Causes of mortality from COVID-19 include respiratory failure, heart failure, and sepsis/multiorgan failure. TLR4 is an innate immune receptor on the cell surface that recognizes pathogen-associated molecular patterns (PAMPs) including viral proteins and triggers the production of type I interferons and proinflammatory cytokines to combat infection. It is expressed on both immune cells and tissue-resident cells. ACE2, the reported entry receptor for SARS-CoV-2, is only present on ~1-2% of the cells in the lungs or has a low pulmonary expression, and recently, the spike protein has been proposed to have the strongest protein-protein interaction with TLR4. Here, we review and connect evidence for SARS-CoV-1 and SARS-CoV-2 having direct and indirect binding to TLR4, together with other viral precedents, which when combined shed light on the COVID-19 pathophysiological puzzle. We propose a model in which the SARS-CoV-2 spike glycoprotein binds TLR4 and activates TLR4 signalling to increase cell surface expression of ACE2 facilitating entry. SARS-CoV-2 also destroys the type II alveolar cells that secrete pulmonary surfactants, which normally decrease the air/tissue surface tension and block TLR4 in the lungs thus promoting ARDS and inflammation. Furthermore, SARS-CoV-2-induced myocarditis and multiple-organ injury may be due to TLR4 activation, aberrant TLR4 signalling, and hyperinflammation in COVID-19 patients. Therefore, TLR4 contributes significantly to the pathogenesis of SARS-CoV-2, and its overactivation causes a prolonged or excessive innate immune response. TLR4 appears to be a promising therapeutic target in COVID-19, and since TLR4 antagonists have been previously trialled in sepsis and in other antiviral contexts, we propose the clinical trial testing of TLR4 antagonists in the treatment of severe COVID-19. Also, ongoing clinical trials of pulmonary surfactants in COVID-19 hold promise since they also block TLR4.

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COVID-19 and Toll-Like Receptor 4 (TLR4): SARS-CoV-2 May Bind and Activate TLR4 to Increase ACE2 Expression, Facilitating Entry and Causing Hyperinflammation.

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guerin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in E. coli, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.

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In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology.

Introduction: A novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was reported via nucleic acid identification in December, 2019. Accuracy of SARS-CoV-2 diagnostic assays has emerged as a major barrier to COVID-19 diagnosis, particularly in cases requiring urgent or emergent treatment.Areas covered: In this review, we explore the major reasons for false-positive and false-negative SARS-CoV-2 test results. How clinical characteristics, specific respiratory comorbidities and SARS-CoV-2 vaccination impact on existing diagnostic assays are highlighted. Different COVID-19 management algorithms based on each test and limitations are thoroughly presented.Expert opinion: The diagnostic accuracy and the capacity of every available assay, which need to be interpreted in the light of the background incidence of SARS-CoV-2 infection in the communities in which they are used, are essential in order to minimize the number of falsely tested cases. Automated testing platforms may enhance diagnostic accuracy by minimizing the potential for human error in assays' performance. Prior immunization against SARS-CoV-2 impairs the utility of serologic testing of suspected COVID-19 cases. Future avenues of research to evaluate lung tissue innate immune responses hold promise as a target for research to optimize SARS-CoV-2 and future infections' testing accuracy.

https://www.tandfonline.com/doi/pdf/10.1080/17476348.2021.1917389

False-positive and false-negative COVID-19 cases: respiratory prevention and management strategies, vaccination, and further perspectives.

https://www.mdpi.com/2076-393X/8/3/423/pdf

Vaccine design from the ensemble of surface glycoprotein epitopes of SARS-CoV-2: An immunoinformatics approach

In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives.

Core proteome mediated therapeutic target mining and multi-epitope vaccine design for Helicobacter pylori

Chlamydia trachomatis core genome data mining for promising novel drug targets and chimeric vaccine candidates identification.

Plasmodium falciparum is an obligate intracellular parasite of humans that causes malaria. Falciparum malaria is a major public health threat to human life responsible for high mortality. Currently, the risk of multi-drug resistance of P. falciparum is rapidly increasing. There is a need to address new anti-malarial therapeutics strategies to combat the drug-resistance threat.
 The P. falciparum essential proteins were retrieved from the recently published studies. These proteins were initially scanned against human host and its gut microbiome proteome sets by comparative proteomics analyses. The human host non-homologs essential proteins of P. falciparum were additionally analysed for druggability potential via in silico methods to possibly identify novel therapeutic targets. Finally, the PfAp4AH target was prioritized for pharmacophore modelling based virtual screening and molecular docking analyses to identify potent inhibitors from drug-like compounds databases. The analyses identified six P. falciparum essential and human host non-homolog proteins that follow the key druggability features. These druggable targets have not been catalogued so far in the Drugbank repository. These prioritized proteins seem novel and promising drug targets against P. falciparum due to their key protein–protein interactions features in pathogen-specific biological pathways and to hold appropriate drug-like molecule binding pockets. The pharmacophore features based virtual screening of Pharmit resource predicted a lead compound i.e. MolPort-045–917-542 as a promising inhibitor of PfAp4AH among prioritized targets. The prioritized protein targets may worthy to test in malarial drug discovery programme to overcome the anti-malarial resistance issues. The in-vitro and in-vivo studies might be promising for additional validation of these prioritized lists of drug targets against malaria.

/pdf/analysing-the-essential-proteins-set-of-plasmodium-56310aq6fu.pdf

Fawad Ali

Papers

Vaccine design from the ensemble of surface glycoprotein epitopes of SARS-CoV-2: An immunoinformatics approach

Core proteome mediated therapeutic target mining and multi-epitope vaccine design for Helicobacter pylori

Chlamydia trachomatis core genome data mining for promising novel drug targets and chimeric vaccine candidates identification.

Analysing the essential proteins set of Plasmodium falciparum PF3D7 for novel drug targets identification against malaria.