淀粉样纤维
纤维
淀粉样蛋白(真菌学)
堆积
计算生物学
蛋白质聚集
化学
淀粉样疾病
结构相似性
生物物理学
生物化学
生物
淀粉样β
医学
无机化学
疾病
有机化学
病理
作者
Stanislav A. Bondarev,M. V. Uspenskaya,Jeremy Y Leclercq,Théo Falgarone,Galina A. Zhouravleva,Andrey V. Kajava
标识
DOI:10.1016/j.jmb.2024.168437
摘要
Typically, amyloid fibrils consist of multiple copies of the same protein. In these fibrils, each polypeptide chain adopts the same β-arc-containing conformation and these chains are stacked in a parallel and in-register manner. In the last few years, however, a considerable body of data has been accumulated about co-aggregation of different amyloid-forming proteins. Among known examples of the co-aggregation are heteroaggregates of different yeast prions and human proteins Rip1 and Rip3. Since the co-aggregation is linked to such important phenomena as infectivity of amyloids and molecular mechanisms of functional amyloids, we analyzed its structural aspects in more details. An axial stacking of different proteins within the same amyloid fibril is one of the most common type of co-aggregation. By using an approach based on structural similarity of the growing tips of amyloids, we developed a computational method to predict amyloidogenic β-arch structures that are able to interact with each other by the axial stacking. Furthermore, we compiled a dataset consisting of 26 experimentally known pairs of proteins capable or incapable to co-aggregate. We utilized this dataset to test and refine our algorithm. The developed method opens a way for a number of applications, including the identification of microbial proteins capable triggering amyloidosis in humans. AmyloComp is available on the website: https://bioinfo.crbm.cnrs.fr/index.php?route=tools&tool=30.
科研通智能强力驱动
Strongly Powered by AbleSci AI