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Utilizing deep learning for alzheimer's disease treatment: Targeting β-amyloid for therapeutic intervention
- 1 Northwest A&F University
* Author to whom correspondence should be addressed.
Abstract
Amyloid-beta (Aβ for short) is a protein intricately linked to Alzheimer’s disease (AD for short). In the brains of AD patients, Aβ forms abnormal deposits known as amyloid plaques, which are considered one of the key factors in the progression of AD. These plaques may disrupt communication between neurons, leading to cell death and a decline in cognitive function. Therefore, this study aims to utilize Computer-aided drug design (CADD) techniques to screen and optimize potential therapeutic agents targeting Aβ. Through literature review and UniProt, we identified the active sites of Aβ and constructed a three-dimensional structural model using AlphaFold. We employed Molecular docking technology to virtually screen a compound library for candidate molecules that may bind to Aβ. The selected candidates were then subjected to Molecular dynamics simulation to verify their stability, and their molecular structures were further optimized using Pharmacophore modeling. Our research results indicate the successful screening of a series of candidate compounds with high affinity and selectivity. These compounds can form stable complexes with the active sites of Aβ, thereby inhibiting its aggregation and deposition. Current structural determination methods for Aβ have certain limitations. Techniques such as cryo-electron microscopy (cryo-EM) and scanning electron microscopy (SEM) can observe the morphology of Aβ fibrils but typically do not provide atomic-level structural information. Additionally, Aβ proteins tend to form non-specific aggregates in vitro, presenting challenges in preparing samples suitable for structural analysis. The innovation of this study lies in the combination of various computer-assisted technologies, offering new perspectives and methods for the drug treatment of AD and laying the groundwork for the development of novel therapeutic agents targeting Aβ.
Keywords
Alzheimer’s Disease (AD), Amyloid-beta (Aβ), Amyloid Precursor Protein (APP)
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Cite this article
Fang,T. (2024). Utilizing deep learning for alzheimer's disease treatment: Targeting β-amyloid for therapeutic intervention. Theoretical and Natural Science,49,66-73.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 4th International Conference on Biological Engineering and Medical Science
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