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https://hdl.handle.net/10216/122230| Author(s): | Zsuzsa Sárkány Fernando Rocha Ana M. Damas Sandra Macedo Ribeiro Pedro M. Martins |
| Title: | Chemical Kinetic Strategies for High-Throughput Screening of Protein Aggregation Modulators |
| Issue Date: | 2019 |
| Abstract: | Insoluble aggregates staining positive to amyloid dyes are known histological hallmarks of different neurodegenerative disorders and of type II diabetes. Soluble oligomers are smaller assemblies whose formation prior to or concomitant with amyloid deposition has been associated to the processes of disease propagation and cell death. While the pathogenic mechanisms are complex and differ from disease to disease, both types of aggregates are important biological targets subject to intense investigation in academia and industry. Here we review recent advances in the fundamental understanding of protein aggregation that can be used on the development of anti-amyloid and anti-oligomerization drugs. Specifically, we pinpoint the chemical kinetic aspects that should be attended during the development of high-throughput screening assays and in the hit validation phase. The strategies here devised are expected to establish a connection between basic research and pharmaceutical innovation. |
| DOI: | 10.1002/asia.201801703 |
| URI: | https://hdl.handle.net/10216/122230 |
| Related Information: | info:eu-repo/grantAgreement/Comissão de Coordenação e Desenvolvimento Regional do Norte/P2020|Norte2020-Projetos Integrados ICDT/NORTE-01-0145-FEDER-000005/LEPABE-2-ECO-INNOVATION/LEPABE-2-ECO-INNOVATION info:eu-repo/grantAgreement/FCT - Fundação para a Ciência e Tecnologia/Projetos Estratégicos/UID/EQU/00511/2013 - POCI-01-0145-FEDER-006939/Laboratório de Engenharia de Processos, Ambiente, Biotecnologia e Energia/LEPABE |
| Document Type: | Artigo em Revista Científica Internacional |
| Rights: | openAccess |
| Appears in Collections: | FEUP - Artigo em Revista Científica Internacional |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| 351166.pdf | 1.75 MB | Adobe PDF | ![]() View/Open |
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