De novo antioxidant peptide design via machine learning and DFT studies

De novo antioxidant peptide design via machine learning and DFT studies

Abstract Antioxidant peptides (AOPs) are highly valued in food and pharmaceutical industries due to their significant role in human function. This study introduces a novel approach to identifying robust AOPs using a deep generative model based on sequence representation. Through filtration with a de...

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Bibliographic Details
Main Authors: Parsa Hesamzadeh, Abdolvahab Seif, Kazem Mahmoudzadeh, Mokhtar Ganjali Koli, Amrollah Mostafazadeh, Kosar Nayeri, Zohreh Mirjafary, Hamid Saeidian
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Antioxidant peptides
De novo design
Deep learning
Machine learning
DFT calculation
Molecular dynamics simulations
Online Access:https://doi.org/10.1038/s41598-024-57247-z

Internet

https://doi.org/10.1038/s41598-024-57247-z

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