Ionic liquids inhibit the dynamic transition from α-helices to β-sheets in peptides

Abstract

Abnormalities in the transition between α-helices and β-sheets (α-β transition) may lead to devastating neurodegenerative diseases, such as Parkinson's syndrome and Alzheimer's disease. Ionic liquids (ILs) are potential drugs for targeted therapies against these diseases because of their excellent bioactivity and designability of ILs. However, the mechanism through which ILs regulate the α-β transition remains unclear. Herein, a combination of GPU-accelerated microsecond molecular dynamics simulations, correlation analysis, and machine learning was used to probe the dynamical α-β transition process induced by ILs of 1-alkyl-3-methylimidazolium chloride ([Cnmim]Cl) and its molecular mechanism. Interestingly, the cation of [Cnmim]+ in ILs can spontaneously insert into the peptides as free ions (n ≤ 10) and clusters (n ≥ 11). Such insertion can significantly inhibit the α-β, transition and the inhibiting ability for the clusters is more significant than that of free ions, where [C10mim]+ and [C12mim]+ can reduce the maximum β-sheet content of the peptide by 18.5% and 44.9%, respectively. Furthermore, the correlation analysis and machine learning method were used to develop a predictive model accounting for the influencing factors on the α-β transition, which could accurately predict the effect of ILs on the α-β transition. Overall, these quantitative results may not only deepen the understanding of the role of ILs in the α-β transition but also guide the development of the IL-based treatments for related diseases.

Keywords

• α-β transition
• Molecular dynamics simulation
• Ionic liquids
• Machine learning
• Membrane channel protein