Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium
Abstract The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 13. Okt. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hu, Lucas ZhongMing [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2023.10.08.561457 |
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| PPN (Katalog-ID): |
XBI041110951 |
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| 520 | |a Abstract The Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have implemented an efficient integrative experimental and computational framework leveraging the systematic generation and analysis of drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Protein activity-based analyses revealed highly reproducible, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide polypharmacology map, characterization of MoA-related drug clusters and off-target effects, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins. The proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, could help support more systematic and quantitative approaches to precision oncology. | ||
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| 700 | 1 | |a Turunen, Mikko |4 aut | |
| 700 | 1 | |a Pampou, Sergey |4 aut | |
| 700 | 1 | |a Grunn, Adina |4 aut | |
| 700 | 1 | |a Realubit, Ron |4 aut | |
| 700 | 1 | |a Antolin, Albert A. |4 aut | |
| 700 | 1 | |a Wang, Alexander L.E. |4 aut | |
| 700 | 1 | |a Li, Hai |4 aut | |
| 700 | 1 | |a Subramaniam, Prem |4 aut | |
| 700 | 1 | |a Karan, Charles |4 aut | |
| 700 | 1 | |a Alvarez, Mariano |4 aut | |
| 700 | 1 | |a Califano, Andrea |0 (orcid)0000-0003-4742-3679 |4 aut | |
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