EAPSI: Predicting mechanisms for the formation of terpenes - natural products from plants

EAPSI：萜烯（植物天然产物）形成的预测机制

• 批准号: 1414996
• 负责人: Brandi Hudson
• 金额: $ 0.51万
• 依托单位: Hudson Brandi M
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1414996&HistoricalAwards=false
• 关键词: EAPSI; Predicting; mechanisms; formation; terpenes

Natural organisms produce thousands of organic molecules (natural products), but how and why specific molecules are produced remains unknown. Terpenes constitute a large class of complex natural products whose members have found applications in perfumery, medicine, food and wine flavoring, pesticides, among others. Understanding the chemical mechanisms by which terpenes are formed will allow for these structures to be produced in the laboratory on demand. This project will be conducted at Kyoto University, Japan with Dr. Keiji Morokuma, the developer of a new computational tool that will be used to connect molecular structure to natural product production. The limits of this new methodology will be tested on a naturally occurring terpene precursor, then it will be applied to mapping out the pathways for the formation of non-natural, designed terpene derivatives. The global reaction route mapping (GRRM) strategy using the artificial force induced reaction (AFIR) method will be integrated with quantum chemical calculations on intermediates and transition state structures (TSSs) in terpene-forming pathways. Mechanistic studies on chemical reactions rely heavily on finding TSSs between two intermediates. The GRRM/AFIR method is an alternative approach to locating TSSs--often the most challenging aspect of a computational reaction mechanism investigation--opening the door to pathways that may be overlooked by humans. Of special interest is the effect of methylation on carbocation precursors to terpenes. Methylation of biologically relevant compounds has been shown to have profound effects on function and reactivity. The GRRM/AFIR method will allow the prediction of reactivity of substrates that are not yet known. Furthermore, GRRM/AFIR method for mapping chemical reactions and biosynthetic pathways will be applied to advance blind and visually impaired students' ability to search for TSSs independently and accessibly, as locating TSSs manually currently requires sighted assistance. This NSF EAPSI award is funded in collaboration with the Japan Society for the Promotion of Science.

自然生物产生成千上万的有机分子（天然产物），但如何以及为什么产生特定的分子仍然是未知的。萜类化合物是一类复杂的天然产物，其成员已在香料、医药、食品和酒类调味品、农药等方面得到应用。了解萜烯形成的化学机制将允许这些结构在实验室中按需生产。该项目将在日本京都大学与Keiji Morokuma博士一起进行，他是一种新的计算工具的开发者，该工具将用于将分子结构与天然产物生产联系起来。这种新方法的局限性将在天然存在的萜烯前体上进行测试，然后将其应用于绘制非天然的、设计的萜烯衍生物的形成途径。使用人工力诱导反应（AFIR）方法的全局反应路线映射（GRRM）策略将与量子化学计算相结合，对形成term的途径中的中间体和过渡态结构（TSS）进行计算。化学反应机理的研究在很大程度上依赖于在两个中间体之间找到TSS。GRRM/AFIR方法是定位TSS的另一种方法-通常是计算反应机制研究中最具挑战性的方面-为人类可能忽略的途径打开了大门。特别感兴趣的是甲基化对萜烯的碳阳离子前体的影响。生物相关化合物的甲基化已被证明对功能和反应性具有深远的影响。GRRM/AFIR方法将允许预测尚不知道的底物的反应性。此外，GRRM/AFIR方法将用于绘制化学反应和生物合成途径，以提高盲人和视障学生独立和无障碍地搜索TSS的能力，因为目前手动定位TSS需要视力帮助。这个NSF EAPSI奖是与日本科学促进协会合作资助的。