Steered Molecular Dynamics Methods Applied to Enzyme Mechanism and Energetics

One of the main goals of chemistry is to understand the underlying principles of chemical reactions, in terms of both its reaction mechanism and the thermodynamics that govern it. Using hybrid quantum mechanics/molecular mechanics (QM/MM)-based methods in combination with a biased sampling scheme, i...

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Autor principal: Ramírez, C.L
Otros Autores: Martí, M.A, Roitberg, A.E
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: Academic Press Inc. 2016
Acceso en línea:Registro en Scopus
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024 7 |2 scopus  |a 2-s2.0-85027447893 
024 7 |2 cas  |a chorismic acid, 617-12-9; prephenate dehydratase, 9044-88-6; amidase, 9012-56-0; chorismate mutase, 9068-30-8; Amidohydrolases; Bacterial Proteins; Chorismate Mutase; Chorismic Acid; Cyclohexanecarboxylic Acids; Cyclohexenes; N-acetyl-1-D-inosityl-2-amino-2-deoxy-alpha-D-glucopyranoside deacetylase; prephenic acid 
040 |a Scopus  |b spa  |c AR-BaUEN  |d AR-BaUEN 
030 |a MENZA 
100 1 |a Ramírez, C.L. 
245 1 0 |a Steered Molecular Dynamics Methods Applied to Enzyme Mechanism and Energetics 
260 |b Academic Press Inc.  |c 2016 
270 1 0 |m Roitberg, A.E.; University of FloridaUnited States; email: roitberg@ufl.edu 
506 |2 openaire  |e Política editorial 
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520 3 |a One of the main goals of chemistry is to understand the underlying principles of chemical reactions, in terms of both its reaction mechanism and the thermodynamics that govern it. Using hybrid quantum mechanics/molecular mechanics (QM/MM)-based methods in combination with a biased sampling scheme, it is possible to simulate chemical reactions occurring inside complex environments such as an enzyme, or aqueous solution, and determining the corresponding free energy profile, which provides direct comparison with experimental determined kinetic and equilibrium parameters. Among the most promising biasing schemes is the multiple steered molecular dynamics method, which in combination with Jarzynski's Relationship (JR) allows obtaining the equilibrium free energy profile, from a finite set of nonequilibrium reactive trajectories by exponentially averaging the individual work profiles. However, obtaining statistically converged and accurate profiles is far from easy and may result in increased computational cost if the selected steering speed and number of trajectories are inappropriately chosen. In this small review, using the extensively studied chorismate to prephenate conversion reaction, we first present a systematic study of how key parameters such as pulling speed, number of trajectories, and reaction progress are related to the resulting work distributions and in turn the accuracy of the free energy obtained with JR. Second, and in the context of QM/MM strategies, we introduce the Hybrid Differential Relaxation Algorithm, and show how it allows obtaining more accurate free energy profiles using faster pulling speeds and smaller number of trajectories and thus smaller computational cost. © 2016 Elsevier Inc.  |l eng 
593 |a FCEN, UBA, Buenos Aires, Argentina 
593 |a University of Florida, Gainesville, FL, United States 
690 1 0 |a FREE ENERGY 
690 1 0 |a JARZYNSKI RELATIONSHIP 
690 1 0 |a MULTIPLE TIME STEP 
690 1 0 |a NONEQUILIBRIUM DYNAMICS 
690 1 0 |a CHORISMIC ACID 
690 1 0 |a PREPHENATE DEHYDRATASE 
690 1 0 |a AMIDASE 
690 1 0 |a BACTERIAL PROTEIN 
690 1 0 |a CHORISMATE MUTASE 
690 1 0 |a CYCLOHEXANECARBOXYLIC ACID DERIVATIVE 
690 1 0 |a CYCLOHEXENE DERIVATIVE 
690 1 0 |a N-ACETYL-1-D-INOSITYL-2-AMINO-2-DEOXY-ALPHA-D-GLUCOPYRANOSIDE DEACETYLASE 
690 1 0 |a PREPHENIC ACID 
690 1 0 |a ALGORITHM 
690 1 0 |a ANALYTIC METHOD 
690 1 0 |a CHEMICAL REACTION 
690 1 0 |a COMPUTER SIMULATION 
690 1 0 |a ENERGY TRANSFER 
690 1 0 |a ENZYME MECHANISM 
690 1 0 |a MOLECULAR DYNAMICS 
690 1 0 |a MOLECULAR MECHANICS 
690 1 0 |a QUANTUM MECHANICS 
690 1 0 |a THERMODYNAMICS 
690 1 0 |a BACILLUS SUBTILIS 
690 1 0 |a CHEMISTRY 
690 1 0 |a ENZYME SPECIFICITY 
690 1 0 |a ENZYMOLOGY 
690 1 0 |a KINETICS 
690 1 0 |a METABOLISM 
690 1 0 |a MOLECULAR DYNAMICS 
690 1 0 |a MYCOBACTERIUM TUBERCULOSIS 
690 1 0 |a QUANTUM THEORY 
690 1 0 |a STATIC ELECTRICITY 
690 1 0 |a ALGORITHMS 
690 1 0 |a AMIDOHYDROLASES 
690 1 0 |a BACILLUS SUBTILIS 
690 1 0 |a BACTERIAL PROTEINS 
690 1 0 |a CHORISMATE MUTASE 
690 1 0 |a CHORISMIC ACID 
690 1 0 |a CYCLOHEXANECARBOXYLIC ACIDS 
690 1 0 |a CYCLOHEXENES 
690 1 0 |a KINETICS 
690 1 0 |a MOLECULAR DYNAMICS SIMULATION 
690 1 0 |a MYCOBACTERIUM TUBERCULOSIS 
690 1 0 |a QUANTUM THEORY 
690 1 0 |a STATIC ELECTRICITY 
690 1 0 |a SUBSTRATE SPECIFICITY 
690 1 0 |a THERMODYNAMICS 
700 1 |a Martí, M.A. 
700 1 |a Roitberg, A.E. 
773 0 |d Academic Press Inc., 2016  |g v. 578  |h pp. 123-143  |p Methods Enzymol.  |x 00766879  |w (AR-BaUEN)CENRE-793  |t Methods in Enzymology 
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