scholarly journals An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-CoV-2

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Renu Jakhar ◽  
S. K. Gakhar
Keyword(s):  
Envelope Protein ◽  
Peptide Vaccine ◽  
Binding Energies ◽  
In Vivo Studies ◽  
T Cell Epitopes ◽  
Immune Epitope ◽  
The World ◽  
Immune Epitope Database

COVID-19 is a new viral emergent disease caused by a novel strain of coronavirus. This virus has caused a huge problem in the world as millions of people are affected by this disease. We aimed at designing a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system. The envelope protein sequence of SARS-CoV-2 has been retrieved from the NCBI database. The bioinformatics analysis was carried out by using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. The predicted HTL and CTL epitopes were docked with HLA alleles and binding energies were evaluated. The allergenicity of predicted epitopes was analyzed, the conservancy analysis was performed, and the population coverage was determined throughout the world. Some overlapped CTL, HTL, and B-cell epitopes were suggested to become a universal candidate for peptide-based vaccine against COVID-19. This vaccine peptide could simultaneously elicit humoral and cell-mediated immune responses. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate.

scholarly journals Screening marine algae metabolites as high-affinity inhibitors of SARS-CoV-2 main protease (3CLpro): an in silico analysis to identify novel drug candidates to combat COVID-19 pandemic

2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Ghazala Muteeb ◽  
Adil Alshoaibi ◽  
Mohammad Aatif ◽  
Md. Tabish Rehman ◽  
M. Zuhaib Qayyum
Keyword(s):  
Hydrophobic Interactions ◽  
In Silico Analysis ◽  
Salt Bridge ◽  
Competitive Inhibitor ◽  
Binding Energies ◽  
Dynamics Simulation ◽  
In Vivo Studies ◽  
Energy Calculation

AbstractThe recent dissemination of SARS-CoV-2 from Wuhan city to all over the world has created a pandemic. COVID-19 has cost many human lives and created an enormous economic burden. Although many drugs/vaccines are in different stages of clinical trials, still none is clinically available. We have screened a marine seaweed database (1110 compounds) against 3CLpro of SARS-CoV-2 using computational approaches. High throughput virtual screening was performed on compounds, and 86 of them with docking score <  − 5.000 kcal mol−1 were subjected to standard-precision docking. Based on binding energies (< − 6.000 kcal mol−1), 9 compounds were further shortlisted and subjected to extra-precision docking. Free energy calculation by Prime-MM/GBSA suggested RC002, GA004, and GA006 as the most potent inhibitors of 3CLpro. An analysis of ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties of RC002, GA004, and GA006 indicated that only RC002 (callophysin A, from red alga Callophycus oppositifolius) passed Lipinski’s, Veber’s, PAINS and Brenk’s filters and displayed drug-like and lead-like properties. Analysis of 3CLpro-callophysin A complex revealed the involvement of salt bridge, hydrogen bonds, and hydrophobic interactions. callophysin A interacted with the catalytic residues (His41 and Cys145) of 3CLpro; hence it may act as a mechanism-based competitive inhibitor. Docking energy and docking affinity of callophysin A towards 3CLpro was − 8.776 kcal mol−1 and 2.73 × 106 M−1, respectively. Molecular dynamics simulation confirmed the stability of the 3CLpro-callophysin A complex. The findings of this study may serve as the basis for further validation by in vitro and in vivo studies.

scholarly journals Persistent, bioaccumulative, and toxic properties of liquid crystal monomers and their detection in indoor residential dust

2019 ◽  
Vol 116 (52) ◽  
pp. 26450-26458 ◽  
Author(s):  
Huijun Su ◽  
Shaobo Shi ◽  
Ming Zhu ◽  
Doug Crump ◽  
Robert J. Letcher ◽  
...  
Keyword(s):  
Liquid Crystal ◽  
Chemical Properties ◽  
Liquid Crystal Displays ◽  
In Vivo Studies ◽  
Indoor Environments ◽  
Initial Screening ◽  
Environmental Matrices ◽  
The World

Liquid crystal monomers (LCMs) are used widely in liquid crystal displays (LCDs), which are dramatically changing the world due to the provision of convenient communication. However, there are essentially no published reports on the fate and/or effects of LCMs in the environment. Of 362 currently produced LCMs, 87 were identified as persistent and bioaccumulative (P&B) chemicals, which indicated that these chemicals would exhibit resistance to degradation and exhibit mobility after entering the environment. Following exposure to mixtures of LCM collected from 6 LCD devices, significant modulation of 5 genes,CYP1A4,PDK4,FGF19,LBFABP, andTHRSP, was observed in vitro. Modulation of expressions of mRNAs coding for these genes has frequently been reported for toxic (T) persistent organic pollutants (POPs). In LCM mixtures, 33 individual LCMs were identified by use of mass spectrometry and screened for in 53 samples of dust from indoor environments. LCMs were detectable in 47% of analyzed samples, and 17 of the 33 LCMs were detectable in at least 1 sample of dust. Based on chemical properties, including P&B&T of LCMs and their ubiquitous detection in dust samples, the initial screening information suggests a need for studies to determine status and trends in concentrations of LCMs in various environmental matrices as well as tissues of humans and wildlife. There is also a need for more comprehensive in vivo studies to determine toxic effects and potencies of LCMs during chronic, sublethal exposures.

scholarly journals THE POTENTIAL OF ROBUSTA COFFEE (COFFEA CANEPHORA) AS A COLORECTAL CANCER THERAPY MODALITY: AN IN SILICO STUDY

2021 ◽  
pp. 83-87
Author(s):  
DESSY AGUSTINI ◽  
LEO VERNADESLY ◽  
DELVIANA ◽  
THEODORUS
Keyword(s):  
Colorectal Cancer ◽  
In Silico ◽  
Hydrophobic Interactions ◽  
Binding Energies ◽  
In Vivo Studies ◽  
Discovery Studio ◽  
Robusta Coffee ◽  
In Silico Study

Objectives: This research aims to determine the efficacy of compounds in robusta coffee against colorectal cancer through the inhibition of the T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) receptor. Methods: This in silico study has been conducted in computing platform from June to August 2021. The selected test compounds would go through the Lipinski rule screening through the SwissADME website and the compounds that met these regulations would be docked to the TIGIT protein using AutoDock Tools and AutoDock Vina. The interactions with the highest binding energies were visualized using BIOVIA Discovery Studio 2020. The test compounds then underwent a toxicity profile analysis on the admetSAR 2.0 website. Results: All test compounds complied with the Lipinski rule. The molecular docking results showed the highest binding energy in kahweol and cafestol (−8.1 kcal/mol) compared to OMC (−7.9 kcal/mol), chlorogenic acid (−7.8 kcal/mol), caffeic acid (−6.3 kcal/mol), caffeine (−6.1 kcal/mol), trigonelline (−5.3 kcal/mol), HMF (−5.1 kcal/mol), furfuryl alcohol (−4.4 kcal/mol), and 5-fluorouracil as the comparator drug (−5.3 kcal/mol). Kahweol, cafestol, and 5-fluorouracil revealed the hydrophobic interactions and hydrogen bonds with amino acid residues in TIGIT. Kahweol and cafestol unveiled minimal toxicity prediction Conclusion: Kahweol and cafestol demonstrated the best results in inhibiting the TIGIT protein which played a role in colorectal cancer. In vitro and in vivo studies are needed to strengthen the findings of this research.

scholarly journals The Role of Glycemic Variability in Cardiovascular Disorders

2021 ◽  
Vol 22 (16) ◽  
pp. 8393
Author(s):  
Valentina Alfieri ◽  
Veronika A. Myasoedova ◽  
Maria Cristina Vinci ◽  
Maurizio Rondinelli ◽  
Paola Songia ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Glycemic Variability ◽  
In Vivo Studies ◽  
Biological Mechanisms ◽  
Prognostic Accuracy ◽  
Disease Outcomes ◽  
The World

Diabetes mellitus (DM) is one of the most common and costly disorders that affect humans around the world. Recently, clinicians and scientists have focused their studies on the effects of glycemic variability (GV), which is especially associated with cardiovascular diseases. In healthy subjects, glycemia is a very stable parameter, while in poorly controlled DM patients, it oscillates greatly throughout the day and between days. Clinically, GV could be measured by different parameters, but there are no guidelines on standardized assessment. Nonetheless, DM patients with high GV experience worse cardiovascular disease outcomes. In vitro and in vivo studies showed that high GV causes several detrimental effects, such as increased oxidative stress, inflammation, and apoptosis linked to endothelial dysfunction. However, the evidence that treating GV is beneficial is still scanty. Clinical trials aiming to improve the diagnostic and prognostic accuracy of GV measurements correlated with cardiovascular outcomes are needed. The present review aims to evaluate the clinical link between high GV and cardiovascular diseases, taking into account the underlined biological mechanisms. A clear view of this challenge may be useful to standardize the clinical evaluation and to better identify treatments and strategies to counteract this DM aspect.

scholarly journals Azithromycin and Hydroxychloroquine combination: The future pharmacotherapy of COVID-19

2020 ◽  
Vol 7 (2) ◽  
pp. 54-57
Author(s):  
Ananya Shukla ◽  
Pornasha Mohabeer ◽  
Abhishek Kashyap ◽  
Jared Robinson ◽  
Indrajit Banerjee
Keyword(s):  
Macrolide Antibiotic ◽  
Qt Prolongation ◽  
In Vivo Studies ◽  
Specific Drug ◽  
Limited Data ◽  
The World ◽  
The Future ◽  
Future Drug

Background: In response to the urgency of increasing death toll due to COVID-19, caused due to SARS CoV-2, various drugs are under clinical trial, as there is no specific drug for its treatment. In an international survey that was recently conducted in which about 7500 physicians participated from all over the world considered that Hydroxychloroquine and Azithromycin were among the most effective ones for the pharmacotherapy of COVID-19. Azithromycin is a macrolide antibiotic whose mechanism of action against COVID-19 is still unknown, but various theories have been postulated. In vitro and in vivo studies have been conducted; however, their results are quite contradictory. Azithromycin is said to increase the risk of QT prolongation in elderly patients and when given in combination with Hydroxychloroquine can increase the risk of Torsade’s de pointes. Therefore, caution has to be paid before prescribing Azithromycin. Conclusion: The mass loss of human lives is regrettable and needs to be stopped as soon as possible. Azithromycin could be the future drug for COVID-19, but such limited data is insufficient to support the drug's safety or efficacy and needs to be reconsidered.

scholarly journals An Immunoinformatics Study to Predict Epitopes in the Envelope Protein of SARS-COV-2

2020 ◽  
Author(s):  
Renu Jakhar ◽  
S.K Gakhar
Keyword(s):  
B Cell ◽  
Envelope Protein ◽  
Peptide Vaccine ◽  
Cell Epitope ◽  
T Helper ◽  
Ctl Epitopes ◽  
The People ◽  
B Cell Epitope

AbstractCOVID-19 is a new viral emergent human disease caused by a novel strain of Coronavirus. This virus has caused a huge problem in the world as millions of the people are affected with this disease in the entire world. We aimed to design a peptide vaccine for COVID-19 particularly for the envelope protein using computational methods to predict epitopes inducing the immune system and can be used later to create a new peptide vaccine that could replace conventional vaccines. A total of available 370 sequences of SARS-CoV-2 were retrieved from NCBI for bioinformatics analysis using Immune Epitope Data Base (IEDB) to predict B and T cells epitopes. Then we docked the best predicted CTL epitopes with HLA alleles. CTL cell epitopes namely interacted with MHC class I alleles and we suggested them to become universal peptides based vaccine against COVID-19. Potentially continuous B cell epitopes were predicted using tools from IEDB. The Allergenicity of predicted epitopes was analyzed by AllerTOP tool and the coverage was determined throughout the worlds. We found these CTL epitopes to be T helper epitopes also. The B cell epitope, SRVKNL and T cell epitope, FLAFVVFLL were suggested to become a universal candidate for peptide-based vaccine against COVID-19. We hope to confirm our findings by adding complementary steps of both in vitro and in vivo studies to support this new universal predicted candidate.

scholarly journals COVID-19 TEDAVİSİNE YÖNELİK GÜNCEL FARMAKOLOJİK YAKLAŞIMLAR

2021 ◽  
Author(s):  
Ezgi Eroğlu ◽  
Hakan Balcı ◽  
Veysel Baskın ◽  
Zuhal Aktuna
Keyword(s):  
Specific Treatment ◽  
In Vivo Studies ◽  
Wholesale Market ◽  
Randomized Controlled ◽  
Therapeutic Drugs ◽  
The World ◽  
Current Outbreak ◽  
Almost All

The current outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred in the wholesale market in Wuhan, China in the last months of 2019 and spread to almost all countries in the world. Although there is currently no specific treatment for COVID-19, certain agents are used worldwide, based on in vitro, in vivo studies, and randomized controlled trials. In this review, brief information about these drugs used for the treatment of COVID-19, the results of the conducted studies and the possible adverse effects of the drugs are summarized. We hope that this review will provide an impression of the most current therapeutic drugs used to prevent, control and treat COVID-19 patients until the approval of vaccines and specific drugs targeting SARS-CoV-2. Key Words: COVID-19, SARS CoV-2, pharmacotherapeutics

scholarly journals In Vitro and In Vivo Studies for Assessing the Immune Response and Protection-Inducing Ability Conferred by Fasciola hepatica-Derived Synthetic Peptides Containing B- and T-Cell Epitopes

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e105323 ◽  
Author(s):  
Jose Rojas-Caraballo ◽  
Julio López-Abán ◽  
Luis Pérez del Villar ◽  
Carolina Vizcaíno ◽  
Belén Vicente ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cell ◽  
Synthetic Peptides ◽  
Fasciola Hepatica ◽  
In Vivo Studies ◽  
T Cell Epitopes

scholarly journals Computational Analysis for Prediction of Multi Epitopes Vaccine against Blue Tongue Virus Serotype 4 from VP5 and VP7 Proteins

2020 ◽  
Vol 5 (2) ◽  
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Transmitted Disease ◽  
In Vivo Studies ◽  
T Cell Epitopes ◽  
Binding Prediction ◽  
Virus Serotype ◽  
Immunogenic Proteins

Blue Tongue Disease (BTD) is a non-contagious insect transmitted disease of ruminants caused by double stranded RNA virus. This study aimed to predict an effective multi-epitopes vaccine against BTD from VP5 and VP7 as immunogenic proteins using immunoinformatic tools. The VP5 and VP7 proteins sequences were retrieved from GenBank of National Center for Biotechnology Information (NCBI). The sequences of each protein were aligned for conservancy using Bioedit software. Immune Epitope Database (IEDB) analysis resources were used to predict B and T cell epitopes. The proposed MHC-1 epitopes of both proteins were further subjected to molecular docking to show minimum binding energy of each epitopes. In our results, two epitopes (235-SEEV-235 and 85-PDPLSP-90) from VP5 and two epitopes (79-PISPDYTQ-86 and 297-PIFPPN-302) from VP7 were proposed as B cell epitopes since they were shown to be linear, surface accessible and antigenic epitopes. For T cells, MHC-1 binding prediction tools showed multiple epitopes strongly interacted with BoLA alleles from both VP5 and VP7. Among them three epitopes, (257-KLKKVINAL-265, 487-QMHILRGPL-495 and 350-VMMRFKIPR-358) fromVP5 protein and four epitopes (86-QHMATIGVL-94, 315-TLADVYTVL-323, 17-TLQEARIVL-25 and 10-TVMRACATL-18) from VP7 protein interacted with the highest number of alleles and demonstrated best binding affinity to MHC-1 alleles. Thus were proposed as a vaccine candidate from VP5 and VP7 proteins. All the epitopes from VP5 and VP7 that interacted with MHC-1 alleles when subjected to molecular docking against the sheep b_microglobulin alleles demonstrated biologically significant higher binding affinity which expressed by their lower global and attractive energy. In conclusion, eleven epitopes were predicted as promising vaccine candidates against BTD from the VP5 and VP7 immunogenic proteins. These epitopes require to be validated experimentally through in vitro and in vivo studies.

scholarly journals Epitope‐based peptide vaccine design against spike protein (S) of novel coronavirus (2019-nCoV): an immunoinformatics approach

2020 ◽  
Author(s):  
Eman Ali Awadelkareem ◽  
Nisreen Osman Mohammed ◽  
Bothina Bakor Mohammed Gaafar ◽  
Zahra - Abdelmagid ◽  
Sumaia AwadElkariem Ali
Keyword(s):  
Peptide Vaccine ◽  
Cell Epitope ◽  
Protein S ◽  
Cross Reactivity ◽  
Protein Characterization ◽  
Spike Protein ◽  
T Cell Epitopes ◽  
S Protein

Abstract Background Recently the global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated a significant need on identifying drugs or vaccines to prevent or reduce clinical infection of Coronavirus disease – 2019 (COVID-19). In this study, immuno-informatics tools were utilized to design a potential multi-epitopes vaccine against SARS-CoV-2 spike S protein. Structural analysis for SARS-CoV-2 spike S protein was also conducted. Method: SARS-CoV-2 spike S protein sequences were retrieved from the GeneBank of National Central Biotechnology Information (NCBI). Immune Epitope Database (IEDB) tools were used to predict B and T cell epitopes, to evaluate their allergenicity, toxicity and cross- reactivity and to calculate population coverage. Protparm sever was applied to determine protein characterization of spike protein and predicted epitopes. Molecular docking for the proposed MHCI epitopes were also achieved against Tall like Receptor (TLR8) receptors and HLA-B7 allele. Result Immuno-informatics analysis of S protein using IEDB identified only one B cell epitope 1054QSAPH1058 as linear, surface and antigenic. Although 1054QSAPH1058 was estimated as non-allergic and non-toxic, it showed protein instability. Moreover, around 45 discontinuous epitopes were also recognized as different exposed surface area. In MHCI methods, six conserved stable and safe epitopes (898FAMQMAYRF906, 258WTAGAAAYY266 and 2FVFLVLLPL10, 202 KIYSKHTPI210, 712IAIPTNFTI720 and 1060VVFLHVTYV1068) were identified. These epitopes showed strong interaction when docked with TLR8 and HLA-B7 allele especially 1060VVFLHVTYV1068 and 2FVFLVLLPL10 epitopes. Three epitopes were also predicted (898FAMQMAYRF906, 888FGAGAALQI896 and 342FNATRFASV350) using MHCII methods. Furthermore, the potential multi-epitopes were acquired by assessing allergenicity, toxicity and cross-reactivity to prevent autoimmunity. Conclusion The multi-epitopes vaccine was predicted based on Bioinformatics tools that may provide reliable results in a shorter time and at a lower cost. However, further in vivo and in vitro studies are required to validate their effectiveness.

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