Novel 2019 coronavirus structure, mechanism of action, antiviral drug promises and rule out against its treatment
By Subramanian Boopathi, Adolfo B Poma, P. Kolandaivel. 2020
483 citations recorded by the source corpus.
Abstract In the past two decades, the world has faced several infectious disease outbreaks. Ebola, Influenza A (H1N1), SARS, MERS, and Zika virus have had a massive global impact in terms of economic disruption, the strain on local and global public health. Most recently, the global outbreak of novel coronavirus 2019 (SARS-CoV-2) that causes COVID-19 is a newly discovered virus from the coronavirus family in Wuhan city, China, known to be a great threat to the public health systems. As of 15 April 2020, The Johns Hopkins University estimated that the COVID-19 affected more than two million people, resulting in a death toll above 130,000 around the world. Infected people in Europe and America correspond about 40% and 30% of the total reported cases respectively. At this moment only few Asian countries have controlled the disease, but a second wave of new infections is expected. Predicting inhibitor and target to the COVID-19 is an urgent need to protect human from the disease. Therefore, a protocol to identify anti-COVID-19 candidate based on computer-aided drug design is urgently needed. Thousands of compounds including approved drugs and drugs in the clinical trial are available in the literature. In practice, experimental techniques can measure the time and space average properties but they cannot be captured the structural variation of the COVID-19 during the interaction of inhibitor. Computer simulation is particularly suitable to complement experiments to elucidate conformational changes at the molecular level which are related to inhibition process of the COVID-19. Therefore, computational simulation is essential tool to elucidate the phenomenon. The structure-based virtual screening computational approach will be used to filter the best drugs from the literature, the investigate the structural variation of COVID-19 with the interaction of the best inhibitor is a fundamental step to design new drugs and vaccines which can combat the coronavirus. This mini-review will address novel coronavirus structure, mechanism of action, and trial test of antiviral drugs in the lab and patients with COVID-19.
Subfields: Computational Theory and Mathematics, Infectious Diseases
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Citations in the corpus
- Using X-ray images and deep learning for automated detection of coronavirus disease (2020, background): “The disease would, therefore, to have originated from an animal (zoonosis) but the origin has not been confirmed (Boopathi et al., 2020; CNHC, 2020; El Zowalaty & J € arhult, 2020; Kandel et al., 2020; Manoj et al., 2020; Pant et al., 2020; Roosa et al., 2020; Sun et al., 2020; Wilder-Smith et al.,…”
- Automated Deep Transfer Learning-Based Approach for Detection of COVID-19 Infection in Chest X-rays (2020, unknown): “However, the source of this virus has not been identified [1].”
- SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: an in silico perspective (2020, background): “Several studies are suggesting the effectiveness of different anti-viral drugs and compounds against the coronavirus proteins (Aanouz et al., 2020; Boopathi et al., 2020; Elfiky & Azzam, 2020; Elmezayen et al., 2020; Enayatkhani et al., 2020; Gupta et al., 2020; Khan et al., 2020a, 2020b;…”