METHODS We describe a cross-sectional study of senior high school and university students in Jordan assessing NMU of stimulants. Data were collected between January and April of 2022 through a survey, which was distributed online leading to a google forms page. The survey queried sociodemographic characteristics, history of NMU of stimulants, use of other illicit substances, attitudes toward NMU of stimulants, as well as a mental health assessment. RESULTS A total of 8739 students completed the survey (mean age of 20.40 ± 2.45 years), of which 5.1% reported a lifetime NMU of stimulants. Fenethylline (Captagon) was the most widely reported stimulant (2.6%). Living in the southern region, being diagnosed with a personality disorder, and using concomitant illicit substances were associated with the NMU of stimulants. CONCLUSIONS The NMU of CNS stimulants, especially fenethylline, is prevalent in Jordan. More surveillance ought to be heeded toward the southern borders of Jordan. Students who use stimulants for academic reasons must be made aware of the potential consequences of the NMU of stimulants.
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Affiliation(s)
- Sadan Abdulfattah
- From the Jordan University Hospital, Amman, Jordan (SA, ARA, TAH, FA, RA, RA, TH); Department of Psychiatry, Yale School of Medicine, New Haven, CT (RK); Clinical Neuroscience Research Unit, Connecticut Mental Health Center, New Haven, CT (RK); Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, University of Jordan, Amman, Jordan (MW); Faculty of Pharmacy, University of Helsinki, Helsinki, Finland (MW); Department of Internal Medicine, School of Medicine, University of Jordan, Amman, Jordan (ZA, RB); and Program in Addiction Medicine, Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT (JMT)
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Captagon-induced Brugada phenocopy: A report of two cases. J Electrocardiol 2023; 79:21-23. [PMID: 36913784 DOI: 10.1016/j.jelectrocard.2023.03.002] [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: 12/09/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 03/09/2023]
Abstract
Brugada phenocopies (BrP) represent electrocardiogram changes identical to those of true congenital Brugada syndrome but are induced by reversible clinical conditions. Previous cases have been reported in patients following recreational drug use. This report presents two cases of type 1B BrP associated with Fenethylline abuse, a recreational drug known by its trade name, Captagon.
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Korehpaz-Mashhadi F, Ahmadzadeh H, Rashidlamir A, Saffari N. Changes in metabolites level in internet-addicted adolescents through exercise. J Bodyw Mov Ther 2022; 31:1-6. [DOI: 10.1016/j.jbmt.2022.02.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 11/07/2021] [Accepted: 02/04/2022] [Indexed: 11/26/2022]
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Mohaddes Ardabili H, Akbari A, Rafei P, Butner J, Khan R, Khazaal Y, Arab AZ, Qazizada MR, Al-Ansari B, Baldacchino AM. Tramadol, captagon and khat use in the Eastern Mediterranean Region: opening Pandora's box. BJPsych Int 2021; 19:58-62. [PMID: 36287793 PMCID: PMC9540563 DOI: 10.1192/bji.2021.53] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 08/05/2021] [Accepted: 08/15/2021] [Indexed: 12/12/2022] Open
Abstract
As defined by the World Health Organization, the Eastern Mediterranean Region (EMR), given its special geopolitical situation and internal/external conflicts, faces an increase in illegal activities such as drug production and trafficking, highlighting the need for a comprehensive understanding of the substance use situation. On the basis of a review of published papers between 2015 and 2021 we briefly review substance use in the EMR with special focus on the emerging drugs pertinent to this region, namely tramadol, captagon and khat.
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The Psychonauts' Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity. Pharmaceuticals (Basel) 2021; 14:ph14080720. [PMID: 34451817 PMCID: PMC8398354 DOI: 10.3390/ph14080720] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 12/28/2022] Open
Abstract
Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activity relationship/QSAR and Molecular Docking) were used to analyse DBZDs identified online by an automated web crawler (NPSfinder®) and to predict their possible activity/affinity on the gamma-aminobutyric acid A receptors (GABA-ARs). The computational software MOE was used to calculate 2D QSAR models, perform docking studies on crystallised GABA-A receptors (6HUO, 6HUP) and generate pharmacophore queries from the docking conformational results. 101 DBZDs were identified online by NPSfinder®. The validated QSAR model predicted high biological activity values for 41% of these DBDZs. These predictions were supported by the docking studies (good binding affinity) and the pharmacophore modelling confirmed the importance of the presence and location of hydrophobic and polar functions identified by QSAR. This study confirms once again the importance of web-based analysis in the assessment of drug scenarios (DBZDs), and how computational models could be used to acquire fast and reliable information on biological activity for index novel DBZDs, as preliminary data for further investigations.
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Chen M, Feng Z, Wang S, Lin W, Xie XQ. MCCS, a novel characterization method for protein-ligand complex. Brief Bioinform 2021; 22:bbaa239. [PMID: 33051641 PMCID: PMC8293830 DOI: 10.1093/bib/bbaa239] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 08/23/2020] [Accepted: 08/27/2020] [Indexed: 01/11/2023] Open
Abstract
Delineating the fingerprint or feature vector of a receptor/protein will facilitate the structural and biological studies, as well as the rational design and development of drugs with high affinities and selectivity. However, protein is complicated by its different functional regions that can bind to some of its protein partner(s), substrate(s), orthosteric ligand(s) or allosteric modulator(s) where cogent methods like molecular fingerprints do not work well. We here elaborate a scoring-function-based computing protocol Molecular Complex Characterizing System to help characterize the binding feature of protein-ligand complexes. Based on the reported receptor-ligand interactions, we first quantitate the energy contribution of each individual residue which may be an alternative of MD-based energy decomposition. We then construct a vector for the energy contribution to represent the pattern of the ligand recognition at a receptor and qualitatively analyze the matching level with other receptors. Finally, the energy contribution vector is explored for extensive use in similarity and clustering. The present work provides a new approach to cluster proteins, a perspective counterpart for determining the protein characteristics in the binding, and an advanced screening technique where molecular docking is applicable.
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12
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Cheng J, Chen M, Wang S, Liang T, Chen H, Chen CJ, Feng Z, Xie XQ. Binding Characterization of Agonists and Antagonists by MCCS: A Case Study from Adenosine A 2A Receptor. ACS Chem Neurosci 2021; 12:1606-1620. [PMID: 33856784 DOI: 10.1021/acschemneuro.1c00082] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Characterizing the structural basis of ligand recognition of adenosine A2A receptor (AA2AR) will facilitate its rational design and development of small molecules with high affinity and selectivity, as well as optimal therapeutic effects for pain, cancers, drug abuse disorders, etc. In the present work, we applied our reported algorithm, molecular complex characterizing system (MCCS), to characterize the binding features of AA2AR based on its reported 3D structures of protein-ligand complexes. First, we compared the binding score to the reported experimental binding affinities of each compound. Then, we calculated an output example of residue energy contribution using MCCS and compared the results with data obtained from MM/GBSA. The consistency in results indicated that MCCS is a powerful, fast, and accurate method. Sequentially, using a receptor-ligand data set of 57 crystallized structures of AA2ARs, we characterized the binding features of the binding pockets in AA2AR, summarized the key residues that distinguish antagonist from agonist, produced heatmaps of residue energy contribution for clustering various statuses of AA2ARs, explored the selectivity between AA2AR and AA1AR, etc. All the information provided new insights into the protein features of AA2AR and will facilitate its rational drug design.
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Affiliation(s)
- Jin Cheng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.,Department of Pharmacy, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu 224005, China
| | - Maozi Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Siyi Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Tianjian Liang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Hui Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Chih-Jung Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Zhiwei Feng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, and National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
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13
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Liang T, Chen H, Yuan J, Jiang C, Hao Y, Wang Y, Feng Z, Xie XQ. IsAb: a computational protocol for antibody design. Brief Bioinform 2021; 22:6238584. [PMID: 33876197 DOI: 10.1093/bib/bbab143] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 02/24/2021] [Accepted: 03/23/2021] [Indexed: 12/15/2022] Open
Abstract
The design of therapeutic antibodies has attracted a large amount of attention over the years. Antibodies are widely used to treat many diseases due to their high efficiency and low risk of adverse events. However, the experimental methods of antibody design are time-consuming and expensive. Although computational antibody design techniques have had significant advances in the past years, there are still some challenges that need to be solved, such as the flexibility of antigen structure, the lack of antibody structural data and the absence of standard antibody design protocol. In the present work, we elaborated on an in silico antibody design protocol for users to easily perform computer-aided antibody design. First, the Rosetta web server will be applied to generate the 3D structure of query antibodies if there is no structural information available. Then, two-step docking will be used to identify the binding pose of an antibody-antigen complex when the binding information is unknown. ClusPro is the first method to be used to conduct the global docking, and SnugDock is applied for the local docking. Sequentially, based on the predicted binding poses, in silico alanine scanning will be used to predict the potential hotspots (or key residues). Finally, computational affinity maturation protocol will be used to modify the structure of antibodies to theoretically increase their affinity and stability, which will be further validated by the bioassays in the future. As a proof of concept, we redesigned antibody D44.1 and compared it with previously reported data in order to validate IsAb protocol. To further illustrate our proposed protocol, we used cemiplimab antibody, a PD-1 checkpoint inhibitor, as an example to showcase a step-by-step tutorial.
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Affiliation(s)
- Tianjian Liang
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Hui Chen
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Jiayi Yuan
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Chen Jiang
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Yixuan Hao
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Yuanqiang Wang
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Pittsburgh, PA 15261, USA
| | - Zhiwei Feng
- School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Xiang-Qun Xie
- Computational Drug Abuse Research and Computational Chemogenomics Screening Center at the University of Pittsburgh, Pittsburgh, PA 15261, USA
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Feng Z, Liang T, Wang S, Chen M, Hou T, Zhao J, Chen H, Zhou Y, Xie XQ. Binding Characterization of GPCRs-Modulator by Molecular Complex Characterizing System (MCCS). ACS Chem Neurosci 2020; 11:3333-3345. [PMID: 32941011 PMCID: PMC10063373 DOI: 10.1021/acschemneuro.0c00457] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Increasing attention has been devoted to allosteric modulators as the preferred therapeutic agents for their colossal advantages such as higher selectivity, fewer side effects, and lower toxicity since they bind at allosteric sites that are topographically distinct from the classic orthosteric sites. However, the allosteric binding pockets are not conserved and there are no cogent methods to comprehensively characterize the features of allosteric sites with the binding of modulators. To overcome this limitation, our lab has developed a novel algorithm that can quantitatively characterize the receptor-ligand binding feature named Molecular Complex Characterizing System (MCCS). To illustrate the methodology and application of MCCS, we take G protein coupled receptors (GPCRs) as an example. First, we summarized and analyzed the reported allosteric binding pockets of class A GPCRs using MCCS. Sequentially, a systematic study was conducted between cannabinoid receptor type 1 (CB1) and its allosteric modulators, where we used MCCS to analyze the residue energy contribution and the interaction pattern. Finally, we validated the predicted allosteric binding site in CB2 via MCCS in combination with molecular dynamics (MD) simulation. Our results demonstrate that the MCCS program is advantageous in recapitulating the allosteric regulation pattern of class A GPCRs of the reported pockets as well as in predicting potential allosteric binding pockets. This MCCS program can serve as a valuable tool for the discovery of small-molecule allosteric modulators for class A GPCRs.
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Affiliation(s)
- Zhiwei Feng
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Tianjian Liang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Siyi Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Maozi Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Tianling Hou
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Jack Zhao
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Hui Chen
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Yuehan Zhou
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research; Drug Discovery Institute; Departments of Computational Biology and Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
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Taylor DL, Gough A, Schurdak ME, Vernetti L, Chennubhotla CS, Lefever D, Pei F, Faeder JR, Lezon TR, Stern AM, Bahar I. Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology. Handb Exp Pharmacol 2019; 260:327-367. [PMID: 31201557 PMCID: PMC6911651 DOI: 10.1007/164_2019_239] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.
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Affiliation(s)
- D Lansing Taylor
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA.
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Albert Gough
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mark E Schurdak
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lawrence Vernetti
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chakra S Chennubhotla
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daniel Lefever
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
| | - Fen Pei
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - James R Faeder
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Timothy R Lezon
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew M Stern
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ivet Bahar
- University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
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