天然产物对抗阿尔茨海默病的机器学习、分子建模和 QSAR 研究

Title:Machine Learning, Molecular Modeling, and QSAR Studies on Natural Products Against Alzheimer’s Disease

Volume: 28 Issue: 38

关键词: 阿尔茨海默病，计算机，分子对接，分子动力学，QSAR，分子学习。

摘要:

Background: Alzheimer's disease (AD) is a very common neurodegenerative disorder in individuals over 65 years of age; however, younger individuals can also be affected due to brain damage.

Introduction: The general symptoms of this disease include progressive loss of memory, changes in behavior, deterioration of thinking, and gradual loss of ability to perform daily activities. According to the World Health Organization, dementia has affected more than 50 million people worldwide, and it is estimated that there are 10 million new cases per year, of which 70% are due to AD.

Methods: This paper reported a review of scientific articles available on the internet which discuss in silico analyzes such as molecular docking, molecular dynamics, and quantitative structure-activity relationship (QSAR) of different classes of natural products and their derivatives published from 2016 onwards. In addition, this work reports the potential of fermented papaya preparation against oxidative stress in AD.

Results: This research reviews the most recent studies on AD, computational analysis methods used in proposing new bioactive compounds and their possible molecular targets, and finally, the molecules or classes of natural products involved in each study.

Conclusion: Thus, studies like this can orientate new research works on neurodegenerative diseases, especially AD.

Cite this article as:

Machine Learning, Molecular Modeling, and QSAR Studies on Natural Products Against Alzheimer’s Disease, Current Medicinal Chemistry 2021; 28 (38) . https://dx.doi.org/10.2174/0929867328666210603104749