Adjusting extracellular pH to prevent entry of SARS-CoV-2 into human cells

Structural and pKa Estimation of the Amphipathic HR1 in SARS-CoV-2: Insights from Constant pH MD, Linear vs. Nonlinear Normal Mode Analysis

A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context.

Preclinical efficacy and safety of novel SNAT against SARS-CoV-2 using a hamster model

To address the unprecedented global public health crisis due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we designed and developed a novel antiviral nano-drug, called SNAT (Smart Nano-Enabled Antiviral Therapeutic), comprised of taxoid (Tx)-decorated amino (NH₂)-functionalized near-atomic size positively charged silver nanoparticles (Tx-[NH₂-AgNPs]) that are stable for over 3 years. Using a hamster model, we tested the preclinical efficacy of inhaled SNAT on the body weight, virus titer, and histopathology of lungs in SARS-CoV-2-infected hamsters, including biocompatibility in human lung epithelium and dermal fibroblasts using lactase dehydrogenase (LDH) and malondialdehyde (MDA) assays. Our results showed SNAT could effectively reverse the body weight loss, reduce the virus load in oral swabs, and improve lung health in hamsters. Furthermore, LDH assay showed SNAT is noncytotoxic, and MDA assay demonstrated SNAT to be an antioxidant, potentially quenching lipid peroxidation, in both the human cells. Overall, these promising pilot preclinical findings suggest SNAT as a novel, safer antiviral drug lead against SARS-CoV-2 infection and may find applications as a platform technology against other respiratory viruses of epidemic and pandemic potential.

Extracellular pH, osmolarity, temperature and humidity could discourage SARS-CoV-2 cell docking and propagation via intercellular signaling pathways

The COVID-19 pandemic and its virus variants continue to pose a serious and long-lasting threat worldwide. To combat the pandemic, the world's largest COVID-19 vaccination campaign is currently ongoing. As of July 19th 2021, 26.2% of the world population has received at least one dose of a COVID-19 vaccine (1.04 billion), and one billion has been fully vaccinated, with very high vaccination rates in countries like Israel, Malta, and the UEA. Conversely, only 1% of people in low-income countries have received at least one dose with examples of vaccination frequency as low as 0.07% in the Democratic Republic of Congo. It is thus of paramount importance that more research on alternate methods to counter cell infection and propagation is undertaken that could be implemented in low-income countries. Moreover, an adjunctive therapeutic intervention would help to avoid disease exacerbation in high-rate vaccinated countries too. Based on experimental biochemical evidence on viral cell fusion and propagation, herein we identify (i) extracellular pH (epH), (ii) temperature, and (iii) humidity and osmolarity as critical factors. These factors are here in discussed along with their implications on mucus thick layer, proteases, abundance of sialic acid, vascular permeability and exudate/edema. Heated, humidified air containing sodium bicarbonate has long been used in the treatment of certain diseases, and here we argue that warm inhalation of sodium bicarbonate might successfully target these endpoints. Although we highlight the molecular/cellular basis and the signalling pathways to support this intervention, we underscore the need for clinical investigations to encourage further research and clinical trials. In addition, we think that such an approach is also important in light of the high mutation rate of this virus originating from a rapid increase.

Biomarkers of severe COVID-19 pneumonia on admission using data-mining powered by common laboratory blood tests-datasets

In the epidemiological COVID-19 research, artificial intelligence is a unique approach to make predictions about disease severity to manage COVID-19 patients. A limitation of artificial intelligence is, however, the high risk of bias. We investigated the skill of data mining and machine learning, two advanced forms of artificial intelligence, to predict severe COVID-19 pneumonia based on routine laboratory tests. A sample of 4009 COVID-19 patients was divided into Severe (PaO₂< 60 mmHg, 489 cases) and Non-Severe (PaO₂ ≥ 60 mmHg, 3520 cases) groups according to blood hypoxemia on admission and their laboratory datasets analyzed by the R software and WEKA workbench. After curation, data were processed for the selection of the most influential features including hemogram, pCO₂, blood acid-base balance, prothrombin time, inflammation biomarkers, and glucose. The best fit of variables was successfully confirmed by either the Multilayer Perceptron, a feedforward neural network algorithm that performed machine recognition of severe COVID-19 with 96.5% precision, or by the C4.5 software, a supervised learning algorithm based on an objective-predefined variable (severity) that generated a decision tree with 89.4% precision. Finally, a complex bivariate Pearson's correlation matrix combined with advanced hierarchical clustering (dendrograms) were conducted for knowledge discovery. The hidden structure of the datasets revealed shift patterns related to the development of COVID-19-induced pneumonia that involved the lymphocyte-to-C-reactive protein and leukocyte-to-C-protein ratios, neutrophil %, pH and pCO₂. The data mining approaches to the hematological fluctuations associated with severe COVID-19 pneumonia could not only anticipate adverse clinical outcomes, but also reveal putative therapeutic targets.

The use of negative oxygen ion clusters [O2-(H2O)n] and bicarbonate ions [HCO3-] as the supportive treatment of COVID-19 infections: A possibility

The COVID-19 or novel coronavirus SARS-CoV-2 pandemic is challenging worldwide healthcare system and severely affecting global economy. Furious efforts to end the pandemic including prevention of spread of SARS-CoV-2, use of antiviral drugs, symptomatic treatments and vaccination are underway. But there are no effective treatments available to save the dying patient in stage 2 (pulmonary) and stage 3 (hyperinflammation) of the infection. The detailed genetic and phenotypical analysis of SARS-CoV-2 revealed that the spike protein (S1) has increased positive charges (compared to SARS-CoV) on them and are responsible for attachment to human angiotensin-converting enzyme 2 (ACE2) receptor and infection by the virus. In addition, it was also reported that the inflammation in the tissue rendered the lung environment more acidic supporting the fusion of SARS-CoV-2 with the cells. We hypothesize that the intermittent use of the oxygen ionizer generating negative oxygen ion clusters [O₂^-(H₂O)_n] and sodium bicarbonate nebulizer (generating HCO₃^-); when connected to ventilator inlet or oxygen concentrator will neutralize the spike protein of the virus in respiratory tract and lungs and change the lung environment to neutral/alkaline condition respectively facilitating improved oxygen pressure in blood. These physical changes can effectively reduce the viral burden and help the patient recover from the infection faster.