Diosgenin reduces β-sheet content in mutated α-syn aggregation: Insights from conformational dynamics at intracellular and extracellular neuronal salt concentrations
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引用次数: 0
Abstract
Parkinson's disease (PD) is marked by the aggregation of α-syn protein and its mutant forms, such as A30P, A53T, and E46K, which make the protein more prone to misfolding and aggregation, leading to neuronal cell death. This study explores the potential of Diosgenin, a phytoconstituent identified through ADMET predictions, to inhibit α-syn aggregation at both extracellular (0.145 M) and intracellular (0.015 M) salt concentrations. Molecular dynamics (MD) simulation revealed that Diosgenin stabilizes α-syn mutants by inducing conformational changes that reduce β-sheet content, a key factor in aggregation. The salt concentration influenced the structural dynamics, with higher salt levels generally promoting more compact and stable conformations. Principal component analysis (PCA) and free energy landscapes further confirmed the enhanced stability of the Diosgenin-bound α-syn mutants. The outcomes of the study suggest that Diosgenin could serve as a promising therapeutic agent for mitigating PD progression by targeting the aggregation of α-syn mutants and reducing its β-sheet content at intracellular and extracellular neuronal salt concentration.
期刊介绍:
The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design.
As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.