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Amelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow

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dc.contributor.authorXie, Chenglong
dc.contributor.authorZhuang, Xu-Xu
dc.contributor.authorNiu, Zhangming
dc.contributor.authorAi, Ruixue
dc.contributor.authorLautrup, Sofie
dc.contributor.authorZheng, Shuangjia
dc.contributor.authorJiang, Yinghui
dc.contributor.authorHan, Ruiyu
dc.contributor.authorSen Gupta, Tanima
dc.contributor.authorCao, Shuqin
dc.contributor.authorLagartos-Donate, Maria Jose
dc.contributor.authorCai, Cui-Zan
dc.contributor.authorXie, Li-Ming
dc.contributor.authorCaponio, Domenica
dc.contributor.authorWang, Wen-Wen
dc.contributor.authorSchmauck-Medina, Tomas
dc.contributor.authorZhang, Jianying
dc.contributor.authorWang, He-ling
dc.contributor.authorLou, Guofeng
dc.contributor.authorXiao, Xianglu
dc.contributor.authorZheng, Wenhua
dc.contributor.authorPalikaras, Konstantinos
dc.contributor.authorYang, Guang
dc.contributor.authorCaldwell, Kim A.
dc.contributor.authorCaldwell, Guy A.
dc.contributor.authorShen, Han-Ming
dc.contributor.authorNilsen, Hilde
dc.contributor.authorLu, Jia-Hong
dc.contributor.authorFang, Evandro F.
dc.contributor.otherWenzhou Medical University
dc.contributor.otherUniversity of Oslo
dc.contributor.otherOujiang Laboratory
dc.contributor.otherUniversity of Macau
dc.contributor.otherSun Yat Sen University
dc.contributor.otherAthens Medical School
dc.contributor.otherNational & Kapodistrian University of Athens
dc.contributor.otherRoyal Brompton Hospital
dc.contributor.otherImperial College London
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherUniversity of Alabama Birmingham
dc.contributor.otherNational University of Singapore
dc.contributor.otherZhengzhou University
dc.date.accessioned2023-09-28T19:11:26Z
dc.date.available2023-09-28T19:11:26Z
dc.date.issued2022
dc.description.abstractA reduced removal of dysfunctional mitochondria is common to aging and age-related neurodegenerative pathologies such as Alzheimer's disease (AD). Strategies for treating such impaired mitophagy would benefit from the identification of mitophagy modulators. Here we report the combined use of unsupervised machine learning (involving vector representations of molecular structures, pharmacophore fingerprinting and conformer fingerprinting) and a cross-species approach for the screening and experimental validation of new mitophagy-inducing compounds. From a library of naturally occurring compounds, the workflow allowed us to identify 18 small molecules, and among them two potent mitophagy inducers (Kaempferol and Rhapontigenin). In nematode and rodent models of AD, we show that both mitophagy inducers increased the survival and functionality of glutamatergic and cholinergic neurons, abrogated amyloid-beta and tau pathologies, and improved the animals' memory. Our findings suggest the existence of a conserved mechanism of memory loss across the AD models, this mechanism being mediated by defective mitophagy. The computational-experimental screening and validation workflow might help uncover potent mitophagy modulators that stimulate neuronal health and brain homeostasis.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationXie, C., Zhuang, X.-X., Niu, Z., Ai, R., Lautrup, S., Zheng, S., Jiang, Y., Han, R., Gupta, T. S., Cao, S., Lagartos-Donate, M. J., Cai, C.-Z., Xie, L.-M., Caponio, D., Wang, W.-W., Schmauck-Medina, T., Zhang, J., Wang, H., Lou, G., … Fang, E. F. (2022). Amelioration of Alzheimer’s disease pathology by mitophagy inducers identified via machine learning and a cross-species workflow. In Nature Biomedical Engineering (Vol. 6, Issue 1, pp. 76–93). Springer Science and Business Media LLC. https://doi.org/10.1038/s41551-021-00819-5
dc.identifier.doi10.1038/s41551-021-00819-5
dc.identifier.orcidhttps://orcid.org/0000-0001-7344-7733
dc.identifier.orcidhttps://orcid.org/0000-0002-1132-0179
dc.identifier.orcidhttps://orcid.org/0000-0002-1147-125X
dc.identifier.orcidhttps://orcid.org/0000-0001-7369-5227
dc.identifier.orcidhttps://orcid.org/0000-0002-2938-5923
dc.identifier.orcidhttps://orcid.org/0000-0002-8920-1487
dc.identifier.orcidhttps://orcid.org/0000-0003-4618-0628
dc.identifier.orcidhttps://orcid.org/0000-0001-8161-7536
dc.identifier.orcidhttps://orcid.org/0000-0002-8283-9090
dc.identifier.urihttps://ir.ua.edu/handle/123456789/10976
dc.languageEnglish
dc.language.isoen_US
dc.publisherNature Portfolio
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectINTERFERENCE COMPOUNDS PAINS
dc.subjectBLOOD-BRAIN-BARRIER
dc.subjectASSAY INTERFERENCE
dc.subjectC. ELEGANS
dc.subjectA-BETA
dc.subjectLIFE-SPAN
dc.subjectKAEMPFEROL
dc.subjectNAD(+)
dc.subjectMODEL
dc.subjectNEURONS
dc.subjectEngineering, Biomedical
dc.titleAmelioration of Alzheimer's disease pathology by mitophagy inducers identified via machine learning and a cross-species workflowen_US
dc.typeArticle
dc.typetext

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