Статья

Data and text mining help identify key proteins involved in the molecular mechanisms shared by SARS-CoV-2 and HIV-1

O. Tarasova, S. Ivanov, D. Filimonov, V. Poroikov,
2021

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-CoV-2. 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 by the authors.

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Версии

  • 1. Version of Record от 2021-04-27

Метаданные

Об авторах
  • O. Tarasova
    Department for Bioinformatics, Institute of Biomedical Chemistry, Moscow, 107076, Russian Federation
  • S. Ivanov
    Department of Bioinformatics, Pirogov Russian National Research Medical University, Moscow, 107076, Russian Federation
  • D. Filimonov
  • V. Poroikov
Название журнала
  • Molecules
Том
  • 25
Выпуск
  • 12
Страницы
  • -
Ключевые слова
  • antiinflammatory agent; antivirus agent; complement; differentiation antigen; immunologic factor; interferon; interleukin derivative; ITCH protein, human; leu-13 antigen; repressor protein; toll like receptor; ubiquitin protein ligase; Betacoronavirus; Coronavirus infection; data mining; drug effect; gene expression regulation; genetic database; genetics; host pathogen interaction; human; Human immunodeficiency virus 1; Human immunodeficiency virus infection; immunology; inflammation; innate immunity; metabolism; pandemic; pathogenicity; procedures; signal transduction; virus pneumonia; Anti-Inflammatory Agents; Antigens, Differentiation; Antiviral Agents; Betacoronavirus; Complement System Proteins; Coronavirus Infections; Data Mining; Databases, Genetic; Gene Expression Regulation; HIV Infections; HIV-1; Host-Pathogen Interactions; Humans; Immunity, Innate; Immunologic Factors; Inflammation; Interferons; Interleukins; Metabolic Networks and Pathways; Pandemics; Pneumonia, Viral; Repressor Proteins; Signal Transduction; Toll-Like Receptors; Ubiquitin-Protein Ligases
Издатель
  • MDPI AG
Тип документа
  • journal article
Тип лицензии Creative Commons
  • CC
Правовой статус документа
  • Свободная лицензия
Источник
  • scopus