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Explainable Deep Relational Networks for Predicting Compound–Protein Affinities and Contacts
Predicting compound–protein affinity is beneficial for accelerating drug discovery. Doing so without the often-unavailable structure data is gaining interest. However, recent progress in structure-free affinity prediction, made by machine learning, focuses on accuracy but leaves much to be desired f...
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| Publicado en: | J Chem Inf Model |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2020
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7987499/ https://ncbi.nlm.nih.gov/pubmed/33347301 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acs.jcim.0c00866 |
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