The objective of this present study is to focus on the study to screen for an alternative drug that can block the activity of the angiotensin converting enzyme 2 (ACE2) as a receptor for SARS-CoV-2, potential therapeutic target of the COVID-19 virus using natural compounds (Isothymol, Thymol, Limonene, P-cymene and γ-terpinene) derived from the essential oil of the antiviral and antimicrobial plant (Desf.) Briq. which is located in the occidental Algeria areas. This study reveals that Isothymol, a major component of this plant, gives the best docking scores, compared to, the co-crystallized inhibitor β-D-mannose of the enzyme ACE2, to Captropil drug as good ACE2 inhibitor and to Chloroquine antiviral drug also involved in other mechanisms as inhibition of ACE2 cellular receptor. (ADME), drug-likeness, PASS & P450 site of metabolism prediction, pharmacophore Mapper showed that the compound Isothymol has given a good tests results compared to the β-D-mannose co-crystallized inhibitor, to Captopril and Chloroquine drugs. Also the other natural compounds gave good results. The Molecular Dynamics Simulation study showed good result for the Isotymol- ACE2 docked complex. This study revealed for the first time that Isothymol is a functional inhibitor of angiotensin converting enzyme 2 activity and the components of essential oils can be used as potential inhibitors to the ACE2 receptor of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1763199 | DOI Listing |
PLoS One
January 2025
Immunology and Immunotherapy Division, Center of Molecular Immunology (CIM), Havana, Cuba.
SARS-CoV-2 has continued spreading around the world in recent years since the initial outbreak in 2019, frequently developing into new variants with greater human infectious capacity. SARS-CoV-2 and its mutants use the angiotensin-converting enzyme 2 (ACE2) as a cellular entry receptor, which has triggered several therapeutic strategies against COVID-19 relying on the use of ACE2 recombinant proteins as decoy receptors. In this work, we propose an ACE2 silent Fc fusion protein (ACE2-hFcLALA) as a candidate therapy against COVID-19.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Background: Angiotensin-converting enzyme (ACE) is a validated risk locus for developing late-onset Alzheimer's disease (LOAD). ACE1 controls blood pressure through the renin-angiotensin system (RAS), but it is also present and acts locally in the brain. Hypertension is associated with an increased risk for developing AD, and people taking select RAS-targeting therapeutics have reduced incidence of AD.
View Article and Find Full Text PDFBackground: Seizures, traumatic brain injury (TBI), and dementia increase in prevalence with age. However, the role of seizure and TBI on cognitive impairment risk (CI) is unclear. This study investigated how a diagnosis of seizures and TBI was associated with the progression to CI and assessed the role of medications.
View Article and Find Full Text PDFJ Cell Biochem
January 2025
Bioinformatics Division I Microbiology Division, ICMR-Regional Medical Research Centre, Bhubaneswar, Odisha, India.
B0AT1 (SLC6A19) is a major sodium-coupled neutral amino acid transporter that relies on angiotensin converting enzyme 2 (ACE2) or collectrin for membrane trafficking. Despite its significant role in disorders associated with amino acid metabolism, there is a deficit of comprehensive structure-function understanding of B0AT1 in lipid environment. Herein, we have employed molecular dynamics (MD) simulations to explore the architectural characteristics of B0AT1 in two distinct environments: a simplified POPC bilayer and a complex lipid system replicating the native membrane composition.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Cardiology, Shaanxi Provincial People's Hospital, Xi'an, People's Republic of China.
Purpose: Heart failure (HF) is a clinical syndrome in which structural or functional abnormalities of the heart result in impaired ventricular filling or ejection capacity. In order to improve the adaptability of models to different patient populations and data situations. This study aims to develop predictive models for HF risk using six machine learning algorithms, providing valuable insights into the early assessment and recognition of HF by clinical features.
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