Computational Chemistry Studies of Terpene Synthase

On a typical morning, I usually grab an orange and get a cinnamon bagel from coffee shop for breakfast. Around 11 am, I have an apple as a snack. I normally get the steamed broccoli in the dining hall for lunch. In the evening on my way back home, sometimes I can smell cannabis on the highway — everything I just mentioned contains terpene. Citrus fruits usually have a large amount of limonene. Cinnamon, broccoli, and some other spices possess β-caryophyllene, which has anti-diabetic potential. Cannabis has a variety of different terpenes that depend on the specific strain, such as myrcene, β-caryophyllene and α-humulene.

 In fact, terpenes, also known as terpenoids, are the largest class of natural products. There are over 80,000 such compounds in the greater family found in nature. They are everywhere in our daily life: perfumes, food flavors, antibiotics, biofuel, essential oils and so many other things that are important to our life. The most famous terpene is the anti-cancer chemotherapy drug Paclitaxel (Taxol). Many terpenes have pharmaceutical properties and currently are being used in clinical practices.

Terpenes are mostly hydrocarbon structures. The basic building block of terpene is a five-carbon structure known as isoprene. This five-carbon unit can be ligated to form 10, 15, 20, 25 or more carbon terpene structures. [Figure 1] These hydrocarbon structures can then undergo a series of rearrangements and ring closure reactions to form a variety of terpene products. Additional functional groups can also be added to the foundational hydrocarbon structure to get terpenoids.

Terpenes are synthesized by a specific class of enzymes - terpene synthases. The formation of terpenes catalyzed by terpene synthases is very interesting, mechanistically. Terpene synthase activity can be summarized in two phrases: 1) One fold, many products and 2) One enzyme, multi-steps (reactions). Thousands of terpene scaffolds are synthesized from only a few simple, acyclic polyprenyl diphosphate precursors. These precursors undergo multistep, complex carbocationic reactions catalyzed by terpene synthases. Class I terpene synthases catalyze these reactions by generating carbocation intermediates via ionization reaction. Despite the fact that the products have large chemical and structural diversity, all class I terpene synthases share the same alpha-helical fold. [Figure 2]

My research [Figure 3] is focused on enzyme engineering of terpene synthases, which means we’ll make some modifications of the terpene synthase protein sequence and engineer the enzyme to produce novel compounds that are not found in nature, such as pharmaceuticals or research tools. In order to do this, it’s important to obtain the structure of the naturally occurring enzyme to be modified. It’s also important to understand the mechanism and the structure-function relationship for this enzyme family. Both tasks can be challenging, yet interesting, for computational chemists.

First of all, obtaining the structure of a terpene synthase is not simple. The most common way to get a  target protein structure is from X-ray crystallography. However, sometimes it can be difficult to crystallize the target protein of interest and determine the structure. In this case, we can use computational methods to predict target protein structure. A common technique is comparative protein modeling; previously solved crystal structures are used as a starting point to predict protein structure for a target sequence. These structures are called templates. Templates are chosen based on sequence similarity to the target protein of interest. Under the assumption that two homologous proteins may share similar folds, the structure of the target protein can be predicted. With AlphaFold and many other powerful protein structure prediction tools becoming available, it’ll be much easier to predict protein structure with an atomic accuracy.

Secondly, due to the nature of the terpene synthase enzyme family, it can be challenging to predict the binding orientation of the terpene substrate or how this substrate is sitting within the terpene synthase enzyme. This information is crucial for enzyme engineering later. To understand how the terpene molecule is interacting with the terpene synthase, different methods can be applied. For example, small molecule - protein interaction can be simulated in silico with molecular modeling and docking, which is one of the most frequently used methods. The binding orientation can be predicted and evaluated with certain criteria including scoring functions and chemical knowledge of the enzyme family. Once the binding orientation is predicted, one can design the protein sequence to produce novel products. This is first carried out computationally, then the proposed sequences can be tested experimentally. One example for such study is ent-kaurene synthase, an enzyme that produces a 20-carbon terpene, ent-kaurene. Previous studies have shown that a single-residue switch, or a single residue mutation of the ent-kaurene synthase enzyme will alter the product outcome completely. Replacing the key aliphatic residue, alanine to serine, “short-circuits” the enzymatic activity. Computational studies have indicated that this serine residue may act as a catalytic base. With this knowledge, reengineering such an enzyme becomes possible.

To summarize, terpenes and related derivatives are one of the largest classes of compounds in nature. Understanding the mechanisms for terpene synthases can be challenging and rewarding. In future studies, enzyme engineering and metabolic engineering of terpene synthases and related metabolic pathways will hopefully help us to make more valuable terpene products that will benefit our daily life.

References   

Booth, J. K., and Bohlmann, J. (2019) Terpenes in Cannabis sativa – From plant genome to humans. Plant Sci. 284, 67–72.

Christianson, D. W. (2017) Structural and Chemical Biology of Terpenoid Cyclases. Chem. Rev. 117, 11570–11648.

Jia, M., Zhang, Y., Siegel, J. B., Tantillo, D. J., and Peters, R. J. (2019) Switching on a Nontraditional Enzymatic Base - Deprotonation by Serine in the ent-Kaurene Synthase from Bradyrhizobium japonicum. ACS Catal. 9, 8867–8871.