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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00017176</identifier>
        <datestamp>2025-01-22T23:29:16Z</datestamp>
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          <dc:title>蛋白質化合物複合体立体構造データに基づく類似相互作用蛋白質の検索方式</dc:title>
          <dc:title xml:lang="en">Retrieval of Protein with Similar Interaction Based on Structural Data of Protein-compound Complex</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>野々村, 祐介</jpcoar:creatorName>
            <jpcoar:creatorName>吉野, 公一</jpcoar:creatorName>
            <jpcoar:creatorName>中江, 達哉</jpcoar:creatorName>
            <jpcoar:creatorName>大川剛直</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Yusuke, Nonomura</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Koichi, Yoshino</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Tatsuya, Nakae</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Takenao, Ohkawa</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">バイオインフォマティックス</jpcoar:subject>
          <datacite:description descriptionType="Other">蛋白質の機能解明に向けて，相互作用部位の立体構造が類似する部分構造を持つ蛋白質の検索が重要な役割を果たす．このとき，同様の相互作用が厳密に同一の原子配置によってのみ行われるわけではないため，入力となる相互作用部位立体構造データをそのまま検索のクエリに用いると類似構造の発見が困難になる．そこで本研究では，空間上で近接しており物性の類似する原子をグループ化することによって入力データを抽象化し，抽象化したデータを用いて類似構造の探索を行う方式を提案する．提案した方式を，化合物GDP，NADP，FMN に結合する蛋白質1i4d，1nvt，1um0 を入力として，同じ化合物に結合する複数の立体構造データに適用した結果，類似の相互作用部位を検出し，また，グループ化を行わない手法に比べ誤り部位の検出数を抑えることができ，その有効性が確認された．</datacite:description>
          <datacite:description descriptionType="Other">Retrieval of proteins that have similar structures at their interaction site plays an important role in elucidating their functions. This paper proposes a method for retrieving proteins with similar interaction using abstract data by grouping atoms located nearby and having similar physical properties. The proposed method was applied to the retrieval problem where GDPbinding protein 1i4d (PDB ID), NADP-binding protein 1nvt, and FMN-binding protein 1um0 were given as a query. The effectiveness of the method was confirmed by both the facts that it can extract similar interaction sites correctly, and the noises in detection are significantly smaller than in the method that does not group atoms.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2006-02-15</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_6501">journal article</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/17176</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">1882-7780</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA11464803</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>情報処理学会論文誌数理モデル化と応用（TOM）</jpcoar:sourceTitle>
          <jpcoar:volume>47</jpcoar:volume>
          <jpcoar:issue>SIG1(TOM14)</jpcoar:issue>
          <jpcoar:pageStart>110</jpcoar:pageStart>
          <jpcoar:pageEnd>119</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2008-02-15</datacite:date>
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