Can natural detergent properties of bile acids be used beneficially in tackling coronavirus disease-19?

In vitro co-culture of Clostridium scindens with primary human colonic epithelium protects the epithelium against Staphylococcus aureus

A complex and dynamic network of interactions exists between human gastrointestinal epithelium and intestinal microbiota. Therefore, comprehending intestinal microbe-epithelial cell interactions is critical for the understanding and treatment of intestinal diseases. Primary human colonic epithelial cells derived from a healthy human donor were co-cultured with Clostridium scindens (C. scindens), a probiotic obligate anaerobe; Staphylococcus aureus (S. aureus), a facultative anaerobe and intestinal pathogen; or both bacterial species in tandem. The co-culture hanging basket platform used for these experiments possessed walls of controlled oxygen (O2) permeability to support the formation of an O2 gradient across the intestinal epithelium using cellular O2 consumption, resulting in an anaerobic luminal and aerobic basal compartment. Both the colonic epithelial cells and C. scindens remained viable over 48 h during co-culture. In contrast, co-culture with S. aureus elicited significant damage to colonic epithelial cells within 24 h. To explore the influence of the intestinal pathogen on the epithelium in the presence of the probiotic bacteria, colonic epithelial cells were inoculated sequentially with the two bacterial species. Under these conditions, C. scindens was capable of repressing the production of S. aureus enterotoxin. Surprisingly, although C. scindens converted cholic acid to secondary bile acids in the luminal medium, the growth of S. aureus was not significantly inhibited. Nevertheless, this combination of probiotic and pathogenic bacteria was found to benefit the survival of the colonic epithelial cells compared with co-culture of the epithelial cells with S. aureus alone. This platform thus provides an easy-to-use and low-cost tool to study the interaction between intestinal bacteria and colonic cells in vitro to better understand the interplay of intestinal microbiota with human colonic epithelium.

Trends in the Diversification of the Detergentome

Detergents are amphiphilic molecules that serve as enabling steps for today's world applications. The increasing diversity of the detergentome is key to applications enabled by detergent science. Regardless of the application, the optimal design of detergents is determined empirically, which leads to failed preparations, and raising costs. To facilitate project planning, here we review synthesis strategies that drive the diversification of the detergentome. Synthesis strategies relevant for industrial and academic applications include linear, modular, combinatorial, bio-based, and metric-assisted detergent synthesis. Scopes and limitations of individual synthesis strategies in context with industrial product development and academic research are discussed. Furthermore, when designing detergents, the selection of molecular building blocks, i. e., head, linker, tail, is as important as the employed synthesis strategy. To facilitate the design of safe-to-use and tailor-made detergents, we provide an overview of established head, linker, and tail groups and highlight selected scopes and limitations for applications. It becomes apparent that most recent contributions to the increasing chemical diversity of detergent building blocks originate from the development of detergents for membrane protein studies. The overview of synthesis strategies and molecular blocks will bring us closer to the ability to predictably design and synthesize optimal detergents for challenging future applications.

Synthesis and in silico study of chenodeoxycholic acid and its analogues as an alternative inhibitor of spike glycoprotein of SARS-CoV-2

COVID-19, caused by SARS-CoV-2, is a viral infection that has generated one of the most significant health problems in the world. Spike glycoprotein is a crucial enzyme in viral replication and transcription mediation. There are reports in the literature on using bile acid in the fight against this virus through in vitro tests. This work presents the synthesis of nine chenodeoxycholic acid derivatives (1-9), which were prepared by oxidation, acetylation, formylation, and esterification reactions, and the analogs 6-9 have not yet been reported in the literature and the possibility of conducting an in silico study of bile acid derivatives as a therapeutic alternative to combat the virus using glycoprotein as a macromolecular target. As a result, five compounds (1, 6-9) possessed favorable competitive interactions with the lowest energies compared to the native ligand (BLA), and the highlighted compound 9 got the best scores. At the same time, analog 1 presented the best ADME filter result. Molecular dynamics also simulated these compounds to verify their stability within the active protein site to seek new therapeutic propositions to fight against the pandemic. Physical and spectroscopic data have fully characterized all the compounds.Communicated by Ramaswamy H. Sarma.

Virtual repurposing of ursodeoxycholate and chenodeoxycholate as lead candidates against SARS-Cov2-Envelope protein: A molecular dynamics investigation

Drug repurposing is an apt choice to combat the currently prevailing global threat of COVID-19, caused by SARS-Cov2in absence of any specific medication/vaccine. The present work employs state of art computational methods like homology modelling, molecular docking and molecular dynamics simulations to evaluate the potential of two widely used surfactant drugs namely chenodeoxycholate(CDC) and ursodeoxycholate (UDC), to bind to the envelope protein of SARS-Cov2(SARS-Cov2-E).The monomeric unit of SARS-Cov2-E was modelled from a close homologue (>90% sequence identity) and a pentameric assembly was modelled using symmetric docking, followed by energy minimization in a DPPC membrane environment. The minimized structure was used to generate best scoring SARS-Cov2-E-CDC/UDC complexes through blind docking. These complexes were subjected to 230 ns molecular dynamics simulations in triplicates in a DPPC membrane environment. Comparative analyses of structural properties and molecular interaction profiles from the MD trajectories revealed that, both CDC and UDC could stably bind to SARS-Cov2-E through H-bonds, water-bridges and hydrophobic contacts with the transmembrane-channelresidues.T30 was observed to be a key residue for CDC/UDC binding. CDC/UDC binding affected the H-bonding pattern between adjacent monomeric chains, slackening the compact transmembrane region of SARS-Cov2-E. Additionally, the polar functional groups of CDC/UDC facilitated entry of a large number of water molecules into the channel. These observations suggest CDC/UDC as potential candidates to hinder the survival of SARS-Cov2 by disrupting the structure of SARS-Cov2-E and facilitating the entry of solvents/polar inhibitors inside the viral cell.Communicated by Ramaswamy H. Sarma.

Surfactant-based therapy against COVID-19: A review

The coronavirus disease 2019 (COVID-19) has led to serious health and economic damage to all over the world, and it still remains unstoppable. The SARS-CoV-2, by using its S-glycoprotein, binds with an angiotensin-converting enzyme 2 receptor, mostly present in alveolar epithelial type II cells. Eventually pulmonary surfactant depletion occurs. The pulmonary surfactant is necessary for maintaining the natural immunity as well as the surface tension reduction within the lung alveoli during the expiration. Its insufficiency results in the reduction of blood oxygenation, poor pulmonary regeneration, lung fibrosis, and finally the respiratory system collapses. Exogenous surfactants have previously shown great promise in the treatment of infant respiratory distress syndrome, and they may also aid in the healing of damaged alveolar cells and the prevention of respiratory failure. Surfactant based therapy has been advised for the prevention of COVID-19, and the trials have begun around the world. Furthermore, greater research on the timing, dose, and the distribution of surfactant to the COVID-19 patients is required before this technique can be implemented in clinical practice.

Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets

COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high throughput COVID-19 datasets, including proteomic, metabolomic and transcriptomic measurements. Pathway analysis of the selected features was also performed. Analysis of a combined proteomic and metabolomic dataset led to 10 equivalent signatures of two features each, with AUC 0.840 (CI 0.723-0.941) in discriminating severe from non-severe COVID-19 patients. A transcriptomic dataset led to two equivalent signatures of eight features each, with AUC 0.914 (CI 0.865-0.955) in identifying COVID-19 patients from those with a different acute respiratory illness. Another transcriptomic dataset led to two equivalent signatures of nine features each, with AUC 0.967 (CI 0.899-0.996) in identifying COVID-19 patients from virus-free individuals. Signature predictive performance remained high upon validation. Multiple new features emerged and pathway analysis revealed biological relevance by implication in Viral mRNA Translation, Interferon gamma signaling and Innate Immune System pathways. In conclusion, AutoML analysis led to multiple biosignatures of high predictive performance, with reduced features and large choice of alternative predictors. These favorable characteristics are eminent for development of cost-effective assays to contribute to better disease management.