Download or read book Combining Quantum Mechanics Calculations with Molecular Modeling to Predict Enzyme Behavior written by Terrence Edward O'Brien and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 1 Sesquiterpenoids comprise a class of terpenoid natural products with thousands of compounds that are highly diverse in structure, generally containing a polycyclic carbon backbone that is constructed by a sesquiterpene synthase. However, for the vast majority of these enzymes the productive binding orientation of the intermediate carbocations has remained unclear. In this work, a method that combines quantum mechanics and computational docking is used to generate an all-atom model of every putative intermediate formed in the context of the enzyme active site for tobacco epi-aristolochene synthase (TEAS). This method identifies a single pathway that links the first intermediate to the last, enabling us to propose the first high-resolution model for the reaction intermediates in the active site of TEAS, providing testable predictions both experimentally and computationally. Chapter 2 For a variety of sesquiterpene synthases a neutral intermediate is made in the mechanism. This intermediate must then be re-ionized to restart the carbocation cascade of product formation, but the source of this protonation in the active site isn’t understood. Building on the models developed in our lab for epi-aristolochene synthase a variety of potential proton sources were examined explicitly, including an alternate cysteine (C440), a potential active site bound water and no constraint to any proton source at all were all examined. From these results a variety of point mutants were suggested and are being tested by our collaborator. Chapter 3 Terpene synthases is a family of enzyme which takes linear polyisoprenyl diphosphates and creates complex, polycyclic carbon backbones via a carbocation intermediates. To accommodate this chemistry, the active site are lines with alkyl and aromatic sidechain, which are thought to play a role in sequestering the reactive intermediates until the final product is made. This provides a unique challenge to modellers, as correctly predicting the correcting binding mode of a greasy substrate in a greasy pocket is a huge challenge. Here we report our answer to the said challenge: TerDockin (short for terpene docking). A recipe of protocols to help predict the carbon skeletons orientaion in the active site relative to the diphosphate group. Using this recipe for bornyl diphosphate synthase has allowed the method to reproduce three known exprimental outcomes, exclude very similar products the enzyme doesn’t produce and is partially consistent with previous modelling studies. This system serves as a model to illustrate the potential power of TerDockin as a starting point for other higher theory (i.e. QM/MM) terpene synthase calculations and sets the stage for the rational engineering of this family of enzymes. Chapter 4 The TerDockin method has only been applied to type 1 terpene synthase. Here we expand TerDockin to a type 2 terpene synthase. In order to accomplish this the mechanism for product formation of the enzyme Rv3377c was identified using quantum mechanics. With the intermediates identified the TerDockin recipe can now be applied and allow for the prediction of the catalytically relevant orientation. Chapter 5 The rapidly growing appreciation of enzymes’ catalytic and substrate promiscuity may lead to their expanded use in the fields of chemical synthesis and industrial biotechnology. Here we explore the substrate promiscuity of enoyl-acyl carrier protein reductases (commonly known as FabI), and how that promiscuity is a function of inherent reactivity and the geometric demands of the enzyme’s active site. We demonstrate that these enzymes catalyze the reduction of a wide range of substrates, particularly [alpha],[beta]-unsaturated aldehydes. In addition, we demonstrate that a combination of quantum mechanical hydride affinity calculations and molecular docking can be used to rapidly categorize compounds that FabI can use as substrates. The results here provide new insight into the determinants of catalysis for FabI and set the stage for the development of a new assay for drug discovery, organic synthesis, and novel biocatalysts.