Selected article for: "genome sequence and NCBI database"

Author: Bo Ram Beck; Bonggun Shin; Yoonjung Choi; Sungsoo Park; Keunsoo Kang
Title: Predicting commercially available antiviral drugs that may act on the novel coronavirus (2019-nCoV), Wuhan, China through a drug-target interaction deep learning model
  • Document date: 2020_2_2
  • ID: cszqykpu_6
    Snippet: Amino acid sequences of 3C-like proteinase (accession YP_009725301.1), RNA-dependent RNA polymerase (accession YP_009725307.1), helicase (accession YP_009725308.1), 3'-to-5' exonuclease (accession YP_009725309.1), endoRNAse (accession YP_009725310.1), and 2'-O-ribose methyltransferase (accession YP_009725311.1) of the 2019-nCoV replication complex were extracted from the 2019-nCoV whole genome sequence (accession NC_045512.2), from the National C.....
    Document: Amino acid sequences of 3C-like proteinase (accession YP_009725301.1), RNA-dependent RNA polymerase (accession YP_009725307.1), helicase (accession YP_009725308.1), 3'-to-5' exonuclease (accession YP_009725309.1), endoRNAse (accession YP_009725310.1), and 2'-O-ribose methyltransferase (accession YP_009725311.1) of the 2019-nCoV replication complex were extracted from the 2019-nCoV whole genome sequence (accession NC_045512.2), from the National Center for Biotechnology Information (NCBI) database. The raw prediction results were screened for antiviral drugs that are FDA approved, target viral proteins, and have a Kd value less than 1,000 nM.

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