Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin-Madison , Madison, Wisconsin 53706-1322, United States.
Langmuir. 2016 Jul 12;32(27):7009-22. doi: 10.1021/acs.langmuir.6b01582. Epub 2016 Jun 29.
Understanding the molecular structural and energetic basis of the interactions between peptides and inorganic surfaces is critical to their applications in tissue engineering and biomimetic material synthesis. Despite recent experimental progresses in the identification and functionalization of hydroxyapatite (HAP)-binding peptides, the molecular mechanisms of their interactions with HAP surfaces are yet to be explored. In particular, the traditional method of molecular dynamics (MD) simulation suffers from insufficient sampling at the peptide-inorganic interface that renders the molecular-level observation dubious. Here we demonstrate that an integrated approach combining bioinformatics, MD, and metadynamics provides a powerful tool for investigating the structure-activity relationship of HAP-binding peptides. Four low charge density peptides, previously identified by phage display, have been considered. As revealed by bioinformatics and MD, the binding conformation of the peptides is controlled by both the sequence and the amino acid composition. It was found that formation of hydrogen bonds between lysine residue and phosphate ions on the surface dictates the binding of positively charged peptide to HAP. The binding affinities of the peptides to the surface are estimated by free energy calculation using parallel-tempering metadynamics, and the results compare favorably to measurements reported in previous experimental studies. The calculation suggests that the charge density of the peptide primarily controls the binding affinity to the surface, while the backbone secondary structure that may restrain side chain orientation toward the surface plays a minor role. We also report that the application of enhanced-sampling metadynamics effects a major advantage over the steered MD method by significantly improving the reliability of binding free energy calculation. In general, our novel integration of diverse sampling techniques should contribute to the rational design of surface-recognition peptides in biomedical applications.
了解肽与无机表面相互作用的分子结构和能量基础对于它们在组织工程和仿生材料合成中的应用至关重要。尽管最近在鉴定和功能化羟磷灰石（HAP）结合肽方面取得了实验进展，但它们与 HAP 表面相互作用的分子机制仍有待探索。特别是，传统的分子动力学（MD）模拟方法在肽-无机界面的采样不足，这使得分子水平的观察结果值得怀疑。在这里，我们证明了结合生物信息学、MD 和元动力学的综合方法为研究 HAP 结合肽的结构-活性关系提供了强大的工具。我们考虑了以前通过噬菌体展示鉴定的四个低电荷密度肽。通过生物信息学和 MD 揭示，肽的结合构象既受序列又受氨基酸组成的控制。发现赖氨酸残基与表面上的磷酸离子之间形成氢键决定了带正电荷的肽与 HAP 的结合。使用平行温度元动力学进行自由能计算来估计肽与表面的结合亲和力，结果与以前的实验研究报告的测量结果相当。计算表明，肽的电荷密度主要控制与表面的结合亲和力，而可能限制侧链朝向表面取向的骨架二级结构则起次要作用。我们还报告说，增强采样元动力学的应用通过显著提高结合自由能计算的可靠性，相对于导向 MD 方法具有显著优势。总的来说，我们对各种采样技术的新颖整合应该有助于在生物医学应用中合理设计表面识别肽。
