Amyloids are proteins which exist in the form of insoluble aggregates and possess a characteristic cross-beta structure. The formation of amyloid aggregates can be seen during several pathological processes in humans, including neurodegenerative diseases, diabetes, and systemic amyloidoses. Despite their infamous association with the previously mentioned conditions, amyloids can also serve a functional role in biological systems. For example, Pmel17, which is involved in melanin polymerization in mammalian cells, resembles an amyloid structure, and some peptide hormones are also known to be stored in amyloid form in secretory granules of the endocrine system [1]. Thus, studying amyloids as functional proteins may aid in both determining targets for the treatment of pathological conditions and in understanding their unique role in the organism. The analysis of amyloid-like properties requires a comprehensive approach using bioinformatic prediction, which can later be verified using bacterial and yeast systems as well as various biochemical tests. The object of this study is the protein COL2A1, better known as type II collagen. This type of collagen forms the basis of cartilage tissue and its mutant form can cause diseases known as collagenopathies. This protein possesses some distinctive features characteristic of amyloids. These features include Congo red staining and a tendency to form fibrillar structures. In addition, the possibility of it forming amyloid structures was predicted for the third isoform of type II collagen via the ArchCandy program. In this work, we present data on the investigation of COL2A1’s amyloid properties in a C-DAG system [2] and a yeast model [3]. Currently, additional studies are being conducted to obtain the protein in a bacterial system to assess its biochemical properties.
Author Contributions
Conceptualization A.A.R.; data acquisition and formal analysis, A.B., A.A.Z. and M.V.R.; supervision, A.A.R., funding acquisition, A.A.R., writing—review and editing, A.B. and A.A.R. All authors have read and agreed to the published version of the manuscript.
Funding
This research was supported by St. Petersburg State University (project No. 95444727).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
References
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