<i>In silico</i> study the inhibition of angiotensin converting enzyme 2 receptor of COVID-19 by <i>Ammoides verticillata</i> components harvested from Western Algeria

Abdelli, Imane; Hassani, Faiçal; Brikci, Sohayb Bekkel; Ghalem, Saïd

doi:10.1080/07391102.2020.1763199

Cited by 151 publications

(119 citation statements)

References 42 publications

Supporting

Mentioning

110

Contrasting

Unclassified

Order By: Relevance

“…While, structural composition of domain III mainly consists of alpha-helices (Anand et al, 2005;Yang et al, 2005;Lu et al, 2006;Jin et al, 2020), protease has been characterized as one of the potential drug targets among coronaviruses (Anand et al, 2003). In this sense, many recent studies suggested that the selection of various FDA-approved antiviral compounds may yield promising results against COVID-19 infection (Chang et al, 2016;Chang et al, 2020;Contini, 2020;Gonzalez-Paz et al, 2020;Khan et al, 2020;El ky, 2020a;Islam et al, 2020;Sinha et al, 2020;Wahedi et al, 2020;Kundu et al, 2020;Das et al, 2020;Abdelli et al, 2020 ). Chang et al, 2020 reported that chloroquine, an older antimalarial drug, has ability to inhibit the viral 3CLprotease activity.…”

Section: Introductionmentioning

confidence: 99%

Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches

Kumar

Choudhir

Shukla

et al. 2020

Preprint

View full text Add to dashboard Cite

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel corona virus that causes corona virus disease 2019 (COVID-19). The COVID-19 rapidly spread across the nations with high mortality rate even as very little is known to contain the virus at present. In the current study, we report novel natural metabolites namely, ursolic acid, carvacrol and oleanolic acid as the potential inhibitors against main protease (Mpro) of COVID-19 by using integrated molecular modeling approaches. From a combination of molecular docking and molecular dynamic (MD) simulations, we found three ligands bound to protease during 50 ns of MD simulations. Furthermore, the molecular mechanic/generalized/Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations showed that these chemical molecules have stable and favourable energies causing strong binding with binding site of Mpro protein. All these three molecules, namely, ursolic acid, carvacrol and oleanolic acid, have passed the ADME (Absorption, Distribution, Metabolism, and Excretion) property as well as Lipinski’s rule of five. The study provides a basic foundation and suggests that the three phytochemicals, viz. ursolic acid, carvacrol and oleanolic acid could serve as potential inhibitors in regulating the Mpro protein's function and controlling viral replication.

show abstract

Section: Introductionmentioning

confidence: 99%

Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches

Kumar

Choudhir

Shukla

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Molecular docking study revealed it to form a stable interaction with ACE2 receptor. Based on the results of the study, authors suggested that Ammoides verticillata essential oil components could slow down the spread of infection by blocking the entry of the virus in to the cell [ 97 ].…”

Section: Potential Of Medicinal Plants Against Covid-19mentioning

confidence: 99%

Combating COVID-19: The role of drug repurposing and medicinal plants

Khan

Al-Balushi

2021

Journal of Infection and Public Health

View full text Add to dashboard Cite

Background A novel corona virus-2 disease has spread to 213 countries and territories across the globe. The corona pandemic has claimed more than 548,934 deaths worldwide till the evening of 8 th of July 2020 and the number of confirmed cases is increasing at an alarming rate. Therefore, there is an urgent need to find a treatment or a vaccine for COVID-19 at the earliest. The aim of this mini-review is to give an overview of identified repurposed anti-COVID-19 drugs which are currently under clinical trials. Methods A thorough literature survey was done to retrieve relevant information using various web based search engines such as Google, Google scholar, and various other electronic research databases such as PubMed, Medline, MeSh etc . The findings of the recently published articles, clinical trials, COVID-19 update by World Health Organization etc ., and the opinion of the authors is summarized in this brief review. The antiviral medicinal plants were identified based on their use in Chinese/Indian indigenous systems of medicine, traditional use, published scientific phytochemical studies and/or their effectiveness against upper respiratory infections, severe acute respiratory syndrome (SARS) or Middle East respiratory syndrome (MERS). Results The disease is just over six months old and effective prophylactic or therapeutic agents are yet to be developed for COVID-19. Thus, in the absence of an effective therapy, scientific community has rationally considered the drug repurposing approach for the development of anti COVID-19 drugs. Various studies and clinical trials involving antimalarial drugs, anti-HIV drugs, anti-hepatitis drugs, anti-parasitic drug, anti-inflammatory drugs, the combination of antimalarial and macrolide antibiotic and few other molecules identified through drug repurposing are currently underway to combat COVID-19. Due emphasis is also given to develop novel corona vaccines for the prophylaxis and to identify drugs for adjunct/supportive therapy. Several medicinal plants along with their major phytochemicals exhibiting antiviral activity are identified for further exploration. It is anticipated that these natural products might also play an important role in combating COVID-19. Conclusions Use of drug repurposing strategy to develop anti COVID-19 drugs and exploring antiviral medicinal plants as adjunct or supportive therapy appears to be a viable option. Therefore, it is the need of the hour to work in parallel on different strategies such as genetic engineering, in silico approach, herbal remedies and drug repositioning to achieve the common goal of finding a safe and effective treatment for COVID-19 at the earliest.

show abstract

“…Identified first time in Wuhan city of China in late December 2019 (Aanouz et al, 2020;Elfiky & Azzam, 2020;Elmezayen et al, 2020;Enayatkhani et al, 2020;Fausto et al, 2020;Ghosh et al, 2020;Muralidharan et al, 2020;Phulen et al, 2020;Rajib et al, 2020;Rothan & Byrareddy, 2020;Rowan & Laffey, 2020;Salman et al, 2020;Sourav et al, 2020;Umesh et al, 2020), Covid19 is a respiratory disease that is caused by the new coronavirus SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) 2019 (Abdelli et al, 2020;Rakesh et al, 2020;Rameez et al, 2020;World Health Organization, 2020). Covid19 is the name given by the World Health Organization (WHO) on 11 February 2020 (World Health Organization, 2020).…”

Section: Introductionmentioning

confidence: 99%

Using X-ray images and deep learning for automated detection of coronavirus disease

Asnaoui

Youness

2020

Journal of Biomolecular Structure and Dynamics

294

239

View full text Add to dashboard Cite

Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classification system as a speedy elective finding choice to forestall COVID-19 spreading among individuals. Medical images analysis is one of the most promising research areas, it provides facilities for diagnosis and making decisions of a number of diseases such as Coronavirus. This paper conducts a comparative study of the use of the recent deep learning models (VGG16, VGG19, DenseNet201, Inception_ResNet_V2, Inception_V3, Resnet50, and MobileNet_V2) to deal with detection and classification of coronavirus pneumonia. The experiments were conducted using chest X-ray & CT dataset of 6087 images (2780 images of bacterial pneumonia, 1493 of coronavirus, 231 of Covid19, and 1583 normal) and confusion matrices are used to evaluate model performances. Results found out that the use of inception_Resnet_V2 and Densnet201 provide better results compared to other models used in this work (92.18% accuracy for Inception-ResNetV2 and 88.09% accuracy for Densnet201). ARTICLE HISTORY

show abstract

In silico study the inhibition of angiotensin converting enzyme 2 receptor of COVID-19 by Ammoides verticillata components harvested from Western Algeria

Cited by 151 publications

References 42 publications

Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches

Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches

Combating COVID-19: The role of drug repurposing and medicinal plants

Using X-ray images and deep learning for automated detection of coronavirus disease

Contact Info

Product

Resources

About