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

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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.