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Fulltext SARS-CoV-2 spike protein: Site-specific breakpoints for the development of COVID-19 vaccines

Velusamy P, Kiruba K, Su CH, Arun V, Anbu P, Gopinath SCB, et al.

J King Saud Univ Sci, 2021 Dec;33(8):101648.
PMID: 34690467 DOI: 10.1016/j.jksus.2021.101648

SARS-CoV2 is a member of human coronaviruses and is the causative agent of the present pandemic COVID-19 virus. In order to control COVID-19, studies on viral structure and mechanism of infectivity and pathogenicity are sorely needed. The spike (S) protein is comprised of S1 & S2 subunits. These spike protein subunits enable viral attachment by binding to the host cell via ACE-2 (angiotensin converting enzyme-2) receptor, thus facilitating the infection. During viral entry, one of the key steps is the cleavage of the S1-S2 spike protein subunits via surface TMPRSS2 (transmembrane protease serine 2) and results in viral infection. Hence, the S-protein is critical for the viral attachment and penetration into the host. The rapid advancement of our knowledge on the structural and functional aspects of the spike protein could lead to development of numerous candidate vaccines against SARS-CoV2. Here the authors discuss about the structure of spike protein and explore its related functions. Our aim is to provide a better understanding that may aid in fighting against CoVID-19 and its treatment.
Fulltext Determinants, predictors and negative impacts of burnout among health care workers during COVID-19 pandemic

Al-Otaibi T, Abbas A, Ashry Gheith O, Nair P, Zahab MA, Hammouda MAA, et al.

J King Saud Univ Sci, 2023 Jan;35(1):102441.
PMID: 36405649 DOI: 10.1016/j.jksus.2022.102441

The first defense line of the battle, healthcare workers (HCWs), faces a significant challenge in managing the current COVID-19 pandemic. An online electronic survey was sent to HCWs via email and social media networks. Socio-demographic data and work environment-related variables were assessed. Consequences of burnout (BO) were reported, e.g., elicited medical errors. Maslach burnout inventory was used to diagnose BO. Two hundred and eighty-four participants were included with a mean age of 39.83 ± 7.34 years, 70.8% worked in the COVID-19 frontline, 91.9% were followed daily updates about COVID-19, 63.7% were not satisfied with the coordination between triage and isolation, 64.4% got COVID-19 infection, 91.9% had a colleague or family member developed COVID-19 infection, and 21.5% experienced a colleague /a family member died due to COVID-19. Multivariate analysis by linear regression revealed that; working as a frontline HCW (OR 1.28, CI = 0.14-2.55) and sleep deprivation (OR 3.93, CI = 1.88-8.22) were the predictors of burnout.
Fulltext Mathematical model based on fractional trace operator for COVID-19 image enhancement

Karim FK, Jalab HA, Ibrahim RW, Al-Shamasneh AR

J King Saud Univ Sci, 2022 Oct;34(7):102254.
PMID: 35957965 DOI: 10.1016/j.jksus.2022.102254

The medical image enhancement is major class in the image processing which aims for improving the medical diagnosis results. The improving of the quality of the captured medical images is considered as a challenging task in medical image. In this study, a trace operator in fractional calculus linked with the derivative of fractional Rényi entropy is proposed to enhance the low contrast COVID-19 images. The pixel probability values of the input image are obtained first in the proposed image enhancement model. Then the covariance matrix between the input image and the probability of a pixel intensity of the input image to be calculated. Finally, the image enhancement is performed by using the convolution of covariance matrix result with the input image. The proposed enhanced image algorithm is tested against three medical image datasets with different qualities. The experimental results show that the proposed medical image enhancement algorithm achieves the good image quality assessments using both the BRISQUE, and PIQE quality measures. Moreover, the experimental results indicated that the final enhancement of medical images using the proposed algorithm has outperformed other methods. Overall, the proposed algorithm has significantly improved the image which can be useful for medical diagnosis process.
Fulltext Community behavioral change and management of COVID-19 Pandemic: Evidence from Indonesia

Tjahjadi B, Soewarno N, Adibah Wan Ismail W, Kustiningsih N, Nasihatun Nafidah L

J King Saud Univ Sci, 2023 Feb;35(2):102451.
PMID: 36415666 DOI: 10.1016/j.jksus.2022.102451

OBJECTIVES: This study aims to investigate the effect of information and motivation on behavioral change related to the COVID-19 pandemic management in Indonesia. It also examines the role of behavioral skills in mediating the information-behavioral change relationship and the motivation-behavioral change relationship.
METHOD: This study employs the partial least squares structural equation modeling (PLS-SEM) to test the research hypotheses. Using the online survey method to collect data, 845 responses were obtained from several main islands of Indonesia.
RESULTS: The results of the study show that information and motivation positively influence people's behavior changes. Behavioral skills mediate the influence of information and motivation on behavioral change. This study contributes to the development of the information-motivation-behavior model (IMB-Model). It also provides additional knowledge on pandemic management in the research setting of Indonesia as a country that has complex characteristics in terms of religion and belief, demography, culture, economy, and politics.
CONCLUSIONS: This study concludes that the success of Indonesia in dealing with the pandemic greatly depends on the success of changing the community behavior. Providing reliable and consistent information enhances people's motivation to build their behavioral skills. With increased behavioral skills, people have changed their behavior in fighting against COVID-19 by obeying health protocols, participating in vaccination programs, and practicing a healthier lifestyle.
Fulltext Combined docking methods and molecular dynamics to identify effective antiviral 2, 5-diaminobenzophenonederivatives against SARS-CoV-2

Ouassaf M, Belaidi S, Mogren Al Mogren M, Chtita S, Ullah Khan S, Thet Htar T

J King Saud Univ Sci, 2021 Mar;33(2):101352.
PMID: 33558797 DOI: 10.1016/j.jksus.2021.101352

The aim of this work is to contribute to the research in finding lead compounds for clinical use, to identify new drugs that target the SARS-CoV-2 virus main protease (Mpro). In this study, we used molecular docking strategies to analyze 2.5-diaminobenzophenone compounds against Malaria and to compare results with the Nelfinavir as a FDA-approved HIV-1 protease inhibitor recommended for the treatment of COVID-19. These efforts identified the potential compounds against SAR-COV-2 Mpro with the docking scores ranges from -6.1 to -7.75 kcal/mol, which exhibited better interactions than the Nelfinavir. Among thirty-six studied, compounds 20c, 24c, 30c, 34c, 35c and 36c showed the highest affinity and involved in forming hydrophobic interactions with Glu166, Thr24, Thr25, and Thr26 residues and forming H-bonding interactions with Gln189, Cys145, and His41residues. Pharmacokinetic properties and toxicity (ADMET) were also determined for identified compounds. This study result in the identification of two compounds 35 and 36 having high binding affinity, good pharmacokinetics properties and lowest toxicity. The structural stability and dynamics of lead compounds within the active site of 3CLpro was also examined using molecular dynamics (MD) simulation. Essential dynamics demonstrated that the two complexes remain stable during the entire duration of simulation. We have shown that these two lead molecules would have the potential to act as promising drug-candidates and would be of interest as starting point for designing compounds against the SARS-CoV-2.