나도균 (중앙대학교)

한빛사논문

조회644

중앙대학교

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Mol. Syst. Biol., 20 November 2023 | https://doi.org/10.15252/msb.202311801 A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration

Dokyun Na ^1,†, Do-Hwan Lim ^2,3,†, Jae-Sang Hong ^2,4, Hyang-Mi Lee ¹, Daeahn Cho ¹, Myeong-Sang Yu ¹, Bilal Shaker ¹, Jun Ren ¹, Bomi Lee ⁵, Jae Gwang Song ⁵, Yuna Oh ⁶, Kyungeun Lee ⁶, Kwang-Seok Oh ⁷, Mi Young Lee ⁷, Min-Seok Choi², Han Saem Choi ⁵, Yang-Hee Kim ⁵, Jennifer M Bui ⁸, Kangseok Lee ⁹, Hyung Wook Kim ⁵, Young Sik Lee ^2,* & Jörg Gsponer ^8,*

¹Department of Biomedical Engineering, Chung-Ang University, Seoul, Republic of Korea
²College of Life Sciences and Biotechnology, Korea University, Seoul, Republic of Korea
³School of Systems Biomedical Science, Soongsil University, Seoul, Republic of Korea
⁴Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
⁵College of Life Sciences, Sejong University, Seoul, Republic of Korea
⁶Korea Institute of Science and Technology, Seoul, Republic of Korea
⁷Information-based Drug Research Center, Korea Research Institute of Chemical Technology, Deajeon, Republic of Korea
⁸Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
⁹Department of Life Science, Chung-Ang University, Seoul, Republic of Korea

^†These authors contributed equally to this work
^*Corresponding authors: correspondence to Young Sik Lee or Jörg Gsponer

Abstract

The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.

논문정보

형식Research article
게재일2023년 11월 (BRIC 등록일 2023-11-21)
연구진국내(교신)+국외 연구진
분야 생명과학 > 분자생물학

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