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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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| Опубликовано в: : | J Phys Chem B |
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| Главные авторы: | , , , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2020
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| Предметы: | |
| Online-ссылка: | 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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