Discovering Effective Chiral Dipeptides against Aβ(1–42) Aggregation by the Computational Screening Strategy
The β-sheet-breaker (BSB) peptides inhibiting amyloidogenic aggregation have been extensively studied. However, the inhibition efficacy of ultrashort chiral dipeptides remains inadequately understood. In this study, we proposed a computational screening strategy to identify chiral dipeptides as BSB with optimal antiaggregation performance against Aβ(1-42) aggregation. We constructed a complete dipeptide library encompassing all possible chiral sequence arrangements and then filtered the library by cascaded molecular docking-molecular dynamics (MD) simulation. Our screening strategy discovered dipeptide <sup>D</sup>W<sup>D</sup>P (superscript for chirality) that displayed strong interactions with Aβ fibrils and inhibitory effects on Aβ aggregation, validated by subsequent experiments. Mechanistic investigation by both MD and replica-exchange molecular dynamics (REMD) simulations revealed that <sup>D</sup>W<sup>D</sup>P interacts with Aβ by hydrophobic contacts and hydrogen bonds and thus inhibits Aβ intermolecular contacts and salt bridge formation, therefore inhibiting Aβ aggregation and disrupting Aβ aggregates. Totally, our strategy presents a viable approach to discover potential dipeptides with effective antiaggregation ability as potential therapeutic agents for Alzheimer's disease.
Authors
- Wenhui Shi (ORCID: https://orcid.org/0000-0002-9903-2138)
- Rongxin Su (ORCID: https://orcid.org/0000-0001-9778-9113)
- Yuefei Wang (ORCID: https://orcid.org/0000-0002-5736-7431)
- Shengping You (ORCID: https://orcid.org/0000-0003-3546-1555)
- Xin Peng (ORCID: https://orcid.org/0000-0003-1654-2130)
- Zixuan Wang (ORCID: https://orcid.org/0009-0009-9134-4952)
- Jiaxing Zhang (ORCID: https://orcid.org/0000-0003-4104-6657)
- Wei Dong Qi (ORCID: https://orcid.org/0000-0002-7378-1392)
- Wen Wang (ORCID: https://orcid.org/0000-0001-8392-3457)
Institutions
- Tianjin University (CN)
- Collaborative Innovation Center of Chemical Science and Engineering Tianjin (CN)
- State Key Laboratory of Chemical Engineering (CN)
Publication Details
- Journal
- ACS Chemical Neuroscience
- Published
- 2024-10-03
- DOI
- https://doi.org/10.1021/acschemneuro.4c00287
- Citations
- 2
- Primary Topic
- Chemical Synthesis and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.47
Funders
- National Natural Science Foundation of China
- Hebei Provincial Department of Bureau of Science and Technology
- Beijing Municipal Science and Technology Commission
- Tianjin Science and Technology Committee
- Tianjin Municipal Science and Technology Bureau