{"created":"2023-06-20T14:06:33.804366+00:00","id":36,"links":{},"metadata":{"_buckets":{"deposit":"987d9cf6-d1cf-4a32-9fc2-ce21686311e3"},"_deposit":{"created_by":2,"id":"36","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"36"},"status":"published"},"_oai":{"id":"oai:maebashi-it.repo.nii.ac.jp:00000036","sets":["6:7"]},"author_link":["150","151"],"item_2_alternative_title_18":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"In silico screening of novel drug candidates for diabetes mellitus"}]},"item_2_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2017-11-21","bibliographicIssueDateType":"Issued"},"bibliographic_titles":[{}]}]},"item_2_date_granted_63":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2017-09-27"}]},"item_2_degree_grantor_61":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_name":"前橋工科大学"}],"subitem_degreegrantor_identifier":[{}]}]},"item_2_degree_name_60":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士(工学)"}]},"item_2_description_39":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"subitem_description":"Thesis or Dissertation","subitem_description_type":"Other"}]},"item_2_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"抗糖尿病活性を有する植物からの抽出物の知見に基づき、計算機支援創薬技法を用いて新規抗糖尿病化合物を選定した。選定した第一の抗糖尿病化合物は、タチナタマメ由来のタンパク質と適切な様態の相互作用を示し、インスリン分泌刺激による抗糖尿病制御機構を示すことを計算機解析で確認した。第二の抗糖尿病化合物は、植物由来の化合物をPTPN1阻害剤に基づく薬理原子団モデルを基準に選定した。選定した化合物は、薬剤適性、薬物動態、詳細な結合挙動を計算機による解析で評価した。更にPTPN1 (PDB ID: 3EAX)の結晶構造を目標分子として計算機上で結合解析を行った。\\n\\n選定したこれらの化合物及びその類似化合物は、抗糖尿病活性確認のための臨床検査に推奨される。\\n\\n\\nMost diabetes medicines nowadays available and have approval, but unfortunately, they could not approach satisfactory levels of blood sugar (glucose) in patients suffering diabetes mellitus and possess numerous adverse effects. Thus novel classes of anti-diabetic drugs are required. The contribution of computer-aided drug design (CADD) techniques in the identification of antidiabetic agents has been discussed in this dissertation. \\n\\nIn chapter 1, I introduced the background and current status of CADD for diabetes mellitus, my research goals and the strategies used in this dissertation.\\n\\nIn chapter 2, by computational analysis of Canavalia ensiformis protein, I demonstrated that it’s conserved amino acid sequence homologous to human insulin protein. The plant insulin (UniProt ID: Q7M217) used as alternative source of human insulin showed its mechanism of action in terms of optimal binding mode with available antidiabetic drugs. A biphenyl derivative was identified as a lead compound and designed its analogs. Molecular docking analyses showed that four analogs could be recommended as antidiabetic agents with suitable drug-like properties as compared with a standard antidiabetic drug (aleglitazar).\\n\\nIn chapter 3, plant-derived protein tyrosine phosphatase non-receptor type 1 (PTPN1) inhibitors possessing antidiabetic activity were used for pharmacophore model generation. The pharmacophore-based screening of plant-derived compounds of the ZINC database was conducted using ZINCpharmer; screened hits were assessed to evaluate their drug-likeness, pharmacokinetics, detailed binding behavior and aggregator possibility. The crystal structure of PTPN1 (PDB ID: 3EAX) was used as a molecular target for docking analyses of screened dataset. Through the virtual screening and in silico pharmacology protocols ZINC30731533 (isosilybin) was identified as a lead compound with optimal properties.\\n\\nChapter 4 sum-ups the achievement and originality of this research work. It concluded with significant aspects of the current research scheme in the area of drug discovery.","subitem_description_type":"Abstract"}]},"item_2_dissertation_number_64":{"attribute_name":"学位授与番号","attribute_value_mlt":[{"subitem_dissertationnumber":"　甲第20号"}]},"item_2_text_66":{"attribute_name":"更新日","attribute_value_mlt":[{"subitem_text_value":"2019-10-28"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shabana, Bibi"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"シャバナ, ビビ"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-09-18"}],"displaytype":"detail","filename":"PhD thesis -Shabana Bibi.pdf","filesize":[{"value":"2.3 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"PhD thesis -Shabana Bibi.pdf","url":"https://maebashi-it.repo.nii.ac.jp/record/36/files/PhD thesis -Shabana Bibi.pdf"},"version_id":"10c81bb2-07f9-4e17-a861-d2023891253b"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"計算機創薬"},{"subitem_subject":"computer-aided drug design"},{"subitem_subject":"糖尿病"},{"subitem_subject":"diabetes mellitus"},{"subitem_subject":"植物インスリン"},{"subitem_subject":"plant insulin"},{"subitem_subject":"リード化合物同定と最適化"},{"subitem_subject":"lead identification and optimization"},{"subitem_subject":"フラボノイド"},{"subitem_subject":"flavonoid"},{"subitem_subject":"イソシルビン"},{"subitem_subject":"Isosilybin"},{"subitem_subject":"チロシンフォスファターゼ非受容体タイプ1"},{"subitem_subject":"protein tyrosine phosphatase non-receptor type"},{"subitem_subject":"薬理原子団モデリング"},{"subitem_subject":"pharmacophore modeling"},{"subitem_subject":"分子結合"},{"subitem_subject":"molecular docking"},{"subitem_subject":"薬物動態"},{"subitem_subject":"pharmacokinetics"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_title":"計算機支援薬剤設計法による糖尿病薬剤候補化合物の選定","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"計算機支援薬剤設計法による糖尿病薬剤候補化合物の選定"}]},"item_type_id":"2","owner":"2","path":["7"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-11-21"},"publish_date":"2017-11-21","publish_status":"0","recid":"36","relation_version_is_last":true,"title":["計算機支援薬剤設計法による糖尿病薬剤候補化合物の選定"],"weko_creator_id":"2","weko_shared_id":2},"updated":"2023-06-20T14:10:46.754452+00:00"}