Computational Drug Discovery and Repurposing for the Treatment of COVID-19: A Systematic Review

TL;DR: Covering all activities concerned with emergency medicine, it is the journal to turn to for information to help increase the ability to understand, recognize and treat emergency conditions.

TL;DR: In this article, the authors provide an introduction to molecular docking and to the different docking procedures with a focus on several considerations and protocols, including protonation states, active site waters and consensus, that can greatly improve the docking results.

TL;DR: In this paper , a review summarizes representative structures and typically potential therapy agents that target SARS-CoV-2 or some critical proteins for viral pathogenesis, providing insights into the mechanisms underlying viral infection, prevention of infection, and treatment.

TL;DR: Persistency of immunoglobulin concentrations is one of the factors that determines the possibility of reaching herd immunity or periodic outbreaks in coronavirus disease (COVID-19).

TL;DR: It is found that many FDA approved drugs are potentially highly potent to 2019-nCoV, and an SBDR model based on machine learning and mathematics is developed to screen 1465 drugs in the DrugBank that have been approved by the U.S. Food and Drug Administration.

TL;DR: The current status of high-performance computing applications in the general area of drug discovery is reviewed and an introduction to the methodologies applied at atomic and molecular scales is provided, followed by three specific examples of implementation of these tools.

TL;DR: Using in vivo single cell clonal analysis, the bi-potency of single BASCs that differentiate into club cells, ciliated cells, AT2 and AT1 cells after bronchiole-alveoli double injuries is identified.