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This work establishes linear-scaling density-functional theory (DFT) as a powerful tool for understanding enzyme catalysis, one that can complement quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics simulations. The thesis reviews benchmark studies demonstrating techniques capable of simulating entire enzymes at the ab initio quantum-mechanical level of accuracy. DFT has transformed the physical sciences by allowing researchers to perform parameter-free quantum-mechanical calculations to predict a broad range of physical and chemical properties of materials. In principle, similar methods could be applied to biological problems. However, even the simplest biological systems contain many thousands of atoms and are characterized by extremely complex configuration spaces associated with a vast number of degrees of freedom. The development of linear-scaling density-functional codes makes biological molecules accessible to quantum-mechanical calculation, but has yet to resolve the complexity of the phase space. Furthermore, these calculations on systems containing up to 2,000 atoms can capture contributions to the energy that are not accounted for in QM/MM methods (for which the Nobel prize in Chemistry was awarded in 2013) and the results presented here reveal profound shortcomings in said methods.
The 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.
Green chemistry already draws on many techniques and approaches developed by theoretical chemists, whilst simultaneously revealing a whole range of interesting new challenges for theoretical chemists to explore. Highlighting how work at the intersection of these fields has already produced beneficial results, Green Chemistry and Computational Chemistry: Shared Lessons in Sustainability is a practical, informative guide to combining green and theoretical chemistry principles and approaches in the development of more sustainable practices.Beginning with an introduction to both theoretical chemistry and green chemistry, the book goes on to explore current approaches being taken by theoretical chemists to address green and sustainable chemistry issues, before moving on to highlight ways in which green chemists are employing the knowledge and techniques of theoretical chemistry to help in developing greener processes. The future possibilities for theoretical chemistry in addressing sustainability issues are discussed, before a selection of case studies provides good insight into how these interactions and approaches have been successfully used in practice. Highlights the benefits of green and theoretical chemistry groups working together to tackle sustainability issues across both academia and industry Supports readers in easily selecting the most appropriate path through the book for their own needs Presents a range of examples examining the practical implications and outcomes of interdisciplinary approaches
The largest collection of articles on the three major gene families, this work ranges from enzymology to molecular biology to physiological implications. The three gene families are related in that the enzymes catalyse the NAD(P) dependent oxidation or reduction of carbonyl containing substrates. The substrates are important in diverse areas such as alcoholism, diabetes and cancer related problems as well as simple detoxification. The scope of the chapters, contributed by leading international scientists, is wide and covers gene regulation to enzyme mechanisms and protein structure. This is the only publication dealing in such depth with just three gene families. An important reference for researchers in toxicology and molecular biology.
Computational Approaches for Studying Enzyme Mechanism Part A, is the first of two volumes in the Methods in Enzymology series, focusses on computational approaches for studying enzyme mechanism. The serial achieves the critically acclaimed gold standard of laboratory practices and remains one of the most highly respected publications in the molecular biosciences. Each volume is eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 550 volumes, the series remains a prominent and essential publication for researchers in all fields of life sciences and biotechnology, including biochemistry, chemical biology, microbiology, synthetic biology, cancer research, and genetics to name a few. Focuses on computational approaches for studying enzyme mechanism Continues the legacy of this premier serial with quality chapters authored by leaders in the field Covers research methods in intermediate filament associated proteins, and contains sections on such topics as lamin-associated proteins, intermediate filament-associated proteins and plakin, and other cytoskeletal cross-linkers
Both strategies for investigation (computational and experimental) in structural and mechanistic Enzymology have developed to some extent independently. However, over the last few years a trend has emerged for strengthening their integration. This combination not only brings together computations and experiments focused on the same enzymatic problems, but also provides complementary insights into the investigated properties and has a powerful synergy effect. This thematic volume of Advances in Protein Chemistry and Structural Biology focuses on the recent success in structural and mechanistic enzymology and has its main emphasis on explaining the enzyme phenomena by using both the experimental and computational approaches. The selected contributions demonstrate how the application of a variety of experimental techniques and modeling methods helps further the understanding of enzyme dynamics, mechanism, inhibition, and drug design. Focuses on the recent success in structural and mechanistic enzymology Has its main emphasis on explaining the enzyme phenomena by using both the experimental and computational approaches Demonstrates how the application of a variety of experimental techniques and modeling methods helps further the understanding of enzyme dynamics, mechanism, inhibition, and drug design
“Multi-scale Quantum Models for Biocatalysis” explores various molecular modelling techniques and their applications in providing an understanding of the detailed mechanisms at play during biocatalysis in enzyme and ribozyme systems. These areas are reviewed by an international team of experts in theoretical, computational chemistry, and biophysics. This book presents detailed reviews concerning the development of various techniques, including ab initio molecular dynamics, density functional theory, combined QM/MM methods, solvation models, force field methods, and free-energy estimation techniques, as well as successful applications of multi-scale methods in the biocatalysis systems including several protein enzymes and ribozymes. This book is an excellent source of information for research professionals involved in computational chemistry and physics, material science, nanotechnology, rational drug design and molecular biology and for students exposed to these research areas.
Enzyme Functionality serves as a conduit for trailblazing research in enzyme engineering-relating current understanding of sequence families, the new notion of enzyme structure classes, and modern methods in protein engineering, design, and directed evolution to accelerate the development of novel enzyme functionalities. This reference gathers the
Ein Lehr- und Handbuch der Thermodynamik biochemischer Reaktionen mit modernen Beispielen und umfangreichen Hinweisen auf die Originalliteratur. - Schwerpunkt liegt auf Stoffwechsel und enzymkatalysierten Reaktionen - Grundlagen der Thermodynamik (z. B. chemisches Gleichgewicht) werden anschaulich abgehandelt - zu den speziellen Themen gehören Reaktionen in Matrices, Komplexbildungsgleichgewichte und Ligandenbindung, Phasengleichgewichte, Redoxreaktionen, Kalorimetrie