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10.1021/acs.jcim.0c00420

http://scihub22266oqcxt.onion/10.1021/acs.jcim.0c00420
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32672454!ä!32672454

suck abstract from ncbi


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pmid32672454      J+Chem+Inf+Model 2020 ; 60 (12): 5730-5734
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  • Bioactivity Profile Similarities to Expand the Repertoire of COVID-19 Drugs #MMPMID32672454
  • Duran-Frigola M; Bertoni M; Blanco R; Martinez V; Pauls E; Alcalde V; Turon G; Villegas N; Fernandez-Torras A; Pons C; Mateo L; Guitart-Pla O; Badia-I-Mompel P; Gimeno A; Soler N; Brun-Heath I; Zaragoza H; Aloy P
  • J Chem Inf Model 2020[Dec]; 60 (12): 5730-5734 PMID32672454show ga
  • Until a vaccine becomes available, the current repertoire of drugs is our only therapeutic asset to fight the SARS-CoV-2 outbreak. Indeed, emergency clinical trials have been launched to assess the effectiveness of many marketed drugs, tackling the decrease of viral load through several mechanisms. Here, we present an online resource, based on small-molecule bioactivity signatures and natural language processing, to expand the portfolio of compounds with potential to treat COVID-19. By comparing the set of drugs reported to be potentially active against SARS-CoV-2 to a universe of 1 million bioactive molecules, we identify compounds that display analogous chemical and functional features to the current COVID-19 candidates. Searches can be filtered by level of evidence and mechanism of action, and results can be restricted to drug molecules or include the much broader space of bioactive compounds. Moreover, we allow users to contribute COVID-19 drug candidates, which are automatically incorporated to the pipeline once per day. The computational platform, as well as the source code, is available at https://sbnb.irbbarcelona.org/covid19.
  • |*COVID-19 Drug Treatment[MESH]
  • |Antiviral Agents/*chemistry/pharmacology[MESH]
  • |Computer Simulation[MESH]
  • |Drug Design[MESH]
  • |Drug Repositioning/*methods[MESH]
  • |Humans[MESH]
  • |Models, Molecular[MESH]
  • |Molecular Structure[MESH]
  • |SARS-CoV-2/*drug effects[MESH]


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