Nejvíce citovaný článek - PubMed ID 37733610
Nonaqueous Ion Pairing Exemplifies the Case for Including Electronic Polarization in Molecular Dynamics Simulations
Glycosaminoglycans (GAGs) are negatively charged polysaccharides found on cell surfaces, where they regulate transport pathways of foreign molecules toward the cell. The structural and functional diversity of GAGs is largely attributed to varied sulfation patterns along the polymer chains, which makes understanding their molecular recognition mechanisms crucial. Molecular dynamics (MD) simulations, thanks to their unmatched microscopic resolution, have the potential to be a reference tool for exploring the patterns responsible for biologically relevant interactions. However, the capability of molecular dynamics force fields used in biosimulations to accurately capture sulfation-specific interactions is not well established, partly due to the intrinsic properties of GAGs that pose challenges for most experimental techniques. In this work, we evaluate the performance of molecular dynamics force fields for sulfated GAGs by studying ion pairing of Ca2+ to sulfated moieties─N-methylsulfamate and methylsulfate─that resemble N- and O-sulfation found in GAGs, respectively. We tested available nonpolarizable (CHARMM36 and GLYCAM06) and explicitly polarizable (Drude and AMOEBA) force fields, and derived new implicitly polarizable models through charge scaling (prosECCo75 and GLYCAM-ECC75) that are consistent with our developed "charge-scaling" framework. The calcium-sulfamate/sulfate interaction free energy profiles obtained with the tested force fields were compared against reference ab initio molecular dynamics (AIMD) simulations, which serve as a robust alternative to experiments. AIMD simulations indicate that the preferential Ca2+ binding mode to sulfated GAG groups is solvent-shared pairing. Only our scaled-charge models agree satisfactorily with the AIMD data, while all other force fields exhibit poorer agreement, sometimes even qualitatively. Surprisingly, even explicitly polarizable force fields display a notable disagreement with the AIMD data, likely attributed to difficulties in their optimization and possible inherent limitations in depicting high-charge-density ion interactions accurately. Finally, the underperforming force fields lead to unrealistic aggregation of sulfated saccharides, which qualitatively disagrees with our understanding of the soft glycocalyx environment. Our results highlight the importance of accurately treating electronic polarization in MD simulations of sulfated GAGs and caution against over-reliance on currently available models without thorough validation and optimization.
- MeSH
- glykosaminoglykany * chemie MeSH
- kyseliny sulfonové chemie MeSH
- simulace molekulární dynamiky * MeSH
- sírany * chemie MeSH
- statická elektřina * MeSH
- vápník chemie MeSH
- Publikační typ
- časopisecké články MeSH
- Názvy látek
- glykosaminoglykany * MeSH
- kyseliny sulfonové MeSH
- sírany * MeSH
- sulfamic acid MeSH Prohlížeč
- vápník MeSH
prosECCo75 is an optimized force field effectively incorporating electronic polarization via charge scaling. It aims to enhance the accuracy of nominally nonpolarizable molecular dynamics simulations for interactions in biologically relevant systems involving water, ions, proteins, lipids, and saccharides. Recognizing the inherent limitations of nonpolarizable force fields in precisely modeling electrostatic interactions essential for various biological processes, we mitigate these shortcomings by accounting for electronic polarizability in a physically rigorous mean-field way that does not add to computational costs. With this scaling of (both integer and partial) charges within the CHARMM36 framework, prosECCo75 addresses overbinding artifacts. This improves agreement with experimental ion binding data across a broad spectrum of systems─lipid membranes, proteins (including peptides and amino acids), and saccharides─without compromising their biomolecular structures. prosECCo75 thus emerges as a computationally efficient tool providing enhanced accuracy and broader applicability in simulating the complex interplay of interactions between ions and biomolecules, pivotal for improving our understanding of many biological processes.
