Identify compound-protein interaction with knowledge graph embedding of perturbation transcriptomics
Abstract The emergence of perturbation transcriptomics provides a new perspective and opportunity for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to improve compound-protein interaction with knowledge graph embedding of perturbation transcriptomics. PertKGE incorporates diverse regulatory elements and accounts for multi-level regulatory events within biological systems, leading to significant improvements compared to existing baselines in two critical “cold-start” settings: inferring binding targets for new compounds and conducting virtual ligand screening for new targets. We further demonstrate the pivotal role of incorporating multi- level regulatory events in alleviating dataset bias. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti- tumor immunotherapy effect of tankyrase inhibitor K-756, and the discovery of five novel hits targeting the emerging cancer therapeutic target, aldehyde dehydrogenase 1B1, with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery by elucidating mechanisms of action and identifying novel therapeutic compounds..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 16. Apr. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ni, Shengkun [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.04.08.588632 |
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| PPN (Katalog-ID): |
XBI04325117X |
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| 520 | |a Abstract The emergence of perturbation transcriptomics provides a new perspective and opportunity for drug discovery, but existing analysis methods suffer from inadequate performance and limited applicability. In this work, we present PertKGE, a method designed to improve compound-protein interaction with knowledge graph embedding of perturbation transcriptomics. PertKGE incorporates diverse regulatory elements and accounts for multi-level regulatory events within biological systems, leading to significant improvements compared to existing baselines in two critical “cold-start” settings: inferring binding targets for new compounds and conducting virtual ligand screening for new targets. We further demonstrate the pivotal role of incorporating multi- level regulatory events in alleviating dataset bias. Notably, it enables the identification of ectonucleotide pyrophosphatase/phosphodiesterase-1 as the target responsible for the unique anti- tumor immunotherapy effect of tankyrase inhibitor K-756, and the discovery of five novel hits targeting the emerging cancer therapeutic target, aldehyde dehydrogenase 1B1, with a remarkable hit rate of 10.2%. These findings highlight the potential of PertKGE to accelerate drug discovery by elucidating mechanisms of action and identifying novel therapeutic compounds. | ||
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| 700 | 1 | |a Zhang, Yingying |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Zhengyang |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Zhaokun |e verfasserin |4 aut | |
| 700 | 1 | |a Fu, Zunyun |e verfasserin |4 aut | |
| 700 | 1 | |a Huo, Ruifeng |e verfasserin |4 aut | |
| 700 | 1 | |a Tong, Xiaochu |e verfasserin |4 aut | |
| 700 | 1 | |a Qu, Ning |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Xiaolong |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Kun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Runze |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Zimei |e verfasserin |4 aut | |
| 700 | 1 | |a Shi, Jiangshan |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Yitian |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Ruirui |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Xutong |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Sulin |e verfasserin |4 aut | |
| 700 | 1 | |a Zheng, Mingyue |e verfasserin |0 (orcid)0000-0002-3323-3092 |4 aut | |
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