(1) Background: Enterococcus faecium DO is an environmental microbe, which is a mesophilic, facultative, Gram-positive, and multiple habitat microorganism. Enterococcus faecium DO is responsible for many diseases in human. The fight against infectious diseases is confronted by the development of multiple drug resistance in E. faecium. The focus of this research work is to identify a novel compound against this pathogen by using bioinformatics tools and technology. (2) Methods: We screened the proteome (accession No. PRJNA55353) information from the genome database of the National Centre for Biotechnology Information (NCBI) and suggested a potential drug target. I-TASSER was used to predict the three-dimensional structure of the protein, and the structure was optimized and minimized by different tools. PubChem and ChEBI were used to retrieve the inhibitors. Pharmacophore modeling and virtual screening were performed to identify novel compounds. Binding interactions of compounds with target protein were checked using LigPlot. pkCSM, SwissADME, and ProTox-II were used for adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. (3) Results: Novel selected compounds have improved absorption and have better ADMET properties. Based on our results, the chemically identified inhibitor ZINC48942 targeted the receptor that can inhibit the activity of infection in E. faecium. This research work will be beneficial for the scientific community and could aid in the design of a new drug against E. faecium infections. (4) Conclusions: It was observed that novel compounds are potential inhibitors with more efficacy and fewer side effects. This research work will help researchers in testing and identification of these chemicals useful against E. faecium.
Analysis has been done to investigate the heat generation/absorption effects in a steady flow of non-Newtonian nanofluid over a surface which is stretching linearly in its own plane. An upper convected Maxwell model (UCM) has been utilized as the non-Newtonian fluid model in view of the fact that it can predict relaxation time phenomenon which the Newtonian model cannot. Behavior of the relaxations phenomenon has been presented in terms of Deborah number. Transport phenomenon with convective cooling process has been analyzed. Brownian motion “Db” and thermophoresis effects “Dt” occur in the transport equations. The momentum, energy and nanoparticle concentration profiles are examined with respect to the involved rheological parameters namely the Deborah number, source/sink parameter, the Brownian motion parameters, thermophoresis parameter and Biot number. Both numerical and analytic solutions are presented and found in nice agreement. Comparison with the published data is also made to ensure the validity. Stream lines for Maxwell and Newtonian fluid models are presented in the analysis.
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