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Author: Publisher: Academic Press ISBN: 0128053631 Category : Science Languages : en Pages : 560
Book Description
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
Author: Publisher: Academic Press ISBN: 0128053631 Category : Science Languages : en Pages : 560
Book Description
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
Author: Publisher: Academic Press ISBN: 0128111089 Category : Science Languages : en Pages : 538
Book Description
Computational Approaches for Studying Enzyme Mechanism, Part B is the first of two volumes in the Methods in Enzymology series that focuses 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 the life sciences and biotechnology, including biochemistry, chemical biology, microbiology, synthetic biology, cancer research, genetics, and other fields of study. - 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
Author: Publisher: Academic Press ISBN: 9780128053478 Category : Science Languages : en Pages : 0
Book Description
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.
Author: Natasha Seelam Publisher: ISBN: Category : Languages : en Pages : 213
Book Description
Enzymes readily perform chemical reactions several orders of magnitude faster than their uncatalyzed versions in ambient conditions with high specificity, making them attractive design targets for industrial purposes. Traditionally, enzyme reactivity has been contextualized through transition-state theory (TST), in which catalytic strategies are described by their ability to minimize the activation energy to cross the reaction barrier through a combination of ground-state destabilization (GSD) and transition-state stabilization (TSS). While excellent progress has been made to rationally design enzymes, the complexity of the design space and the highly optimized nature of enzymes make general application of these approaches difficult. This thesis presents a set of computational methods and applications in order to investigate the larger perspective of enzyme-assisted kinetic processes. For the first part of the thesis, we analyzed the energetics and dynamics of proficient catalyst orotidine 5'-monophosphate decarboxylase (OMPDC), an enzyme that catalyzes decarboxylation nearly 17 orders of magnitude more proficiently than the uncatalyzed reaction in aqueous solvent. Potential-of-mean-force (PMF) calculations on wild type (WT) and two catalytically hindered mutants, S127A and V155D (representing TSS and GSD, respectively), characterized the energy barriers associated with decarboxylation as a function of two parameters: the distance between the breaking C–C bond and a proton-transfer coordinate from the nearby side chain of K72, a conserved lysine in the active site. Coupling PMF analyses with transition path sampling (TPS) approaches revealed two distinct decarboxylation strategies: a simultaneous, K72-assisted pathway and a stepwise, relatively K72-independent pathway. Both PMF and TPS rate calculations reasonably reproduced the empirical differences in relative rates between WT and mutant systems, suggesting these approaches can enable in silico inquiry into both pathway and mechanism identification in enzyme kinetics. For the second study, we investigated the electronic determinants of reactivity, using the enzyme ketol-acid reductoisomerase (KARI). KARI catalyzes first a methyl isomerization and then reduction with an active site comprised of several polar residues, two magnesium divalent cations, and NADPH. This study focused on isomerization, which is rate limiting, with two objectives: characterization of chemical mechanism in successful catalytic events (“reactive”) versus failed attempts to cross the barrier ("non-reactive"), and the interplay between atomic positions, electronic descriptors, and reactivity. Natural bonding orbital (NBO) analyses provided detailed electronic description of the dynamics through the reaction and revealed that successful catalytic events crossed the reaction barrier through a 3-center-2-electron (3C) bond, concurrent to isomerization of hydroxyl/carbonyls on the substrate. Interestingly, the non-reactive ensemble adopted a similar electronic pathway as the reactive ensemble, but its members were generally unable to form and sustain the 3C bond. Supervised machine learning classifiers then identified small subsets of geometric and electronic descriptors, “features”, that predicted reactivity; our results indicated that fewer electronic features were able to predict reactivity as effectively as a larger set of geometric features. Of these electronic features, the models selected diverse descriptors representing several facets of the chemical mechanism (charge, breaking–bond order, atomic orbital hybridization states, etc.). We then inquired how geometric features reported on electronic features with classifiers that leveraged pairs of geometric features to predict the relative magnitude of each electronic feature. Our findings indicated that the geometric, pair-feature models predicted electronic structure with comparable performance as cumulative geometric models, suggesting small subsets of features were capable of reporting on electronic descriptors, and that different subsets could be leveraged to describe various aspects of a chemical mechanism. Lastly, we revisited OMPDC in order to learn the key geometric features that distinguished between the simultaneous and stepwise pathways of decarboxylation, aggregating and labeling pathways drawn from WT and mutant systems ensembles. We leveraged classifiers that predicted between reactive pathways by selecting small subsets of structural features from 620 geometric features comprised of atoms from the active site. The classifiers performed comparably, with greater than 80% testing accuracy and AUC, between times starting from in the reactant basin to 30 fs into crossing the reaction barrier. Remarkably, model-selected features reported on chemically meaningful interactions despite no explicit prior knowledge of the mechanism in training. To illustrate this, we focused analyses on two particular features shown to be predictive while in the reactant basin, prior to crossing the barrier: a potential hydrogen-bond between D75*, an aspartate in the active site, and the 2'-hydroxyl of OMP, and electrostatic repulsion through the proximity of a different aspartate, D70, to the leaving group carboxylate of OMP. Analysis between the simultaneous and stepwise ensembles demonstrated that the simultaneous ensemble adopted shorter distances for both features, generally suggesting stronger interactions. Both features were additionally shown to be associated with the ability to distort the planarity of the orotidyl ring, where shorter distances for either feature were correlated with larger degrees of distortion. Taken together, this suggested the simultaneous ensemble was more effective at distorting the ground state structure prior to crossing the reaction barrier.
Author: Aleksandra Skirycz Publisher: Springer Nature ISBN: 1071626248 Category : Science Languages : en Pages : 261
Book Description
This thorough volume explores protocols of proteome- and metabolome-wide strategies for the identification of protein-small molecule complexes in different organisms, in order to shed light on these important regulatory interactions. Experimental and computational strategies to characterize protein-metabolite interactions are discussed, and recent advances in enabling technologies are featured as well. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice to ensure success in future research. Authoritative and practical, Cell-Wide Identification of Metabolite-Protein Interactions will aid researchers seeking a better understanding of the mechanisms of signal transduction occurring in the cell and assessing the effect of complex formation on cell physiology.
Author: Inaki Tunon Publisher: Royal Society of Chemistry ISBN: 1782626832 Category : Science Languages : en Pages : 558
Book Description
The simulation of enzymatic processes is a well-established field within computational chemistry, as demonstrated by the 2013 Nobel Prize in Chemistry. It has been attracting increasing attention in recent years due to the potential applications in the development of new drugs or new environmental-friendly catalysts. Featuring contributions from renowned authors, including Nobel Laureate Arieh Warshel, this book explores the theories, methodologies and applications in simulations of enzyme reactions. It is the first book offering a comprehensive perspective of the field by examining several different methodological approaches and discussing their applicability and limitations. The book provides the basic knowledge for postgraduate students and researchers in chemistry, biochemistry and biophysics, who want a deeper understanding of complex biological process at the molecular level.
Author: Publisher: Academic Press ISBN: 0123983185 Category : Science Languages : en Pages : 473
Book Description
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
Author: Gábor Náray-Szabó Publisher: Springer Science & Business Media ISBN: 0306469340 Category : Science Languages : en Pages : 386
Book Description
A quantitative description of the action of enzymes and other biological systems is both a challenge and a fundamental requirement for further progress in our und- standing of biochemical processes. This can help in practical design of new drugs and in the development of artificial enzymes as well as in fundamental understanding of the factors that control the activity of biological systems. Structural and biochemical st- ies have yielded major insights about the action of biological molecules and the mechanism of enzymatic reactions. However it is not entirely clear how to use this - portant information in a consistent and quantitative analysis of the factors that are - sponsible for rate acceleration in enzyme active sites. The problem is associated with the fact that reaction rates are determined by energetics (i. e. activation energies) and the available experimental methods by themselves cannot provide a correlation - tween structure and energy. Even mutations of specific active site residues, which are extremely useful, cannot tell us about the totality of the interaction between the active site and the substrate. In fact, short of inventing experiments that allow one to measure the forces in enzyme active sites it is hard to see how can one use a direct experimental approach to unambiguously correlate the structure and function of enzymes. In fact, in view of the complexity of biological systems it seems that only computers can handle the task of providing a quantitative structure-function correlation.
Author: Thakshila D. Dissanayake Rallage Publisher: ISBN: Category : Catalysts Languages : en Pages : 124
Book Description
Enzyme catalysis is an extremely important and complex process that is fundamental to biology. Experiments provide a wealth of valuable information about the function of enzymes; however, this information requires the use of computational models to establish a meaningful interpretation that can be used to guide design. Multiscale computational models, which integrate a hierarchy of theoretical methods to address complex biomolecular problems that span large spatial and temporal ranges, afford powerful tools to provide a detailed molecular level interpretation of a wide range of experimental data from which a consensus view of catalytic mechanism may emerge. In this dissertation, I detail my efforts to develop and apply multiscale methods to study the mechanisms of RNA backbone cleavage catalyzed by Ribonuclease A, an important archetype enzyme system, and the factors that regulate its activity. In the first phase of this research, I use molecular dynamics simulations to characterize the structure and dynamics of the active enzyme in solution at different stages along the reaction path. In this work, I demonstrate that the crystallographic structure represents an inactive, catalytically non-relevant state, and make predictions that a conformational change involving the flipping of the side chain of a conserved histidine residue (His12) is required to adopt a catalytically competent conformation. In the second phase of this research, I apply ''constant pH molecular dynamics simulations'' (CpHMD) to characterize the conditional probability of finding key active site residues in a protonation state that supports general acid-base catalysis. This allowed the prediction of pKa shifts for His12, His119 and Lys41, and, for the first time, activity-pH profiles for an enzyme system that can be compared directly with those measured in kinetic experiments. In the third phase of this research, I use combined quantum mechanical/molecular mechanical methods to study the catalytic chemical steps of transphosphorylation. Results of this work predict a free energy landscape for the reaction, from which the minimum free energy pathway that connects reactants and products allows a detailed molecular-level picture of mechanism. In the fourth phase of this research, I extend the CpHMD method to nucleic acid systems, to benchmark the method for the study of ribozymes that catalyze the same reaction as RNase A.
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Author: Natasha Seelam
Author: Aleksandra Skirycz
Author: Inaki Tunon
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Author: Gábor Náray-Szabó
Author: Thakshila D. Dissanayake Rallage
Author: Nir Ben-Tal