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Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network
Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and whe...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977097/ https://www.ncbi.nlm.nih.gov/pubmed/36859488 http://dx.doi.org/10.1038/s41467-023-36699-3 |