Recent Advances on Antioxidant Identification Based on Machine Learning Methods

Author(s): Pengmian Feng*, Lijing Feng

Journal Name: Current Drug Metabolism

Volume 21 , Issue 10 , 2020


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Abstract:

Antioxidants are molecules that can prevent damages to cells caused by free radicals. Recent studies also demonstrated that antioxidants play roles in preventing diseases. However, the number of known molecules with antioxidant activity is very small. Therefore, it is necessary to identify antioxidants from various resources. In the past several years, a series of computational methods have been proposed to identify antioxidants. In this review, we briefly summarized recent advances in computationally identifying antioxidants. The challenges and future perspectives for identifying antioxidants were also discussed. We hope this review will provide insights into researches on antioxidant identification.

Keywords: Antioxidant, free radical, diseases, sequence encoding scheme, machine learning methods, molecules.

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Article Details

VOLUME: 21
ISSUE: 10
Year: 2020
Published on: 15 December, 2020
Page: [804 - 809]
Pages: 6
DOI: 10.2174/1389200221666200719001449
Price: $65

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