Effect of Salt Concentration on Structural Changes of Amyloid β

سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 46

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شناسه ملی سند علمی:

IBIS11_047

تاریخ نمایه سازی: 19 آذر 1402

چکیده مقاله:

Aggregation of amyloid (A ) has been associated with Alzheimer’s disease. Aggregation depends on two sets of factors, including the intrinsic features of polypeptides and the physicochemical environment (such as ionic strength and pH). The effect of ion strength on the propensity of aggregation and its morphology was supposed. here, we investigated the behavior of the A (۱۶-۲۲) peptide as a fibril-forming core at three di↵erent salt concentrations by a molecular dynamics simulation approach. The region of ۱۶ KLVFFAE۲۲ peptide of A ۴۲ (PDB: ۱Z۰Q) was retrieved as a starting structure. Molecular dynamic simulations were carried out using the AMBER۲۰ package with parameterization of ↵۱۹SB-OPC. Three systems, with ۰ mM (system I), ۳۰ mM (system II), and ۱۵۰ mM (system III) NaCl, were assigned. The length of the simulations was ۵۰ ns. CCPTRAJ has been employed for the analysis of the trajectories. Root mean square deviation (RMSD) of the peptide in system I had the least structural changes compared to the others and the lowest radius of gyration (Rg). The peptide in system I showed the least distance between K۱۶ and E۲۲. Moreover, this peptide had the most intramolecular hydrogen bonds that decreased by increasing the ionic strength of the solvent in other systems. Based on the RMSD, and Rg results, the peptide in system I was the most stable and compact structure since the terminal ends of the peptide had the highest tendency to interact with each other. Ions interact with the opposite charge residues and decrease hydrogen bonds and the energy of electrostatic intramolecular interaction of the peptide resulting in increasing in the flexibility of peptides. Our results are in agreement with previous studies that showed increasing ionic causes the stability of the peptide to decline. These findings could be useful for predicting aggregation

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نویسندگان

Maryam Ghorbaninia

University of isfahan

Shirin Doroudgar

University of arizona

Mohamad reza Ganjalikhany

University of isfahan