{"created":"2025-01-19T01:36:47.494193+00:00","updated":"2025-01-19T09:40:33.287323+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00234903","sets":["1164:2735:11468:11669"]},"path":["11669"],"owner":"44499","recid":"234903","title":["構造ベーススクリーニングに適したAlphaFoldタンパク質構造生成の最適化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-13"},"_buckets":{"deposit":"58a698d3-6c14-4040-9371-d001075cf835"},"_deposit":{"id":"234903","pid":{"type":"depid","value":"234903","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"構造ベーススクリーニングに適したAlphaFoldタンパク質構造生成の最適化","author_link":["641011","641012","641010"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"構造ベーススクリーニングに適したAlphaFoldタンパク質構造生成の最適化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"バイオ情報学1","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-06-13","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学情報理工学院情報工学系"},{"subitem_text_value":"東京工業大学情報理工学院情報工学系"},{"subitem_text_value":"東京工業大学情報理工学院情報工学系"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science, School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, School of Computing, Tokyo Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/234903/files/IPSJ-MPS24148016.pdf","label":"IPSJ-MPS24148016.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-13"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS24148016.pdf","filesize":[{"value":"3.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"7aea0ff0-92ad-44d8-87af-8dba7ae6c742","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"内河, 慶輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"古井, 海里"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大上, 雅史"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"タンパク質の立体構造情報を用いた構造ベースバーチャルスクリーニングは，他手法と比べて新規性の高い薬剤候補化合物を発見しやすいなどの利点がある．一方で，使用する標的タンパク質の立体構造によってスクリーニング精度が大きく変化するという問題があり，一般的に単体構造である apo 体よりもリガンドとの複合体構造である holo 体を用いた方が精度は良いが，予測された立体構造については結果は未知であった．そこで，本研究では，タンパク質立体構造予測の代表的な手法である AlphaFold2 と SBVS の組み合わせに注目し，AlphaFold2 での予測に用いられるパラメータを遺伝的アルゴリズムを使用して最適化することで，予測構造を利用した SBVS の精度改善を図る方法を検討した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"16","bibliographicVolumeNumber":"2024-MPS-148"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":234903,"links":{}}