{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00218620","sets":["1164:2735:10865:10962"]},"path":["10962"],"owner":"44499","recid":"218620","title":["分子動力学シミュレーション軌跡データからの環状ペプチドの膜透過性と相関が高い特徴量の抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-06-20"},"_buckets":{"deposit":"3a306fea-c2c1-4df3-95f1-24ccdbedf99d"},"_deposit":{"id":"218620","pid":{"type":"depid","value":"218620","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"分子動力学シミュレーション軌跡データからの環状ペプチドの膜透過性と相関が高い特徴量の抽出","author_link":["569000","568998","569003","568999","569001","569002"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"分子動力学シミュレーション軌跡データからの環状ペプチドの膜透過性と相関が高い特徴量の抽出"}]},"item_type_id":"4","publish_date":"2022-06-20","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"},{"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"},{"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/218620/files/IPSJ-MPS22138050.pdf","label":"IPSJ-MPS22138050.pdf"},"date":[{"dateType":"Available","dateValue":"2024-06-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS22138050.pdf","filesize":[{"value":"2.5 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":"43c904a6-21c4-45ec-b173-10f0850289ca","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"能祖, 雄大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"杉田, 昌岳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤江, 拓哉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"柳澤, 渓甫"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大上, 雅史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"秋山, 泰"}],"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":"近年注目されている中分子医薬品のうちの 1 つである環状ペプチド医薬品の開発によって，従来の医薬品では狙うことが難しかった細胞内のタンパク質間相互作用（PPI）の阻害などが可能になると期待されている．しかし，一般的に環状ペプチドは細胞膜透過性が低く，経口投与や細胞内標的の阻害が可能な膜透過性の持つ環状ペプチドを選別する必要がある．そこで，充分な膜透過性を持つ環状ペプチドを選別するために，環状ペプチドの膜透過性の予測法の確立が必要とされている．本研究では，環状ペプチドの脂質二重膜の透過過程を分子動力学シミュレーションにて再現し，その軌跡データから膜透過性の高さと相関のある特徴量の抽出を試みた．サンプリングには REST/REUS 法を用いて，広範なコンフォメーションを探索した．また，計算した特徴量を用いて機械学習による膜透過性予測も行った．結果として，10 残基環状ペプチドを用いた単回帰分析では，膜の界面付近での，ペプチドとその周りの分子との静電相互作用が最も膜透過性の実験値と相関があった（r=0.89）．また，6 残基環状ペプチドを用いた機械学習による膜透過性予測においても，膜の界面付近の特徴量が重要であることが示唆された．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-06-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"50","bibliographicVolumeNumber":"2022-MPS-138"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":218620,"updated":"2025-01-19T15:06:19.403646+00:00","links":{},"created":"2025-01-19T01:18:58.529465+00:00"}