Designing Anticancer Peptides by Constructive Machine Learning

Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a deep machine learning model to design membranolytic anticancer peptides (ACPs) de...

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Veröffentlicht in:	ChemMedChem Jg. 13; H. 13; S. 1300 - 1302
Hauptverfasser:	Grisoni, Francesca, Neuhaus, Claudia S., Gabernet, Gisela, Müller, Alex T., Hiss, Jan A., Schneider, Gisbert
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	WEINHEIM Wiley 06.07.2018 Wiley Subscription Services, Inc
Schlagworte:	Adenocarcinoma Amino acids Artificial intelligence Automation Cancer Chemistry, Medicinal Computer memory de novo design deep learning Design drug discovery Erythrocytes Learning algorithms Life Sciences & Biomedicine Machine learning Memory cells Molecular chains Neural networks Organic chemistry peptide design Peptides Pharmacology & Pharmacy Recurrent neural networks Science & Technology Selectivity Transfer learning peptide design de novo design deep learning NK-LYSIN drug discovery artificial intelligence
ISSN:	1860-7179, 1860-7187, 1860-7187
Online-Zugang:	Volltext
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