Atomistic Details of Peptide Reversed-Phase Liquid Chromatography from Molecular Dynamics Simulations

化学 乙腈 恐溶剂的 洗脱 甲酸 色谱法 反相色谱法 分子动力学 水溶液 亲水作用色谱法 解吸 高效液相色谱法 有机化学 分子 计算化学 吸附 生物化学
作者
Pablo M. Scrosati,Lars Konermann
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (7): 3892-3900 被引量:6
标识
DOI:10.1021/acs.analchem.2c05667
摘要

Peptide separations by reversed-phase liquid chromatography (RPLC) are an integral part of bottom-up proteomics. These separations typically employ C18 columns with water/acetonitrile gradient elution in the presence of formic acid. Despite the widespread use of such workflows, the exact nature of peptide interactions with the stationary and mobile phases is poorly understood. Here, we employ microsecond molecular dynamics (MD) simulations to uncover details of peptide RPLC. We examined two tryptic peptides, a hydrophobic and a hydrophilic species, in a slit pore lined with C18 chains that were grafted onto SiO2 support. Our simulations explored peptide trapping, followed by desorption and elution. Trapping in an aqueous mobile phase was initiated by C18 contacts with Lys butyl moieties. This was followed by extensive anchoring of nonpolar side chains (Leu/Ile/Val) in the C18 layer. Exposure to water/acetonitrile triggered peptide desorption in a stepwise fashion; charged sites close to the termini were the first to lift off, followed by the other residues. During water/acetonitrile elution, both peptides preferentially resided close to the pore center. The hydrophilic peptide exhibited no contacts with the stationary phase under these conditions. In contrast, the hydrophobic species underwent multiple transient Leu/Ile/Val binding interactions with C18 chains. These nonpolar interactions represent the foundation of differential peptide retention, in agreement with the experimental elution behavior of the two peptides. Extensive peptide/formate ion pairing was observed in water/acetonitrile, particularly at N-terminal sites. Overall, this work uncovers an unprecedented level of RPLC molecular details, paving the way for MD simulations as a future tool for improving retention prediction algorithms and for the design of novel column materials.
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