1 Ocak 2024 Dergi makalesi Açık Erişim

Yuce, Merve; Ates, Beril; Yasar, Nesrin Isil; Sungur, Fethiye Aylin; Kurkcuoglu, Ozge

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/282493</identifier>
  <creators>
    <creator>
      <creatorName>Yuce, Merve</creatorName>
      <givenName>Merve</givenName>
      <familyName>Yuce</familyName>
      <affiliation>Istanbul Tech Univ, Dept Chem Engn, TR-34469 Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Ates, Beril</creatorName>
      <givenName>Beril</givenName>
      <familyName>Ates</familyName>
      <affiliation>Istanbul Tech Univ, Dept Chem Engn, TR-34469 Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Yasar, Nesrin Isil</creatorName>
      <givenName>Nesrin Isil</givenName>
      <familyName>Yasar</familyName>
      <affiliation>Istanbul Tech Univ, Informat Inst, Computat Sci &amp; Engn Div, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Sungur, Fethiye Aylin</creatorName>
      <givenName>Fethiye Aylin</givenName>
      <familyName>Sungur</familyName>
      <affiliation>Istanbul Tech Univ, Informat Inst, Computat Sci &amp; Engn Div, Istanbul, Turkiye</affiliation>
    </creator>
    <creator>
      <creatorName>Kurkcuoglu, Ozge</creatorName>
      <givenName>Ozge</givenName>
      <familyName>Kurkcuoglu</familyName>
      <affiliation>Istanbul Tech Univ, Dept Chem Engn, TR-34469 Istanbul, Turkiye</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Computational Workflow To Determine Drug Candidates Alternative To Aminoglycosides Targeting The Decoding Center Of &lt;I&gt;E. Coli&lt;/I&gt; Ribosome</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2024</publicationYear>
  <dates>
    <date dateType="Issued">2024-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/282493</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1016/j.jmgm.2024.108817</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;The global antibiotic resistance problem necessitates fast and effective approaches to finding novel inhibitors to treat bacterial infections. In this study, we propose a computational workflow to identify plausible high-affinity compounds from FDA-approved, investigational, and experimental libraries for the decoding center on the small subunit 30S of the E. coli ribosome. The workflow basically consists of two molecular docking calculations on the intact 30S, followed by molecular dynamics (MD) simulations coupled with MM-GBSA calculations on a truncated ribosome structure. The parameters used in the molecular docking suits, Glide and AutoDock Vina, as well as in the MD simulations with Desmond were carefully adjusted to obtain expected interactions for the ligandrRNA complexes. A filtering procedure was followed, considering a fingerprint based on aminoglycoside's binding site on the 30S to obtain seven hit compounds either with different clinical usages or aminoglycoside derivatives under investigation, suggested for in vitro studies. The detailed workflow developed in this study promises an effective and fast approach for the estimation of binding free energies of large protein-RNA and ligand complexes.&lt;/p&gt;</description>
  </descriptions>
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