Implicit solvent simulations of DPC micelle formation
Implicit solvent simulations of DPC micelle formation
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DOI：
10.1021/jp0516801
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发表时间：
2005-08-11
影响因子：
3.3
通讯作者：
Chen, Y
中科院分区：
文献类型：
--
作者：
Lazaridis, T;Mallik, B;Chen, Y
根据蛋白质的EEF1溶剂化模型的精神，通过对表面活性剂的原子细节处理和对溶剂的隐式处理来模拟十二烷基磷脂胆碱（DPC）胶束的形成。DPC原子的溶剂化参数是从蛋白质中类似原子的溶剂化参数继承而来的。为了获得与实验一致的聚合数，需要对头群的参数进行轻微调整。对960个不同浓度的DPC分子进行了分子动力学模拟，得到了聚集数、胶束大小分布和CMC。在20 mM的浓度下，我们得到的聚合数为53-56，CMC为1.25 mM，与实验值接近。在100mm时，聚合数增加到90。对不同大小胶束的模拟表明，表面活性剂分子的有效能量最初是聚集数的递减函数，但稳定在60分子左右。范德华项和非极性基团的溶解有助于胶束化，而极性基团的溶解则相反。根据有效能和自由能之差（由CMC计算），估计每个单体的平动熵和旋转熵对自由能的贡献约为7千卡/摩尔。这里得到的胶束比在显式水模拟中得到的胶束更不规则。这种建模方法允许长时间研究较大的表面活性剂聚集体，并提取热力学信息和结构信息。
The formation of micelles by dodecylphosphocholine (DPC) is modeled by treating the surfactants in atomic detail and the solvent implicitly, in the spirit of the EEF1 solvation model for proteins. The solvation parameters of the DPC atoms are carried over from those of similar atoms in proteins. A slight adjustment of the parameters for the headgroup was found necessary for obtaining an aggregation number consistent with experiment. Molecular dynamics simulations of 960 DPC molecules at different concentrations are used to obtain the aggregation number, the micelle size distribution, and the CMC. At 20 mM concentration we obtain an aggregation number of 53-56 and a CMC of 1.25 mM, values close to the experimental ones. At 100 MM the aggregation number increases to 90. Simulations of individual micelles of varying size show that the effective energy per surfactant molecule is initially a decreasing function of aggregation number but stabilizes at about 60 molecules. The van der Waals term and the desolvation of nonpolar groups contribute to micellization, whereas the desolvation of polar groups opposes it. From the difference between the effective energy and the free energy (calculated from the CMC), the translational and rotational entropy contributions to the free energy are estimated at about 7 kcal/mol per monomer. The micelles obtained here are more irregular than those obtained in explicit water simulations. This modeling approach allows the study of larger surfactant aggregates for longer times and the extraction of thermodynamic in addition to structural information.