Departamento de Ciencias Químicas, Facultad de Ciencias Exactas, Universidad Andres Bello. Autopista Concepción-Talcahuano, 7100, Talcahuano, Chile.
J Mol Model. 2024 Jul 15;30(8):266. doi: 10.1007/s00894-024-06069-x.
Molecularly imprinted polymers (MIPs) have promising applications as synthetic antibodies for protein and peptide recognition. A critical aspect of MIP design is the selection of functional monomers and their adequate proportions to achieve materials with high recognition capacity toward their targets. To contribute to this goal, we calibrated a molecular dynamics protocol to reproduce the experimental trends in peptide recognition of 13 pre-polymerization mixtures reported in the literature for the peptide toxin melittin.
Three simulation conditions were tested for each mixture by changing the box size and the number of monomers and cross-linkers surrounding the template in a solvent-explicit environment. Fully atomistic MD simulations of 350 ns were conducted with the AMBER20 software, with ff19SB parameters for the peptide, gaff2 parameters for the monomers and cross-linkers, and the OPC water model. Template-monomer interaction energies under the LIE approach showed significant differences between high-affinity and low-affinity mixtures. Simulation systems containing 100 monomers plus cross-linkers in a cubic box of 90 Å successfully ranked the mixtures according to their experimental performance. Systems with higher monomer densities resulted in non-specific intermolecular contacts that could not account for the experimental trends in melittin recognition. The mixture with the best recognition capacity showed preferential binding to the 13-26-α-helix, suggesting a relevant role for this segment in melittin imprinting and recognition. Our findings provide insightful information to assist the computational design of molecularly imprinted materials with a validated protocol that can be easily extended to other templates.
分子印迹聚合物（MIPs）作为蛋白质和肽识别的合成抗体具有广阔的应用前景。MIP 设计的一个关键方面是选择功能单体及其适当比例，以实现对目标具有高识别能力的材料。为了实现这一目标，我们校准了一种分子动力学方案，以再现文献中报道的 13 种预聚合混合物在肽毒素蜂毒素识别方面的实验趋势。
通过改变模板周围单体和交联剂的盒子大小和数量，对每种混合物的三种模拟条件进行了测试。在溶剂显式环境中，使用 AMBER20 软件进行了 350 ns 的全原子 MD 模拟，肽的 ff19SB 参数，单体和交联剂的 gaff2 参数，以及 OPC 水模型。LIE 方法下模板-单体相互作用能显示出高亲和力和低亲和力混合物之间的显著差异。在立方盒子中包含 100 个单体加交联剂的模拟系统成功地根据其实验性能对混合物进行了排序。单体密度较高的系统会导致非特异性分子间接触，无法解释蜂毒素识别的实验趋势。具有最佳识别能力的混合物显示出对 13-26-α-螺旋的优先结合，表明该片段在蜂毒素印迹和识别中具有重要作用。我们的研究结果提供了有见地的信息，以协助具有验证方案的分子印迹材料的计算设计，该方案可以很容易地扩展到其他模板。
