A Multistage In Silico Study of Natural Potential Inhibitors Targeting SARS-CoV-2 Main Protease

Among a group of 310 natural antiviral natural metabolites, our team identified three compounds as the most potent natural inhibitors against the SARS-CoV-2 main protease (PDB ID: 5R84), M^pro. The identified compounds are sattazolin and caprolactin A and B. A validated multistage in silico study was conducted using several techniques. First, the molecular structures of the selected metabolites were compared with that of GWS, the co-crystallized ligand of M^pro, in a structural similarity study. The aim of this study was to determine the thirty most similar metabolites (10%) that may bind to the M^pro similar to GWS. Then, molecular docking against M^pro and pharmacophore studies led to the choice of five metabolites that exhibited good binding modes against the M^pro and good fit values against the generated pharmacophore model. Among them, three metabolites were chosen according to ADMET studies. The most promising M^pro inhibitor was determined by toxicity and DFT studies to be caprolactin A (292). Finally, molecular dynamics (MD) simulation studies were performed for caprolactin A to confirm the obtained results and understand the thermodynamic characteristics of the binding. It is hoped that the accomplished results could represent a positive step in the battle against COVID-19 through further in vitro and in vivo studies on the selected compounds.     

EEG rhythm/channel selection for fuzzy rule-based alertness state characterization

The aim of the paper is to automatically select the optimal EEG rhythm/channel combinations capable of classifying human alertness states. Four alertness states were considered, namely ‘engaged’, ‘calm’, ‘drowsy’ and ‘asleep’. The features used in the automatic selection are the energies associated with the conventional rhythms, \(\delta , \theta , \alpha , \beta\) and \(\gamma\), extracted from overlapping windows of the different EEG channels. The selection process consists of two stages. In the first stage, the optimal brain regions, represented by sets of EEG channels, are selected using a simple search technique based on support vector machine (SVM), extreme learning machine (ELM) and LDA classifiers. In the second stage, a fuzzy rule-based alertness classification system (FRBACS) is used to identify, from the previously selected EEG channels, the optimal features and their supports. The IF–THEN rules used in FRBACS are constructed using a novel differential evolution-based search algorithm particularly designed for this task. Each alertness state is represented by a set of IF–THEN rules whose antecedent parts contain EEG rhythm/channel combination. The selected spatio-frequency features were found to be good indicators of the different alertness states, as judged by the classification performance of the FRBACS that was found to be comparable to those of the SVM, ELM and LDA classifiers. Moreover, the proposed classification system has the advantage of revealing simple and easy to interpret decision rules associated with each of the alertness states.

     

Investigation of wall mass transfer characteristics downstream of an orifice

Numerical simulations were performed to determine the effect of Reynolds number and orifice to pipe diameter ratio (d_o/d) on the wall mass transfer rate downstream of an orifice. The simulations were performed for d_o/d of 0.475 for Reynolds number up to 70,000. The effect of d_o/d was determined by performing simulations at a Reynolds number of 70,000 for d_o/d of 0.375, 0.475 and 0.575. The momentum and mass transport equations were solved using the Low Reynolds Number (LRN) K-? turbulence model. The Sherwood number (Sh) profile downstream of the orifice was in relatively good agreement with existing experimental results. The Sh increases sharply downstream of the orifice, reaching a maximum within 1–2 diameters downstream of the orifice, before relaxing back to the fully developed pipe flow value. The Sh number well downstream of the orifice was in good agreement with results for fully developed pipe flow estimated from the correlation of Berger and Hau (1977). The peak Sh numbers from the simulations were higher than that predicted from Tagg et al. (1979) and Coney (1980).     

Electronic fingerprints of DNA bases on graphene

We calculate the electronic local density of states (LDOS) of DNA nucleotide bases (A,C,G,T), deposited on graphene. We observe significant base-dependent features in the LDOS in an energy range within a few electronvolts of the Fermi level. These features can serve as electronic fingerprints for the identification of individual bases in scanning tunneling spectroscopy (STS) experiments that perform image and site dependent spectroscopy on biomolecules. Thus the fingerprints of DNA-graphene hybrid structures may provide an alternative route to DNA sequencing using STS.     

Analysis of a novel metal hydride cycle for simultaneous heating and cooling

Out of the many promising applications of metal hydrides, refrigeration, heat pumping and heat transformation are important. In order to achieve improved performance, a novel three-alloy cycle is proposed in which, for heat input at an intermediate temperature, heat outputs at high temperature and also at warm temperature are obtained in addition to refrigeration. The performance of this cycle using the alloys LaNi_4.6Sn_0.4, LaNi_4.7Al_0.3 and MmNi_4.5Al_0.5 is studied based on thermodynamics and reaction kinetics. Coefficients of performance, half-cycle times and specific alloy outputs are evaluated.     

GPU fuzzy c-means algorithm implementations: performance analysis on medical image segmentation

Multimedia Tools and Applications - Image segmentation in the medical imagery such as MRI, is an essential step to the sensitive analysis of human tissues lesions with the objective to improve the...     

Stress-Induced Lattice Imperfections: the Principal Motive in Enhancing some Physico-Chemical and Electrical Properties of some Quartz Varieties

Silicon - Chemical reactivity, grindability and zeta potential have been measured and correlated for three variably deformed quartz varieties from three different areas. Results show that there is...     

Targeting a polyketide synthase gene for Aspergillus carbonarius quantification and ochratoxin A assessment in grapes using real-time PCR

Aspergillus carbonarius is an ochratoxin producing fungus that has been considered to be responsible of the ochratoxin A (OTA) contamination in grapes and wine. In order to monitor and quantify A. carbonarius, a specific primer pair Ac12RL_OTAF/Ac12RL_OTAR has been designed from the acyltransferase (AT) domain of the polyketide synthase sequence Ac12RL3 to amplify 141 bp PCR product. Among the mycotoxigenic fungi tested, only A. carbonarius gave a positive result. This specific primer pair was also successfully employed in real-time PCR conjugated with SYBR Green I dye for the direct quantification of this fungus in grape samples. A positive correlation (R(2)=0.81) was found between A. carbonarius DNA content and OTA concentration in 72 grape samples, allowing for the estimation of the potential risk from OTA contamination. Consequently, this work offers a quick alternative to conventional methods of OTA quantification and mycological detection and quantification of A. carbonarius in grapes.     

Investigation of the catalytic activity of LaBO3 (B = Ni, Co, Fe or Mn) prepared by the microwave-assisted method for hydrogen evolution in acidic medium

LaBO₃ (B = Ni, Co, Fe and Mn) were prepared by microwave-assisted citrate method. The electrocatalytic activity toward hydrogen evolution reaction (HER) was investigated. XRD characterization showed that pure perovskite crystals were indeed formed. SEM images showed that changing the type of the B-site metal ion affected the morphology of the prepared perovskites. The influence of the type of B-cation on the catalytic activity toward hydrogen evolution was studied and the order of the electrocatalytic activity was LaFeO₃ > LaCoO₃ > LaNiO₃ > LaMnO₃, that was related to the calculated values of the activation energy 51.61, 45.37, 41.15 and 55.05 kJ mol⁻¹ for LaBO₃ (B = Ni, Co, Fe and Mn), respectively. The reaction order and the reaction mechanism for all the prepared perovskites were identified. In addition, the effect of the partial substitution at the B-site in LaNi_{1 − x}Co_xO₃ was also studied. It was found that among ternary perovskites, the catalytic activity of LaNiO₃ decreased by increasing the fraction of doped-Co.