{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00216916","sets":["1164:5352:10882:10883"]},"path":["10883"],"owner":"44499","recid":"216916","title":["機械学習によるタンパク質のアポ構造からホロ構造の予測手法の開発"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-03-03"},"_buckets":{"deposit":"a43979db-0fbd-4292-a98c-c344e42bd952"},"_deposit":{"id":"216916","pid":{"type":"depid","value":"216916","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習によるタンパク質のアポ構造からホロ構造の予測手法の開発","author_link":["560927","560931","560929","560932","560930","560928"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習によるタンパク質のアポ構造からホロ構造の予測手法の開発"},{"subitem_title":"Development of prediction method of holo-structure from apo-structure of protein by machine learning","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-03-03","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"},{"subitem_text_value":"東京工業大学物質・情報卓越教育院"},{"subitem_text_value":"東京工業大学情報理工学院"}]},"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/216916/files/IPSJ-BIO22069006.pdf","label":"IPSJ-BIO22069006.pdf"},"date":[{"dateType":"Available","dateValue":"2024-03-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO22069006.pdf","filesize":[{"value":"2.0 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":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"99962309-0aa7-4d43-96e7-cf399951b6a2","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":"李, 明曄"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"安尾, 信明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"関嶋, 政和"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Mingyeh, Lee","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nobuaki, Yasuo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masakazu, Sekijima","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"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":"蛋白質の立体構造を基にした薬物設計では、タンパク質のホロ構造が必要だが、ホロ構造の構造決定が難しい。そこで、本研究ではタンパク質のアルファカーボンの距離行列を用いて、アポタンパク質の距離行列からホロタンパク質の距離行列を予測する手法の開発を行った。その結果、学習データに対してはホロ構造の距離行列を生成できたが、テストデータでは生成できておらず、モデルが過学習を起こしている可能性が示唆された。本研究により距離行列を用いたアポ構造からホロ構造を予測する機械学習モデルの可能性が示されたが、さらなる研究が必要である。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Although the holo-structure of a protein is necessary for drug design based on its 3D structure, it is difficult to determine the structure of the holo-structure. In this study, we developed a method to predict the distance matrix of the holo protein from the distance matrix of the apo protein using the distance matrix of the alpha carbon of the protein. As a result, we were able to generate the distance matrix of the holo structure for the training data, but not for the test data, suggesting that the model may be overfitting. This study shows the possibility of a machine learning model to predict the holo-structure from the apo structure using the distance matrix, but further research is needed.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2022-BIO-69"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":216916,"updated":"2025-01-19T15:41:18.018524+00:00","links":{},"created":"2025-01-19T01:17:25.659112+00:00"}