PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs
Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:64 |
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| Enthalten in: |
Journal of chemical information and modeling - 64(2024), 8 vom: 22. Apr., Seite 3034-3046 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mslati, Hazem [VerfasserIn] |
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| Links: |
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| Themen: |
EC 2.3.2.27 |
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| Anmerkungen: |
Date Completed 23.04.2024 Date Revised 24.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1021/acs.jcim.3c01878 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/ | ||
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| 700 | 1 | |a Ban, Fuqiang |e verfasserin |4 aut | |
| 700 | 1 | |a Cherkasov, Artem |e verfasserin |4 aut | |
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