PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs.
J Chem Inf Model
; 64(8): 3034-3046, 2024 04 22.
Article
em En
| MEDLINE
| ID: mdl-38504115
ABSTRACT
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/.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Desenho de Fármacos
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Modelos Moleculares
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Proteólise
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Aprendizado Profundo
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article