Modulation of Aβ1-42 Aggregation by a SARS-CoV-2 Protein Fragment.

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Malinda B Premathilaka,Ulrich H E Hansmann
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引用次数: 0

Abstract

A number of studies have pointed out the possibility that SARS-CoV-2 infections could trigger amyloid diseases such as Parkinson's disease or type II diabetes. In the present study, we probe this question for Alzheimer's disease, which is connected with the presence of amyloids rich in Aβ peptides. For this purpose, we study, by way of molecular dynamics simulations, the interaction between the fragment FKNIDGYFKI of the Spike protein with an Aβ1-42 monomer and two fibril models, one patient-derived and one synthetic. We find that the viral protein fragment appears to shift the ensemble of monomer conformations toward more aggregation-prone ones, and that fibril polymorphs found in patients with Alzheimer's disease appear to be more stabilized than synthetic fibrils. We discuss commonalities and differences in the modulation of amyloid formation by the viral protein fragments by comparing our results with previous studies of other amyloid-forming proteins.
SARS-CoV-2蛋白片段对a - β1-42聚集的调控
许多研究指出,新冠病毒感染有可能引发帕金森病或2型糖尿病等淀粉样蛋白疾病。在目前的研究中,我们探讨了阿尔茨海默病的这个问题,这与富含Aβ肽的淀粉样蛋白的存在有关。为此,我们通过分子动力学模拟研究了Spike蛋白片段FKNIDGYFKI与Aβ1-42单体和两种纤维模型(一种是患者衍生的,一种是合成的)之间的相互作用。我们发现病毒蛋白片段似乎将单体构象的集合转向更容易聚集的构象,并且在阿尔茨海默病患者中发现的纤维多态性似乎比合成原纤维更稳定。我们通过将我们的结果与先前对其他淀粉样蛋白形成的研究结果进行比较,讨论了病毒蛋白片段对淀粉样蛋白形成调节的共性和差异。
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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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