{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T05:53:22Z","timestamp":1780984402321,"version":"3.54.1"},"reference-count":49,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomolecules"],"abstract":"<jats:p>Amylin and amyloid \u03b2 belong to the same protein family and activate the same receptors. Amyloid \u03b2 levels are elevated in Alzheimer\u2019s disease. Recent studies have demonstrated that amylin-based peptides can reduce the symptoms of Alzheimer\u2019s disease in animal models. Replica exchange molecular dynamics simulation machine learning, as well as other computational analyses, were applied to improve the understanding of the amino acid residues in these amylin-based peptides. Comparisons were made between amylin, amylin-based peptides, and amyloid \u03b2. These studies converged on amylin residues 10Q, 28S, 29S, 30T, 31N, 32V, 33G, 34S, and 35N (residues 10 and 28\u201335) being ranked highest, meaning that they were the most likely to be involved in activating the same targets as amyloid \u03b2. Surprisingly, the amyloid \u03b2 signaling domain most closely matched amylin residues 29\u201335 in the simulated structures. These findings suggest important residues that are structurally similar between amylin and amyloid \u03b2 and are thus implicated in the activation of the amylin receptor.<\/jats:p>","DOI":"10.3390\/biom15010089","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T07:59:42Z","timestamp":1736409582000},"page":"89","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Structural Analysis of Amylin and Amyloid \u03b2 Peptide Signaling in Alzheimer\u2019s Disease"],"prefix":"10.3390","volume":"15","author":[{"given":"Longsheng","family":"Xie","sequence":"first","affiliation":[{"name":"School of Systems Biology, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Lockhart","sequence":"additional","affiliation":[{"name":"School of Systems Biology, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven R.","family":"Bowers","sequence":"additional","affiliation":[{"name":"School of Systems Biology, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmitri K.","family":"Klimov","sequence":"additional","affiliation":[{"name":"School of Systems Biology, George Mason University, Fairfax, VA 22030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3174-1007","authenticated-orcid":false,"given":"Mohsin Saleet","family":"Jafri","sequence":"additional","affiliation":[{"name":"School of Systems Biology, George Mason University, Fairfax, VA 22030, USA"},{"name":"Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,9]]},"reference":[{"key":"ref_1","unstructured":"Kumar, A., Sidhu, J., Goyal, A., and Tsao, J.W. 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