Multidimensional Design of Anticancer Peptides.
Angew Chem Int Ed Engl
; 54(35): 10370-4, 2015 Aug 24.
Article
em En
| MEDLINE
| ID: mdl-26119906
ABSTRACT
The computer-assisted design and optimization of peptides with selective cancer cell killing activity was achieved through merging the features of anticancer peptides, cell-penetrating peptides, and tumor-homing peptides. Machine-learning classifiers identified candidate peptides that possess the predicted properties. Starting from a template amino acid sequence, peptide cytotoxicity against a range of cancer cell lines was systematically optimized while minimizing the effects on primary human endothelial cells. The computer-generated sequences featured improved cancer-cell penetration, induced cancer-cell apoptosis, and were enabled a decrease in the cytotoxic concentration of co-administered chemotherapeutic agents inâ
vitro. This study demonstrates the potential of multidimensional machine-learning methods for rapidly obtaining peptides with the desired cellular activities.
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Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
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Desenho Assistido por Computador
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Derme
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Peptídeos Penetradores de Células
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Antineoplásicos
Limite:
Female
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Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article