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Deep Learning‐Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease

Li, Xinuo; Sun, Yuan; Zhou, Zheng; Li, Jinran; Liu, Sai; Chen, Long; Shi, Yiting; Wang, Min; Zhu, Zheying; Wang, Guangji; Lu, Qiulun

Deep Learning‐Driven Exploration of Pyrroloquinoline Quinone Neuroprotective Activity in Alzheimer's Disease Thumbnail


Authors

Xinuo Li

Yuan Sun

Zheng Zhou

Jinran Li

Sai Liu

Long Chen

Yiting Shi

Min Wang

ZHEYING ZHU Zheying.Zhu@nottingham.ac.uk
Associate Professor in International Pharmacy and Traditional Medicines

Guangji Wang

Qiulun Lu



Abstract

Alzheimer's disease (AD) is a pressing concern in neurodegenerative research. To address the challenges in AD drug development, especially those targeting Aβ, this study uses deep learning and a pharmacological approach to elucidate the potential of pyrroloquinoline quinone (PQQ) as a neuroprotective agent for AD. Using deep learning for a comprehensive molecular dataset, blood–brain barrier (BBB) permeability is predicted and the anti‐inflammatory and antioxidative properties of compounds are evaluated. PQQ, identified in the Mediterranean‐DASH intervention for a diet that delays neurodegeneration, shows notable BBB permeability and low toxicity. In vivo tests conducted on an Aβ₁₋₄₂‐induced AD mouse model verify the effectiveness of PQQ in reducing cognitive deficits. PQQ modulates genes vital for synapse and anti‐neuronal death, reduces reactive oxygen species production, and influences the SIRT1 and CREB pathways, suggesting key molecular mechanisms underlying its neuroprotective effects. This study can serve as a basis for future studies on integrating deep learning with pharmacological research and drug discovery.

Journal Article Type Article
Acceptance Date Feb 15, 2024
Online Publication Date Mar 7, 2024
Publication Date May 15, 2024
Deposit Date Mar 15, 2024
Publicly Available Date Mar 18, 2024
Journal Advanced Science
Electronic ISSN 2198-3844
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 11
Issue 18
Article Number 2308970
DOI https://doi.org/10.1002/advs.202308970
Keywords neuroprotective activities, Alzheimer's disease, deep learning, pyrroloquinoline quinones
Public URL https://nottingham-repository.worktribe.com/output/32449965
Publisher URL https://onlinelibrary.wiley.com/doi/10.1002/advs.202308970

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