Data and Text Mining Help Identify Key Proteins Involved in the Molecular Mechanisms Shared by SARS-CoV-2 and HIV-1

Data and Text Mining Help Identify Key Proteins Involved in the Molecular Mechanisms Shared by SARS-CoV-2 and HIV-1

Olga Tarasova, Sergey Ivanov, Dmitry A. Filimonov, Vladimir Poroikov

Viruses can be spread from one person to another; therefore, they may cause disorders in many people, sometimes leading to epidemics and even pandemics. New, previously unstudied viruses and some specific mutant or recombinant variants of known viruses constantly appear. An example is a variant of coronaviruses (CoV) causing severe acute respiratory syndrome (SARS), named SARS-CoV-2. Some antiviral drugs, such as remdesivir as well as antiretroviral drugs including darunavir, lopinavir, and ritonavir are suggested to be effective in treating disorders caused by SARS-CoV-2. There are data on the utilization of antiretroviral drugs against SARS-CoV2. Since there are many studies aimed at the identification of the molecular mechanisms of human immunodeficiency virus type 1 (HIV-1) infection and the development of novel therapeutic approaches against HIV-1, we used HIV-1 for our case study to identify possible molecular pathways shared by SARS-CoV-2 and HIV-1. We applied a text and data mining workflow and identified a list of 46 targets, which can be essential for the development of infections caused by SARS-CoV-2 and HIV-1. We show that SARS-CoV-2 and HIV-1 share some molecular pathways involved in inflammation, immune response, cell cycle regulation.

2020

SARS, SARS-CoV-2, HIV-1, data mining, virus–host interactions, text mining

10.3390/molecules25122944

Biotemas

Universidade Federal de Santa Catarina

Organic chemistry