{"links":{},"id":2002720,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02002720","sets":["1164:5352:1740054670081:1749434252473"]},"path":["1749434252473"],"owner":"80578","recid":"2002720","title":["立体構造類似性に着目したフラグメントベースドバーチャルスクリーニングのための化合物代表フラグメント集合の決定"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-06-14"},"_buckets":{"deposit":"84cef749-517a-4bda-935e-5d626a6a9567"},"_deposit":{"id":"2002720","pid":{"type":"depid","value":"2002720","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"立体構造類似性に着目したフラグメントベースドバーチャルスクリーニングのための化合物代表フラグメント集合の決定","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"立体構造類似性に着目したフラグメントベースドバーチャルスクリーニングのための化合物代表フラグメント集合の決定","subitem_title_language":"ja"},{"subitem_title":"Selection of Representative Fragment Sets for Fragment-Based Virtual Screening Focusing on 3D Structural Similarity","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"バイオ情報学（IPSJ-BIO）2","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2025-06-14","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京科学大学情報理工学院情報工学系"},{"subitem_text_value":"東京科学大学情報理工学院情報工学系"},{"subitem_text_value":"東京科学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, Institute of Science Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, School of Computing, Institute of Science Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, School of Computing, Institute of Science Tokyo","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/2002720/files/IPSJ-BIO25082044.pdf","label":"IPSJ-BIO25082044.pdf"},"date":[{"dateType":"Available","dateValue":"2027-06-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO25082044.pdf","filesize":[{"value":"1.5 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":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"cfb39856-e85e-4c0a-ac93-f556edc76dc0","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"米山,慧"}]},{"creatorNames":[{"creatorName":"柳澤,渓甫"}]},{"creatorNames":[{"creatorName":"秋山,泰"}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Satoshi Yoneyama","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Keisuke Yanagisawa","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yutaka Akiyama","creatorNameLang":"en"}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12055912","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":"2188-8590","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"薬剤候補化合物を絞り込む手法の一つに，化合物を部分構造（フラグメント）に分解した上で，計算を行うフラグメントベースドバーチャルスクリーニング(FBVS)がある．フラグメントは多くの化合物に共通するため，フラグメントに対する計算結果の再利用による計算コストの削減が期待できる．さらなる計算コスト削減のために，相互に類似したフラグメントを1つの代表フラグメントで表現することが提案されているが，従来法は類似度の計算上で，フラグメントの立体構造を考慮していないという問題点があった．本研究では，フラグメントの立体構造が類似していればタンパク質との相互作用様式も類似するという仮説のもと，フラグメントの立体構造アラインメントに基づく新たな類似度を提案し，この類似度に基づく化合物代表フラグメント集合を構築した．同じタンパク質に対して類似した相互作用様式を取った時のドッキングスコア差分とフラグメント間の類似度との相関を調査した結果，本研究が提案した立体構造に着目した類似度は，ドッキングスコア差分との決定係数の最大値がr2=0.55となり，立体構造を考慮していない従来の類似度での最大値r2=0.38よりも高い結果となった．提案する類似度と構築した代表フラグメント集合を用いることで，ドッキングスコアの類似をより反映するフラグメント間の紐付けを行うことができるため，FBVSの精度を向上させることが期待できる．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Fragment-based virtual screening (FBVS) is one approach to narrowing down drug candidate compounds, in which compounds are decomposed into substructures (fragments) for computational evaluation. Since many compounds share fragments, reusing computational results for fragments can reduce overall cost. To further reduce the cost, the idea of selecting smaller set of representative fragments has been proposed, but previous methods did not consider the 3D structure of fragments. In this study, we propose a similarity measure based on 3D structural alignment of fragments, under the hypothesis that similar 3D structures lead to similar interaction modes with proteins. Using the proposed similarity measure, we constructed sets of representative fragments for virtual screening. We analyzed the correlation between fragment similarity and the absolute difference in docking scores when fragments showed similar binding modes to the same protein. The proposed method gives a coefficient of determination r2 = 0.55, which is higher than the r2 = 0.38 obtained by the conventional method that ignores the 3D structure. These results suggest that the proposed similarity measure enables more accurate fragment matching in terms of docking score similarity, potentially improving FBVS performance.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2025-06-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"44","bibliographicVolumeNumber":"2025-BIO-82"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"created":"2025-06-09T02:38:41.013728+00:00","updated":"2025-10-09T02:36:59.966951+00:00"}