Carotenoids as potential inhibitors of TNFα in COVID-19 treatment

Tumor necrosis factor-alpha (TNF-α) is a multifunctional pro-inflammatory cytokine, responsible for autoimmune and inflammatory disorders. In COVID-19 patients, increased TNF-α concentration may provoke inflammatory cascade and induce the initiation of cytokine storm that may result in fatal pneumonia and acute respiratory distress syndrome (ADRS). Hence, TNFα is assumed to be a promising drug target against cytokine storm in COVID-19 patients. In the present study, we focused on finding novel small molecules that can directly block TNF-α-hTNFR1 (human TNF receptor 1) interaction. In this regards, TNF-α-inhibiting capacity of natural carotenoids was investigated in terms of blocking TNF-α-hTNFR1 interaction in COVID-19 patients with the help of a combination of in silico approaches, based on virtual screening, molecular docking, and molecular dynamics (MD) simulation. A total of 125 carotenoids were selected out of 1204 natural molecules, based on their pharmacokinetics properties and they all met Lipinski's rule of five. Among them, Sorgomol, Strigol and Orobanchol had the most favorable ΔG with the best ADME (absorption, distribution, metabolism, excretion) properties, and were selected for MD simulation studies, which explored the complex stability and the impact of ligands on protein conformation. Our results showed that Sorgomol formed the most hydrogen bonds, resulting in the highest binding energy with lowest RMSD and RMSF, which made it the most appropriate candidate as TNF-α inhibitor. In conclusion, the present study could serve to expand possibilities to develop new therapeutic small molecules against TNF-α.

Evaluation of model parameters for simulating TiO(2) coated UV reactors

A CFD-based model for simulating TiO(2) coated photocatalytic reactors used in drinking water treatment applications was preliminarily evaluated. The model includes aspects of hydrodynamics, mass transfer, UV-radiation field, and surface chemical reactions. Appropriate models for each of the associated physicochemical phenomena were experimentally or analytically examined. Once defined and evaluated, the individual models were integrated into a CFD-based model for simulating photocatalytic reactor performance, which was experimentally evaluated.

The importance of hydrodynamics in UV advanced oxidation reactors

The flow field of UV reactors was characterised experimentally using particle image velocimetry (PIV) and modelled with computational fluid dynamics (CFD). The reactor flow was integrated with the radiation fluence rate and photolysis kinetics to calculate the overall conversion of photo-reactant components in annular UV reactors with an inlet parallel and perpendicular to the reactor axis. The results indicated that the fluid flow distribution within the reactor volume affects photo-reactor performance.