Instituto de Química de Recursos Naturales, Universidad de Talca, Avenida Lircay S/N, Talca, Chile 3460000.
Departamento de Ciencias Químicas, Facultad de Ciencias Exactas, Universidad Andres Bello, Sede Concepción, Autopista Concepción-Talcahuano 7100, Talcahuano, Chile 4300866.
J Chem Inf Model. 2021 Apr 26;61(4):2048-2061. doi: 10.1021/acs.jcim.0c01446. Epub 2021 Mar 30.
Nanoscale molecularly imprinted polymers (nanoMIPs) are powerful molecular recognition tools with broad applications in the diagnosis, prognosis, and treatment of complex diseases. In this work, fully atomistic molecular dynamics (MD) simulations are used to assist the design of nanoMIPs with recognition capacity toward l-fucose and d-mannose as prototype disease biomarkers. MD simulations were conducted on prepolymerization mixtures containing different molar ratios of the monomers -isopropylacrylamide (NIPAM), methacrylamide (MAM), and (4-acrylamidophenyl)(amino)methaniminium acetate (AB) and fixed molar ratios of the cross-linker ethylene glycol dimethacrylate (EGDMA) in explicit acetonitrile as the porogenic solvent. Prepolymerization mixtures containing ternary mixtures of NIPAM (50%), MAM (25%), and AB (25%) exhibit the best imprinting potential for both l-fucose and d-mannose, as they maximize (i) the stability of template-monomer plus template-cross-linker interactions, (ii) the number of functional monomers plus cross-linkers organized around the template, and (iii) the number of hydrogen bonds participating in template recognition. The studied prepolymerization mixtures exhibit an overall increased recognition capacity toward d-mannose over l-fucose, which is attributed to the higher hydrogen-bonding capacity of the former template. Our results are valuable to guide the synthesis of efficient nanoMIPs for sugar recognition and provide a computational framework extensible to any other template, monomer, or cross-linker combination, thus constituting a promising strategy for the rational design of molecularly imprinted materials.
纳米尺度分子印迹聚合物（nanoMIPs）是一种强大的分子识别工具，在复杂疾病的诊断、预后和治疗中有广泛的应用。在这项工作中，我们使用全原子分子动力学（MD）模拟来辅助设计具有识别能力的 nanoMIPs，以原型疾病生物标志物 l-岩藻糖和 d-甘露糖作为模板。MD 模拟在预聚合混合物上进行，该混合物含有单体 -异丙基丙烯酰胺（NIPAM）、甲基丙烯酰胺（MAM）和（4-丙烯酰胺基苯）（氨基）甲烷亚胺乙酸盐（AB）的不同摩尔比，以及固定摩尔比的交联剂乙二醇二甲基丙烯酸酯（EGDMA），在明确的乙腈中作为致孔溶剂。含有 NIPAM（50%）、MAM（25%）和 AB（25%）的三元混合物的预聚合混合物对 l-岩藻糖和 d-甘露糖表现出最佳的印迹潜力，因为它们最大化了：（i）模板-单体加模板-交联剂相互作用的稳定性；（ii）围绕模板组织的功能单体加交联剂的数量；（iii）参与模板识别的氢键数量。研究的预聚合混合物对 d-甘露糖的整体识别能力高于 l-岩藻糖，这归因于前者模板更高的氢键结合能力。我们的结果对指导高效 nanoMIPs 的合成具有指导意义，用于糖的识别，并提供了一种可扩展到任何其他模板、单体或交联剂组合的计算框架，因此构成了合理设计分子印迹材料的有前途的策略。
