Data-Driven and Machine-Learning Methods to Project Coronavirus Disease 2019 Pandemic Trend in Eastern Mediterranean.

Background: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health crisis worldwide, and the Eastern Mediterranean is one of the most affected areas. Materials and Methods: We use a data-driven approach to assess the characteristics, situation, prevalence, and current intervention actions of the COVID-19 pandemic. We establish a spatial model of the spread of the COVID-19 pandemic to project the trend and time distribution of the total confirmed cases and growth rate of daily confirmed cases based on the current intervention actions. Results: The results show that the number of daily confirmed cases, number of active cases, or growth rate of daily confirmed cases of COVID-19 are exhibiting a significant downward trend in Qatar, Egypt, Pakistan, and Saudi Arabia under the current interventions, although the total number of confirmed cases and deaths is still increasing. However, it is predicted that the number of total confirmed cases and active cases in Iran and Iraq may continue to increase. Conclusion: The COVID-19 pandemic in Qatar, Egypt, Pakistan, and Saudi Arabia will be largely contained if interventions are maintained or tightened. The future is not optimistic, and the intervention response must be further strengthened in Iran and Iraq. The aim of this study is to contribute to the prevention and control of the COVID-19 pandemic.

Identification of Potential Key Agents for Targeting RNA-Dependent RNA Polymerase of SARS-CoV-2 by Integrated Analysis and Virtual Drug Screening.

BACKGROUND: RNA-dependent RNA polymerase (RdRp) is the key enzyme responsible for the SARS-CoV-2 replication process and catalyzes the synthesis of complementary minus strand RNA and genomic plus strand RNA, often recognized as good targets for antiviral drugs. MATERIALS AND METHODS: A systematic screening of existing antiviral compounds, family analysis, conserved domain analysis, three-dimensional structure modeling, drug virtual screening, and bioassays were performed to identify agents that potentially targeted RNA-dependent RNA polymerase of SARS-CoV-2. RESULTS: Four thousand nine hundred and forty seven antiviral lead compounds were selected and evaluated by systematic screening. Of these, 359 agents were screened by family analysis and conserved domain analysis. They were further analyzed by three-dimensional structure modeling, virtual drug screening, and bioassays. The results identified 102 agents with potential for repurposing to target the RNA-dependent RNA polymerase of SARS-CoV-2. CONCLUSION: This study identified 102 key agents with potential anti-SARS-CoV-2 RNA-dependent RNA polymerase function and prospects of rapid clinical application for the treatment of COVID-19.