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Rosetta Machine Learning Models Accurately Classify Positional Effects of Thioamides on Proteolysis
Thioamide substitutions of the peptide backbone have been shown to stabilize therapeutic and imaging peptides toward proteolysis. In order to rationally design thioamide modifications, we have developed a novel Rosetta custom score function to classify thioamide positional effects on proteolysis in...
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| Publicado no: | J Phys Chem B |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7759720/ https://ncbi.nlm.nih.gov/pubmed/32869996 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1021/acs.jpcb.0c05981 |
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