SyntaLinker-Hybrid: A deep learning approach for target specific drug design
Target specific drug design has attracted much attention in drug discovery. But, it is a great challenge to efficiently explore the target-focused chemical space. Fragment-based drug design (FBDD) has shown its potential to do this thing. In this study, we introduced a deep learning-based fragment l...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-12-01
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| Series: | Artificial Intelligence in the Life Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266731852200006X |
| _version_ | 1811197641414934528 |
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| author | Yu Feng Yuyao Yang Wenbin Deng Hongming Chen Ting Ran |
| author_facet | Yu Feng Yuyao Yang Wenbin Deng Hongming Chen Ting Ran |
| author_sort | Yu Feng |
| collection | DOAJ |
| description | Target specific drug design has attracted much attention in drug discovery. But, it is a great challenge to efficiently explore the target-focused chemical space. Fragment-based drug design (FBDD) has shown its potential to do this thing. In this study, we introduced a deep learning-based fragment linking method, namely SyntaLinker-Hybrid, for target specific molecular generation. By carrying out transfer learning and fragment hybridization, this method allows to generate a great number of linker fragments to assemble given terminal fragments into the molecules with target specificity. This work demonstrates that the method has the capacity to generate target specific structures for various targets. We believe that its application could be extended to a broader target scope. |
| first_indexed | 2024-04-12T01:17:05Z |
| format | Article |
| id | doaj.art-e5139cc9baa84947af28deef7b2944ab |
| institution | Directory Open Access Journal |
| issn | 2667-3185 |
| language | English |
| last_indexed | 2024-04-12T01:17:05Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Artificial Intelligence in the Life Sciences |
| spelling | doaj.art-e5139cc9baa84947af28deef7b2944ab2022-12-22T03:53:55ZengElsevierArtificial Intelligence in the Life Sciences2667-31852022-12-012100035SyntaLinker-Hybrid: A deep learning approach for target specific drug designYu Feng0Yuyao Yang1Wenbin Deng2Hongming Chen3Ting Ran4School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou 510006, China; Department of drug and vaccine research, Guangzhou Laboratory, Guangzhou 510530, ChinaDepartment of drug and vaccine research, Guangzhou Laboratory, Guangzhou 510530, ChinaSchool of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou 510006, China; Corresponding authors.Department of drug and vaccine research, Guangzhou Laboratory, Guangzhou 510530, China; Corresponding authors.Department of drug and vaccine research, Guangzhou Laboratory, Guangzhou 510530, China; Corresponding authors.Target specific drug design has attracted much attention in drug discovery. But, it is a great challenge to efficiently explore the target-focused chemical space. Fragment-based drug design (FBDD) has shown its potential to do this thing. In this study, we introduced a deep learning-based fragment linking method, namely SyntaLinker-Hybrid, for target specific molecular generation. By carrying out transfer learning and fragment hybridization, this method allows to generate a great number of linker fragments to assemble given terminal fragments into the molecules with target specificity. This work demonstrates that the method has the capacity to generate target specific structures for various targets. We believe that its application could be extended to a broader target scope.http://www.sciencedirect.com/science/article/pii/S266731852200006XDeep generative modelTransfer learningFragment-based drug designTarget specific drug design |
| spellingShingle | Yu Feng Yuyao Yang Wenbin Deng Hongming Chen Ting Ran SyntaLinker-Hybrid: A deep learning approach for target specific drug design Artificial Intelligence in the Life Sciences Deep generative model Transfer learning Fragment-based drug design Target specific drug design |
| title | SyntaLinker-Hybrid: A deep learning approach for target specific drug design |
| title_full | SyntaLinker-Hybrid: A deep learning approach for target specific drug design |
| title_fullStr | SyntaLinker-Hybrid: A deep learning approach for target specific drug design |
| title_full_unstemmed | SyntaLinker-Hybrid: A deep learning approach for target specific drug design |
| title_short | SyntaLinker-Hybrid: A deep learning approach for target specific drug design |
| title_sort | syntalinker hybrid a deep learning approach for target specific drug design |
| topic | Deep generative model Transfer learning Fragment-based drug design Target specific drug design |
| url | http://www.sciencedirect.com/science/article/pii/S266731852200006X |
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