{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00234906","sets":["1164:2735:11468:11669"]},"path":["11669"],"owner":"44499","recid":"234906","title":["リンク予測を用いたタンパク質原子－リガンド原子間相互作用の予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-13"},"_buckets":{"deposit":"8ef30054-bda9-479d-9756-6a8d193b80d6"},"_deposit":{"id":"234906","pid":{"type":"depid","value":"234906","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"リンク予測を用いたタンパク質原子－リガンド原子間相互作用の予測","author_link":["641017","641018"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"リンク予測を用いたタンパク質原子－リガンド原子間相互作用の予測"},{"subitem_title":"Prediction of Interactions Between Protein and Ligand Atoms Using Link Prediction","subitem_title_language":"en"}]},"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"}]},"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"}]},"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/234906/files/IPSJ-MPS24148019.pdf","label":"IPSJ-MPS24148019.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-13"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS24148019.pdf","filesize":[{"value":"436.6 kB"}],"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":"1beeb3ba-4aa3-4bab-88cb-07b290427d30","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":"柳沢, 優斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石田, 貴士"}],"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－リガンド間相互作用は薬剤設計において重要な情報である．しかし，これを実験的に獲得するには大きなコストを要するため，計算機を用いてタンパク質－リガンド間相互作用を予測する手法が数多く開発されている．既存の手法はシミュレーションベースの手法と機械学習ベースの手法に大別されるが，ネットワーク科学分野の技術「リンク予測」を用いることで，これまでとは異なる観点から予測することが可能である．そこで本研究では，タンパク質配列とリガンド化学構造，そして一部の相互作用情報が与えられたとき，それらをグラフに変換しリンク予測を行うことで，タンパク質とリガンド間の相互作用する原子ペアを予測する手法を提案した．DeepWalk を用いてリンク予測を行った結果，ROC-AUC の平均が 0.594 となり，リンク予測を用いてタンパク質原子－リガンド原子間相互作用を予測することが可能であることが示された．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Protein-ligand interactions are important information in drug design. However, since obtaining this information experimentally is very costly, a number of computational methods have been developed to predict protein-ligand interactions. Existing methods can be broadly classified into simulation-based methods and machine learning-based methods, but by using “link prediction,” a technique in the field of network science, it is possible to predict from a different perspective. In this study, we proposed a method to predict interacting atom pairs between proteins and ligands by converting protein sequences, ligand chemical structures, and some interaction information into graphs and performing link prediction. The results of link prediction using DeepWalk showed that the average of ROC-AUC was 0.594, suggesting that it is possible to predict protein-ligand atom interactions using link prediction.","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":"19","bibliographicVolumeNumber":"2024-MPS-148"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":234906,"updated":"2025-01-19T09:40:30.190474+00:00","links":{},"created":"2025-01-19T01:36:47.773410+00:00"}