DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules
Drug-target interaction prediction is critical for drug development. Through the integration of structural and transcriptional signature information, molecules both binding to the target and producing therapeutic activities could be found out to improve targeted drug prediction. Therefore, the appro...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
|
| Series: | Pharmacological Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1043661825001355 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849713802181869568 |
|---|---|
| author | Yiran Tang Shengqiao Gao Dan Luo Xuyong Jiang Xueru Zhao Wanting Hu Yongxiang Zhang Zhiyong Xiao Lu Han Wenxia Zhou |
| author_facet | Yiran Tang Shengqiao Gao Dan Luo Xuyong Jiang Xueru Zhao Wanting Hu Yongxiang Zhang Zhiyong Xiao Lu Han Wenxia Zhou |
| author_sort | Yiran Tang |
| collection | DOAJ |
| description | Drug-target interaction prediction is critical for drug development. Through the integration of structural and transcriptional signature information, molecules both binding to the target and producing therapeutic activities could be found out to improve targeted drug prediction. Therefore, the approaches that integrate the two types of data are worth exploring. Here, we present an integrated method named Data Integration Oriented Repurposing Strategy (DIORS) combining molecular docking and gene-signature matching to enhance the prediction of protein-targeted drugs. The StandardScaler algorithm was selected after evaluation of five algorithms and was used in DIORS. Surface Plasmon Resonance (SPR) was used to verify the molecular affinities and cell-based assays were used to verify the activities of DIORS predicted molecules. In Piezo1-targeted molecule prediction, among the top ten predicted molecules by DIORS, four of them, namely gefitinib, rifaximin, bosutinib and vandetanib, exhibited binding affinities. In the prediction of TLR4/MD2-targeted anti-inflammatory molecules, among the top ten predicted molecules, three of them, namely enoxolone, dabrafenib and ponatinib, exhibit both high binding affinities and anti-inflammatory activities. The results demonstrated that DIORS can serve as a better approach with high performance to predict and find new targeted drugs by combining structural and signature information. |
| format | Article |
| id | doaj-art-12e41b4483384334aad67b564f5b31e4 |
| institution | DOAJ |
| issn | 1096-1186 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Pharmacological Research |
| spelling | doaj-art-12e41b4483384334aad67b564f5b31e42025-08-20T03:13:52ZengElsevierPharmacological Research1096-11862025-05-0121510771010.1016/j.phrs.2025.107710DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted moleculesYiran Tang0Shengqiao Gao1Dan Luo2Xuyong Jiang3Xueru Zhao4Wanting Hu5Yongxiang Zhang6Zhiyong Xiao7Lu Han8Wenxia Zhou9State Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, China; Pharmacology of Chinese Medicine, Shaanxi University of Chinese Medicine, Xianyang 712046, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, ChinaState Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, China; Corresponding authors.State Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, China; Corresponding authors.State Key Laboratory of National Security Specially Needed Medicines, Academy of Military Medical Sciences, Beijing 100850, China; Corresponding authors.Drug-target interaction prediction is critical for drug development. Through the integration of structural and transcriptional signature information, molecules both binding to the target and producing therapeutic activities could be found out to improve targeted drug prediction. Therefore, the approaches that integrate the two types of data are worth exploring. Here, we present an integrated method named Data Integration Oriented Repurposing Strategy (DIORS) combining molecular docking and gene-signature matching to enhance the prediction of protein-targeted drugs. The StandardScaler algorithm was selected after evaluation of five algorithms and was used in DIORS. Surface Plasmon Resonance (SPR) was used to verify the molecular affinities and cell-based assays were used to verify the activities of DIORS predicted molecules. In Piezo1-targeted molecule prediction, among the top ten predicted molecules by DIORS, four of them, namely gefitinib, rifaximin, bosutinib and vandetanib, exhibited binding affinities. In the prediction of TLR4/MD2-targeted anti-inflammatory molecules, among the top ten predicted molecules, three of them, namely enoxolone, dabrafenib and ponatinib, exhibit both high binding affinities and anti-inflammatory activities. The results demonstrated that DIORS can serve as a better approach with high performance to predict and find new targeted drugs by combining structural and signature information.http://www.sciencedirect.com/science/article/pii/S1043661825001355Drug-target interactionMolecular dockingSignatureStructureLINCSDrug repurposing |
| spellingShingle | Yiran Tang Shengqiao Gao Dan Luo Xuyong Jiang Xueru Zhao Wanting Hu Yongxiang Zhang Zhiyong Xiao Lu Han Wenxia Zhou DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules Pharmacological Research Drug-target interaction Molecular docking Signature Structure LINCS Drug repurposing |
| title | DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules |
| title_full | DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules |
| title_fullStr | DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules |
| title_full_unstemmed | DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules |
| title_short | DIORS: Enhancing drug-target interaction prediction via structure and signature integrated-driven approach and discovering potential targeted molecules |
| title_sort | diors enhancing drug target interaction prediction via structure and signature integrated driven approach and discovering potential targeted molecules |
| topic | Drug-target interaction Molecular docking Signature Structure LINCS Drug repurposing |
| url | http://www.sciencedirect.com/science/article/pii/S1043661825001355 |
| work_keys_str_mv | AT yirantang diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT shengqiaogao diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT danluo diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT xuyongjiang diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT xueruzhao diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT wantinghu diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT yongxiangzhang diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT zhiyongxiao diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT luhan diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules AT wenxiazhou diorsenhancingdrugtargetinteractionpredictionviastructureandsignatureintegrateddrivenapproachanddiscoveringpotentialtargetedmolecules |