Graph-Theoretic Analysis of Monomethyl Phosphate Clustering in Ionic Solutions

Area of Science:

• Computational chemistry and biophysics
• Solution chemistry and molecular interactions

Background:

• Understanding molecular clustering is crucial for various chemical and biological processes.
• Monomethyl phosphate dianion (MMP^2-) is a relevant model for biological molecules like phosphoinositides.

Purpose of the Study:

• To investigate how different cations and their combinations influence MMP^2- clustering in aqueous solutions.
• To explore the underlying mechanisms and potential synergistic effects of cation mixtures on clustering.

Main Methods:

• All-atom molecular dynamics simulations were employed to model cation-MMP^2- interactions.
• Graph-theoretic analysis was used to quantify cluster formation and stability.
• Fourier transform infrared spectroscopy confirmed simulation findings.

Main Results:

• Calcium (Ca²⁺) alone promotes stable and large MMP^2- clusters.
• Potassium (K⁺) alone does not induce significant clustering.
• Mixtures of Ca²⁺ and K⁺ exhibit a synergistic effect, leading to larger clusters and longer link lifetimes.
• This synergy is sensitive to Ca²⁺-phosphorus oxygen interactions and cluster hydration.

Conclusions:

• Cation composition critically dictates MMP^2- clustering behavior in solution.
• The observed synergistic clustering effect of Ca²⁺/K⁺ mixtures provides insights into complex ionic interactions.
• This study offers a foundation for understanding cation-dependent clustering of biologically relevant phosphoinositides in cell membranes.