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dc.contributor.authorPatel, Ishan Satishen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Chemistry.en_US
dc.date.accessioned2016-03-03T21:08:36Z
dc.date.available2016-03-03T21:08:36Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/101554
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 104-109).en_US
dc.description.abstractThe full stack approach, from Biochemical Network Simulation to Quantum Mechanics, is developed and utilized to understand in this thesis to understand enzymatic mechanism. The story falls into two segments that highlight two different aspects of enzymatic mechanisms. The first is the determination of the kinetic complexity of one full enzymatic turnover can affect the system in ways that cannot be predicted by simplistic simulations, as evidenced by differential hydrolysis rates of VX and Paraoxon in the enzyme PTE. Over 4M CPU hours of thermodynamic integration simulations were performed to obtain free energy profiles, as a function of up to 6 dimensions, along a reaction path determined through a combination of knowledge from physical organic chemistry, local energetic optimizations, and experimental information. The activation barriers were converted to reaction rates and simulated with mass action kinetics. The results show the slow-down in one turnover for the enzyme is not exactly the one with the "highest barrier" but is instead the result of non-preferential product-facing equilibrium. We also show that active site poisoning by VX opens up new pathways that are an overall detriment to the enzyme. The second is the uncovering of the drivers of enzymatic reactivity for a purely electronic Claisen rearrangement of Chorismate in CM, CM mutants, 1 F7 antibody, Solvent, and Vacuum. Utilizing Transition Path Sampling (TPS), we performed large scale simulations totaling over I OM CPU hours and 1000 TB of storage space to arrive at an understanding of the causation behind differential reactivity from a quantum mechanical orbital point of view. Our results suggest differential catalytic capacity is driven by, and correlates with, greater capacity to generate the forming bond, and for faster enzymes, greater capacity to disrupt the breaking bond. Further orbital level decompositions were performed that demonstrated disruption of the breaking bond allows greater catalytic gains because orbital symmetry prevents strong intermolecular electronic delocalization of the breaking bond electrons. Our evidence suggests a combination of catalyzing the departure from the reactant basin and the transport through the transition region are both reasons why the WT CM is an extremely capable catalyst.en_US
dc.description.statementofresponsibilityby Ishan Satish Patel.en_US
dc.format.extent119 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectChemistry.en_US
dc.titleLarge scale simulation and analysis to understand enzymatic chemical mechanismsen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.identifier.oclc940565882en_US


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