Amyloid oligomers: A joint experimental/computational perspective on Alzheimer's disease, Parkinson's disease, type II diabetes, and amyotrophic lateral sclerosis

Phuong H. Nguyen, Ayyalusamy Ramamoorthy, Bikash R. Sahoo, Jie Zheng, Peter Faller, John E. Straub, Laura Dominguez, Joan Emma Shea, Nikolay V. Dokholyan, Alfonso de Simone, Buyong Ma, Ruth Nussinov, Saeed Najafi, Son Tung Ngo, Antoine Loquet, Mara Chiricotto, Pritam Ganguly, James McCarty, Mai Suan Li, Carol HallYiming Wang, Yifat Miller, Simone Melchionna, Birgit Habenstein, Stepan Timr, Jiaxing Chen, Brianna Hnath, Birgit Strodel, Rakez Kayed, Sylvain Lesné, Guanghong Wei, Fabio Sterpone, Andrew J. Doig, Philippe Derreumaux

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320 Scopus citations


Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Original languageEnglish (US)
Pages (from-to)2545-2647
Number of pages103
JournalChemical Reviews
Issue number4
StatePublished - Feb 24 2021

Bibliographical note

Funding Information:
Laura Dominguez gratefully acknowledges the support of PAIP 5000-9155, LANCAD-UNAM-DGTIC-306, and CONACyT Ciencia Básica A1-S-8866. John E. Straub gratefully acknowledges the generous support of the National Science Foundation (Grant No. CHE-1900416) and the National Institutes of Health (Grant No. R01 GM107703). Alfonso De Simone acknowledges funding from the European Research Council (ERC), Consolidator Grant (CoG) “BioDisOrder” (819644). Yiming Wang and Carol K. Hall acknowledge the support of a Cheney Visiting Scholar Fellowship from the University of Leeds. The work was also supported by NSF Division of Chemical, Bioengineering, Environmental, and Transport Systems Grants 1743432 and 1512059. Antoine Loquet thanks the ERC starting Grant no. 639020. For Buyong Ma and Ruth Nussinov, this project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract HHSN26120080001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. This Research was supported [in part] by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. Birgit Strodel acknowledges funding by a Helmholtz ERC Recognition Award. Jie Zheng acknowledges funding from NSF (1806138 and 1825122). Stepan Timr acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 840395. Fabio Sterpone acknowledges funding from the ERC (FP7/2007-2013) Grant Agreement no. 258748. Nikolay Dokholyan acknowledges support from the National Institutes for Health grants 1R35 GM134864 and UL1 TR002014 and the Passan Foundation. Joan-Emma Shea acknowledges computational support from the Extreme Science and Engineering Discovery Environment (XSEDE) through the National Science Foundation (NSF) grant number TG-MCA05S027. J.-E. Shea acknowledges the support from the National Science Foundation (NSF Grant MCB-1716956). The funding from the National Institutes of Health (NIH grant R01-GM118560-01A) and partial support from the National Science Foundation MRSEC grant No. DMR 1720256 is also acknowledged. She thanks the Center for Scientific Computing at the California Nanosystems Institute (NSF Grant CNS-1725797). The work of Sylvain Lesné was supported by grants from the National Institutes of Health (NIH) to (RF1-AG044342, R21-AG065693, R01-NS092918, R01-AG062135, and R56-NS113549). Additional support included start-up funds from the University of Minnesota Foundation and bridge funds from the Institute of Translational Neuroscience to S.L. Rakez Kayed was supported by National Institute of Health grants R01AG054025 and R01NS094557. Mai Suan Li was supported by Narodowe Centrum Nauki in Poland (grant 2019/35/B/ST4/02086) and the Department of Science and Technology, Ho Chi Minh City, Vietnam (grant 07/2019/H Đ-KHCNTT). Yifat Miller thanks the Israel Science Foundation, grant no. 532/15 and FP7-PEOPLE-2011-CIG, research grant no. 303741. Son Tung Ngo was supported by Vietnam National Foundation for Science & Technology Development (NAFOSTED) grant #104.99-2019.57. Research in the Ramamoorthy lab is supported by NIH (AG048934). Guanghong Wei acknowledges the financial support from the National Science Foundation of China (Grant Nos. 11674065 and 11274075) and National Key Research and Development Program of China (2016YFA0501702). Philippe Derreumaux acknowledges the support of the Université de Paris, ANR SIMI7 GRAL 12-BS07-0017, “Initiative d’Excellence” program from the French State (Grant “DYNAMO”, ANR- 11-LABX-0011-01) and the CNRS Institute of Chemistry (INC) for two years of délégation in 2017 and 2018. We thank the reviewers for their insightful comments and suggestions.

Publisher Copyright:
© 2021 American Chemical Society


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