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1.
Open Forum Infectious Diseases ; 8(SUPPL 1):S354, 2021.
Article in English | EMBASE | ID: covidwho-1746494

ABSTRACT

Background. The outbreak of COVID-19 pandemic in China regarded as a major health/economic hazard. The importance of coming up with mechanisms for preventing or treating COVID-19 has been felt across the world. This work aimed at examining the efficiency of Sitagliptin (SIT) and human immunodeficiency virus type 1 (HIV-1) trans-activator transcription peptide (TAT) against SARS-CoV-2. Methods. SIT-TAT nano-conjugates were prepared according to a full three-factor bi-level (23) factorial design. SIT concentration (mM, X1), TAT concentration (mM, X2), and pH (X3) were selected as the factors. Particle size (nm, Y1) and zeta potential (mV, Y2) were assessed as responses. Characterization of the optimized formula for Fourier-transformed infrared (FTIR) and Transmission electron microscope was carried out. In addition, IC50 in Vero E6 cells, In vitro 3CL-protease inhibition and docking tests were investigated. Results. The prepared complex's formula was as follows 1: 1 SIT: TAT molar ratio, whereas zeta potential and particle size values were at 34.17 mV and 97.19 nm, respectively. This combination did exhibit its antiviral potentiality against SARS-CoV-2 via IC50 values of 9.083 5.415, and 16.14 μM for TAT, SIT-TAT, and SIT, respectively. In addition, the complex SIT-TAT showed a significant (P < 0.001) viral-3CL-protease inhibitory effect (IC50 = 3.959 μM ± 0.011) in comparison to isolated components (IC50 = 10.93 μM ± 0.25) and TAT (IC50 = 8.128 μM ± 0.42). This was further confirmed via in silico study. Molecular docking investigation has shown promising binding affinity of the formula components towards SARS-CoV-2 main protease (3-CL). Conclusion. While offering significant binding interactions with protein's key pocket residues, an optimized formulation of SIT-TAT could guarantee both the enhanced delivery to the target cells and the improved cellular uptake. The presented findings would guarantee further investigations regarding formula optimization against SARS-CoV-2.

2.
Clinical Pharmacology & Therapeutics ; 109:S27-S28, 2021.
Article in English | Web of Science | ID: covidwho-1136823
3.
Clinical Pharmacology & Therapeutics ; 109:S60-S60, 2021.
Article in English | Web of Science | ID: covidwho-1136809
4.
Novel Intell. Lead. Emerg. Sci. Conf., NILES ; : 618-622, 2020.
Article in English | Scopus | ID: covidwho-998659

ABSTRACT

In the current SARS-CoV2 pandemic, identification and differentiation between SARS-COV2 strains are vital to attain efficient therapeutic targeting, drug discovery and vaccination. In this study, we investigate how the viral genetic code mutated locally and what variations is the Egyptian population most susceptible to in comparison with different strains isolated from Asia, Europe and other countries in Africa. Our aim is to evaluate the significance of these variations and whether they constitute a change on the protein level and identify if any of these variations occurred in the conserved domain of the virus. The available Covid-19 complete genome nucleotide sequences on NCBI were gathered and filtered, and representative sequences were selected from each of the mentioned continents to make the population of our sample 1535 sequences. Multiple sequence alignment was conducted for all the 1535 sequences obtained from NCBI. For higher accuracy, we used the MAFFT iterative refinement method. Conserved domain extraction was carried out for all 1535 sequence for mutation evaluation. When the mutations were evaluated, Spike_D614G, NSP12_P323L, NS3_Q57H and N_R203K were found to be the most common amino acid substitutions among the viral isolates from Egypt. All retrieved mutations were processed and analyzed with principal component analysis (PCA). In general, no clear clusters were clustered based on the mutation pattern of different continents, including Africa, Asia, and Europe. However, PCA shows that the African mutation pattern is a partial subset of the complete European mutation pattern. © 2020 IEEE.

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