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    <link>https://repository.kopri.re.kr/handle/201206/13421</link>
    <description />
    <pubDate>Wed, 11 Mar 2026 20:04:38 GMT</pubDate>
    <dc:date>2026-03-11T20:04:38Z</dc:date>
    <item>
      <title>Evidential deep learning for trustworthy prediction of enzyme commission number</title>
      <link>https://repository.kopri.re.kr/handle/201206/15062</link>
      <description>Title: Evidential deep learning for trustworthy prediction of enzyme commission number
Authors: Mingyu Park; So-Ra Han; Sai Kosaraju; JeungMin Lee; Hyun Lee; Lee, Jun Hyuck; Tae-Jin Oh; Mingon Kang
Abstract: The rapid growth of uncharacterized enzymes and their functional diversity urge accurate and trustworthy computational functional annotation tools. However, current state-of-the-art models lack trustworthiness on the prediction of the multilabel classification problem with thousands of classes. Here, we demonstrate that a novel evidential deep learning model (named ECPICK) makes trustworthy predictions of enzyme commission (EC) numbers with data-driven domain-relevant evidence, which results in significantly enhanced predictive power and the capability to discover potential new motif sites. ECPICK learns complex sequential patterns of amino acids and their hierarchical structures from 20 million enzyme data. ECPICK identifies significant amino acids that contribute to the prediction without multiple sequence alignment. Our intensive assessment showed not only outstanding enhancement of predictive performance on the largest databases of Uniprot, Protein Data Bank (PDB) and Kyoto Encyclopedia of Genes and Genomes (KEGG), but also a capability to discover new motif sites in microorganisms. ECPICK is a reliable EC number prediction tool to identify protein functions of an increasing number of uncharacterized enzymes.</description>
      <pubDate>Mon, 01 Jan 2024 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repository.kopri.re.kr/handle/201206/15062</guid>
      <dc:date>2024-01-01T00:00:00Z</dc:date>
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    <item>
      <title>H2O2-driven hydroxylation of steroids catalyzed by cytochrome P450 CYP105D18: Exploration of substrate access channel</title>
      <link>https://repository.kopri.re.kr/handle/201206/14321</link>
      <description>Title: H2O2-driven hydroxylation of steroids catalyzed by cytochrome P450 CYP105D18: Exploration of substrate access channel
Authors: Bashu Dev Pardhe; Kyoung Pyo Kwon; Jong Kook Park; Lee, Jun Hyuck; Tae-Jin Oh
Abstract: CYP105D18 supports H2O2 as an oxygen surrogate for catalysis well, and shows high H2O2 resistance capacity. We report the hydroxylation of different steroids using H2O2 as a co-substrate. Testosterone was regiospecifically hydroxylated to 2β-hydroxytestosterone. Based on the experimental data and molecular docking, we predicted that hydroxylation of methyl testosterone and nandrolone would occur at the position 2 in the A-ring, while hydroxylation of androstenedione and adrenosterone was predicted to occur in the B-ring. Further, structure-guided rational design of the substrate access channel was performed with the mutagenesis of residues S63, R82, and F184. Among the mutants, S63A showed a marked decrease in product formation, while F184A showed a significant increase in product formation in testosterone, nandrolone, methyl testosterone, androstenedione, and adrenosterone. The catalytic efficiency (Km/kcat) towards testosterone was increased 1.36-fold in F184A mutant as compared with the wild type enzyme. These findings might facilitate the potential use of CYP105D18 and further engineering to establish the basis of biotechnological applications.</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repository.kopri.re.kr/handle/201206/14321</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Complete genome sequence of the antibiotic resistant Pseudomonas fluorescens strain Ant01 from rhizosphere of Antarctic moss</title>
      <link>https://repository.kopri.re.kr/handle/201206/14322</link>
      <description>Title: Complete genome sequence of the antibiotic resistant Pseudomonas fluorescens strain Ant01 from rhizosphere of Antarctic moss
Authors: Hwang, Jisub; Lee, Hyoungseok; Do, Hackwon; Lee, Sung Gu; Tae-Jin Oh; Lee, Jun Hyuck
Abstract: Pseudomonas fluorescens Ant01, was isolated as an antibiotic resistant strain from rhizosphere of a moss in Barton Peninsular, King George Island, Antarctica. The assembled genome size is 6,249,144 bp containing 5,616 coding genes, 69 tRNA genes and 19 rRNA genes.</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repository.kopri.re.kr/handle/201206/14322</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Steroids from the Antarctic lichen Ramalina terebrata and their chemotaxonomical significance</title>
      <link>https://repository.kopri.re.kr/handle/201206/14382</link>
      <description>Title: Steroids from the Antarctic lichen Ramalina terebrata and their chemotaxonomical significance
Authors: Lee, Seulah; Lee, Jun Hyuck; Youn, Ui Joung
Abstract: Four steroids (1-4) were isolated from the Antarctic-lichen, Ramalina terebrata (Ramalinaceae), along with a lupane type triterpenoid (5) and an anthraquinone derivative (6). The structures of the isolated compounds were characterized by comprehensive spectroscopic analyses and LC-MS analysis. The isolated compounds were identified as brassicasterol (1), (22E,24R)-24-methylcholesta-5,22-diene-3β,7α-diol (2), ergosterol peroxide (3), 9,11-dehydroergosterol peroxide (4), lupeol (5) and parietin (6). It is the first report of the identification of steroids and a triterpenoid from R. terebrata. The chemotaxonomical significance of the isolated compounds is also discussed.</description>
      <pubDate>Sun, 01 Jan 2023 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://repository.kopri.re.kr/handle/201206/14382</guid>
      <dc:date>2023-01-01T00:00:00Z</dc:date>
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