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bioRxiv · 10.1101/2023.11.20.567951

PROTACable is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning to Automate the De Novo Design of PROTACs

Mslati, H.·Gentile, F.·Pandey, M.·Ban, F.·Cherkasov, A.
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Abstract

Proteolysis-targeting chimeras (PROTACs) that engages two biological targets at once is 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 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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Mslati, H., Gentile, F., Pandey, M., Ban, F., Cherkasov, A.. 2023-11-21. PROTACable is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning to Automate the De Novo Design of PROTACs. https://doi.org/10.1101/2023.11.20.567951

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