Collaborative Research: Novel Computational Tools to Predict Anionic Pesticide and Pharmaceutical Sorption to Soil Oxides

合作研究：预测阴离子农药和药物对土壤氧化物吸附的新型计算工具

• 批准号: 1604305
• 负责人: Allison MacKay
• 金额: $ 25.03万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1604305&HistoricalAwards=false
• 关键词: Collaborative; Research; Novel; Computational; Tools

1604305 / 1603755 / 1604165MacKay / Vasudevan / JohnstonThe last decade has witnessed a radical shift in the prioritization of environmental contaminants. No longer is our primary concern non-polar compounds that persist and bioaccumulate, but the inventory of organic contaminants has expanded greatly to include many polar and ionic compounds with potential adverse ecotoxicological effects. This study offers an innovative approach to adapt computational chemical tools to the prediction of organic ligand sorption to metal oxides.The proposed approach represents a transformative advance in the quantitative a priori prediction of sorption coefficients for polar and ionic compounds in the environment. The integration of molecular dynamics calculations to obtain quantum mechanics measures of van der Waals, electrostatic energies and solvation effects overcomes the challenge of deconvoluting coupled structure effects from experimental measures of sorption energies alone, is at the current state of the science. Furthermore, other related sorption problems provide opportunity to expand Linear Interaction Energy approximation techniques because environmental sorbent characteristics are more generalizable than protein binding site characteristics. The overarching hypothesis of the project is: that changes in organic ligand structure by the addition/removal of non-ligand group substituents impart regular changes in sorption free energy as a result of coupled hydrophobic, electronic and proximity (i.e., steric and chelation) effects that are in turn mediated by solvent effects. The ultimate goal is to quantitatively describe organic ligand sorption to oxides as a function of specific sorbate structure criteria. A novel approach is used to identify structural criteria by bridging well-established experimental techniques with innovations in computationally relevant environmental surface chemistry, and by using the representative soil oxide, goethite. Task 1: The goethite force field will be fine-tuned using density functional theory to determine accurate compound conformations for a library of test sorbates. The chosen library includes sorbates with incremental changes in structure that allow us to identify the influence of specific ligand and non-ligand structural moieties. Computational efforts will be validated by infrared spectra to delineate binding mechanisms and transmission electron microscopy to identify relevant crystal faces. Quantum mechanics calculations will be used to calculate free energies of the inner sphere complexation reaction. Task 2: Experimental measures of sorption energies, infrared spectra and goethite measures will be obtained for test sorbates sorbed to high purity goethite. Task 3: The Linear Interaction Energy approximation will be used with molecular dynamics simulations and Task 1 force fields and inner sphere binding energies to calculate van der Waals and electrostatic contributions to overall sorption free energies. Linear Interaction Energy offers significant reductions in computational cost because molecular dynamics simulations are conducted only for the bound and unbound states. van der Waals and electrostatic energies will be regressed against experimental measures of sorption free energies to generate a predictive model for sorption coefficients. Findings from Tasks 1-3 will be integrated to identify how specific structural features can be linked to regular changes in van der Waals and electrostatic energies, thereby indicating structure-sorption relationships relevant to quantitative models. The PIs will mentor graduate and undergraduate researchers through the processes of experimental design, manuscript preparation and national professional society presentations. They will also work closely with high school students and teachers to introduce sorption concepts into public education with hands-on demonstration modules of everyday applications: home drinking water treatment and pesticide application. The PIs will continue their committed record of engaging student researchers from groups underrepresented in the sciences and engineering.

在过去的十年中，环境污染物的优先级发生了根本性的变化。我们主要关注的不再是持续存在和生物积累的非极性化合物，而是有机污染物的清单已经大大扩大，包括许多具有潜在不利生态毒理学影响的极性和离子化合物。这项研究提供了一种创新的方法，使计算化学工具适应于预测有机配体对金属氧化物的吸附。提出的方法代表了环境中极性和离子化合物吸附系数的定量先验预测的革命性进步。将分子动力学计算集成到范德瓦尔斯、静电能和溶剂化效应的量子力学测量中，克服了仅从吸附能的实验测量中获得反卷积耦合结构效应的挑战，是目前的科学现状。此外，其他相关的吸附问题提供了扩展线性相互作用能近似技术的机会，因为环境吸附剂的特性比蛋白质结合位点的特性更普遍。该项目的首要假设是：通过添加/去除非配基取代基来改变有机配体结构，从而导致吸附自由能的规则变化，这是由于疏水、电子和邻近（即空间和螯合）效应耦合的结果，而这些效应又由溶剂效应介导。最终目标是定量描述有机配体对氧化物的吸附作为特定山梨酸结构标准的函数。通过将成熟的实验技术与计算相关的环境表面化学的创新结合起来，并使用具有代表性的土壤氧化物针铁矿，采用了一种新的方法来确定结构标准。任务1：将使用密度泛函理论对针铁矿力场进行微调，以确定测试矿石库的精确复合构象。所选择的文库包括具有结构增量变化的sorbates，使我们能够识别特定配体和非配体结构部分的影响。计算工作将通过红外光谱来确定结合机制，并通过透射电子显微镜来识别相关的晶体面。量子力学计算将用于计算内球络合反应的自由能。任务2：对高纯度针铁矿进行吸附试验，获得吸附能实验测量、红外光谱和针铁矿测量。任务3：线性相互作用能近似将与分子动力学模拟和任务1的力场和内球结合能一起使用，以计算范德华和静电对总吸附自由能的贡献。线性相互作用能提供了显著降低计算成本，因为分子动力学模拟只进行了束缚和非束缚状态。范德华能和静电能将对吸附自由能的实验测量进行回归，以产生吸附系数的预测模型。将整合任务1-3的发现，以确定特定的结构特征如何与范德华和静电能的规律变化联系起来，从而表明与定量模型相关的结构-吸附关系。pi将指导研究生和本科生的研究人员完成实验设计、手稿准备和国家专业协会报告的过程。他们还将与高中学生和教师密切合作，通过日常应用的实践示范模块，将吸附概念引入公共教育：家庭饮用水处理和农药应用。ppi将继续保持其一贯的记录，吸引来自科学和工程领域代表性不足的群体的学生研究人员。