A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.

Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past few years, but with the decentralization and globalization of efforts and knowledge, a successful vaccine-based control strategy was efficiently designed and applied worldwide. On the other hand, excused confusion and hesitation have widely impacted public health. This paper aims to reduce COVID-19 vaccine hesitancy taking into consideration the patient's medical history. The dataset used in this study is the Vaccine Adverse Event Reporting System (VAERS) dataset which was created as a corporation between the Food and Drug Administration (FDA) and Centers for Disease Control and Prevention (CDC) to gather reported side effects that may be caused by PFIEZER, JANSSEN, and MODERNA vaccines. In this paper, a Deep Learning (DL) model has been developed to identify the relationship between a certain type of COVID-19 vaccine (i.e. PFIEZER, JANSSEN, and MODERNA) and the adverse reactions that may occur in vaccinated patients. The adverse reactions under study are the recovery condition, possibility to be hospitalized, and death status. In the first phase of the proposed model, the dataset has been pre-proceesed, while in the second phase, the Pigeon swarm optimization algorithm is used to optimally select the most promising features that affect the performance of the proposed model. The patient's status after vaccination dataset is grouped into three target classes (Death, Hospitalized, and Recovered). In the third phase, Recurrent Neural Network (RNN) is implemented for both each vaccine type and each target class. The results show that the proposed model gives the highest accuracy scores which are 96.031% for the Death target class in the case of PFIEZER vaccination. While in JANSSEN vaccination, the Hospitalized target class has shown the highest performance with an accuracy of 94.7%. Finally, the model has the best performance for the Recovered target class in MODERNA vaccination with an accuracy of 97.794%. Based on the accuracy and the Wilcoxon Signed Rank test, we can conclude that the proposed model is promising for identifying the relationship between the side effects of COVID-19 vaccines and the patient's status after vaccination. The study displayed that certain side effects were increased in patients according to the type of COVID-19 vaccines. Side effects related to CNS and hemopoietic systems demonstrated high values in all studied COVID-19 vaccines. In the frame of precision medicine, these findings can support the medical staff to select the best COVID-19 vaccine based on the medical history of the patient.

Design, Synthesis and In Vitro Evaluation of Spirooxindole-Based Phenylsulfonyl Moiety as a Candidate Anti-SAR-CoV-2 and MERS-CoV-2 with the Implementation of Combination Studies.

The search for an effective anti-viral to inhibit COVID-19 is a challenge for the specialized scientific research community. This work investigated the anti-coronavirus activity for spirooxindole-based phenylsulfone cycloadducts in a single and combination protocols. The newly designed anti-SARS-CoV-2 therapeutics spirooxindoles synthesized by [3 + 2] cycloaddition reactions represent an efficient approach. One-pot multicomponent reactions between phenyl vinyl sulfone, substituted isatins, and amines afforded highly stereoselective anti-SARS-CoV-2 therapeutics spirooxindoles with three stereogenic centers. Herein, the newly synthesized spirooxindoles were assessed individually against the highly pathogenic human coronaviruses and proved to be highly potent and safer. Interestingly, the synergistic effect by combining the potent, tested spirooxindoles resulted in an improved antiviral activity as well as better host-cell safety. Compounds 4i and 4d represented the most potent activity against MERS-CoV with IC50 values of 11 and 23 µM, respectively. Both compounds 4c and 4e showed equipotent activity with the best IC50 against SARS-CoV-2 with values of 17 and 18 µM, respectively, then compounds 4d and 4k with IC50 values of 24 and 27 µM, respectively. Then, our attention oriented to perform a combination protocol as anti-SARS-CoV-2 for the best compounds with a different binding mode and accompanied with different pharmacophores. Combination of compound 4k with 4c and combination of compounds 4k with 4i proved to be more active and safer. Compounds 4k with 4i displayed IC50 = 3.275 µM and half maximal cytotoxic-concentration CC50 = 11832 µM. MD simulation of the most potential compounds as well as in silico ADMET properties were investigated. This study highlights the potential drug-like properties of spirooxindoles as a cocktail anti-coronavirus protocol.

Lipid polymer hybrid nanocarriers as a combinatory platform for different anti-SARS-CoV-2 drugs supported by computational studies† † Electronic supplementary information (ESI) available. See DOI: 10.1039/d1ra04576h

The COVID-19 pandemic caused by SARS-CoV-2 has demonstrated the potential of emergent pathogens to severely damage public health and global economies. As a consequence of the pandemic, millions of people have been forced into self-isolation, which has negatively affected the global economy. More efforts are needed to find new innovative approaches that could fundamentally change our understanding and management of this disaster. Herein, lipid polymer hybrid nanoparticles (LPH NPs) were utilized as a platform for the delivery of azithromycin or niclosamide in combination with piroxicam. The obtained systems were successfully loaded with both azithromycin and piroxicam (LPHAzi–Pir) with entrapment efficiencies (EE%) of 74.23 ± 8.14% and 51.52 ± 5.45%, respectively, or niclosamide and piroxicam (LPHNic–Pir) with respective EE% of 85.14 ± 3.47% and 48.75 ± 4.77%. The prepared LPH NPs had a core–shell nanostructure with particle size ≈ 125 nm and zeta potential ≈ −16.5 irrespective of drug payload. A dose-dependent cellular uptake of both LPH NPs was observed in human lung fibroblast cells. An enhanced in vitro antiviral efficacy of both LPHAzi–Pir and LPHNic–Pir was obtained over the mixed solution of the drugs. The LPH NPs of azithromycin or niclosamide with piroxicam displyed a promising capability to hinder the replication of SARS-CoV-2, with IC50 of 3.16 and 1.86 μM, respectively. These results provide a rationale for further in vivo pharmacological as well as toxicological studies to evaluate the potential activity of these drugs to combat the COVID-19 outbreak, especially the concept of combination therapy. Additionally, the molecular docking of macrolide bioactive compounds against papain-like protease (PDB ID:6wuu) was achieved. A ligand-based study, especially rapid overlay chemical structure (ROCS), was also examined to identify the general pharmacophoric features of these compounds and their similarity to reported anti-SARS-CoV-2 drugs. Molecular dynamic simulation was also implemented. Drug repurposing approach to combat SARS-CoV-2: lipid polymer hybrid nanoparticles (LPH) for the delivery of azithromycin or niclosamide in combination with piroxicam.

Structure- and Ligand-Based in silico Studies towards the Repurposing of Marine Bioactive Compounds to Target SARS-CoV-2.

This work was a structured virtual screening for marine bioactive compounds with reported antiviral activities which were subjected to structure-based studies against SARS-CoV-2 co-crystallized proteins. The molecular docking of marine bioactive compounds against the main protease (Mpro, PDB ID: 6lu7 and 6y2f), the spike glycoprotein (PDB ID: 6vsb), and the RNA polymerase (PDB ID: 6m71) of SARS-CoV-2 was performed. Ligand-based approach with the inclusion of rapid overlay chemical structures (ROCS) was also addressed in order to examine the probability of these marine compounds sharing relevance and druggability with the reported drugs. Among the examined marine library, the highest scores in different virtual screening aspects were displayed by compounds with flavonoids core, acyl indole, and pyrrole carboxamide alkaloids. Moreover, a complete overlay with the co-crystallized ligands of Mpro was revealed by sceptrin and debromo-sceptrin. Thalassoilin (A-B) which was found in the Red Sea exhibited the highest binding and similarity outcomes among all target proteins. These data highlight the importance of marine natural metabolites in regard to further studies for discovering new drugs to combat the COVID-19 pandemic.

An in silico perception for newly isolated flavonoids from peach fruit as privileged avenue for a countermeasure outbreak of COVID-19.

3'-Hydroxy-4'-methoxy-chroman-7-O-ß-d-glucopyranoside 4 was first isolated from a natural source, together with three known compounds, the ferulic acid heptyl ester 1, naringenin 2, and 4,2',4'-trihydroxy-6'-methoxychalcone-4'-O-ß-d-glucopyranoside 3, which were isolated from peach [Prunus persica (L.) Batsch] fruits. These compounds were subjected to different virtual screening strategies in order to examine their activity to combat the COVID-19 outbreak. The study design composed of some major aspects: (a) docking with main protease (Mpro), (b) docking with spike protein, (c) 3D shape similarity study (Rapid Overlay Chemical Similarity-ROCS) to the clinically used drugs in COVID-19 patients, and finally, (d) the rule of five and the estimated pre-ADMT properties of the separated flavonoids. Docking study with Mpro of SARS-CoV-2 (PDB ID:6LU7, and 6Y2F) showed that compound 3, its aglycone part, and compound 4 have a strong binding mode to a protease receptor with key amino acids, especially Gln:166AA, and having a similar docking pose to co-crystalized ligands. Docking with the spike protein of SARS-CoV-2 illustrated that compounds 3 and 4 have a good binding affinity to PDB ID:6VSB through the formation of HBs with Asp:467A and Asn:422A. According to ROCS analysis, compounds 1, 3, and 4 displayed high similarities to drugs that prevent SARS-Co2 entry to the lung cells or block the inflammatory storm causing lung injury. Compounds 3 and 4 are good candidates for drug development especially because they showed predicted activity against SARS-CoV-2 through different mechanisms either by preventing genome replication or by blocking inflammatory storm that trigger lung injury. These compounds were isolated from peach fruit, and the study supports data and continues with the recommendation of peach fruits in controlling and managing COVID-19 cases.