Abstract
Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19. Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally. The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods. The delayed revelation of viral infectious mechanisms is currently one of the technical obstacles in the prevention and treatment of infectious diseases. In this study, we proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus–human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections, which help further developing drugs and targeted therapeutic methods against COVID-19. Moreover, we constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases.
Highlights
Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s [1, 2]
We proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus–human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar severe acute respiratory syndrome (SARS) infections, which help further developing drugs and targeted therapeutic methods against COVID-19
By using our prediction model, which is based on a random walk algorithm on a virus–human protein interaction network, we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections
Summary
Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s [1, 2]. Compared with the two other coronavirus subtypes, COVID-19 causes more complicated clinical symptoms [9] and has higher transmissible capacity [3] and faster mutational rates [9]. These characteristics make its prevention and treatment difficult. SARS and MERS have already been controlled by regional governments, the pathogenic mechanisms of these diseases have not been fully revealed [12, 13]. We proposed a computational method to identify the potential pathological mechanisms of COVID19, the coronavirus subtype that is spreading all over the world and causing the 2019–2020 coronavirus pandemic. We constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
