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Large-Scale First-Principles Molecular Dynamics Simulations with Electrostatic Embedding: Application to Acetylcholinesterase Catalysis
Author(s) -
JeanLuc Fattebert,
Edmond Y. Lau,
Brian J. Bennion,
Patrick Huang,
Felice C. Lightstone
Publication year - 2015
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.5b00606
Subject(s) - molecular dynamics , acylation , acetylcholinesterase , embedding , chemistry , computational chemistry , catalysis , reaction coordinate , density functional theory , electrostatics , chemical physics , enzyme , computer science , organic chemistry , artificial intelligence
Enzymes are complicated solvated systems that typically require many atoms to simulate their function with any degree of accuracy. We have recently developed numerical techniques for large scale first-principles molecular dynamics simulations and applied them to the study of the enzymatic reaction catalyzed by acetylcholinesterase. We carried out density functional theory calculations for a quantum-mechanical (QM) subsystem consisting of 612 atoms with an O(N) complexity finite-difference approach. The QM subsystem is embedded inside an external potential field representing the electrostatic effect due to the environment. We obtained finite-temperature sampling by first-principles molecular dynamics for the acylation reaction of acetylcholine catalyzed by acetylcholinesterase. Our calculations show two energy barriers along the reaction coordinate for the enzyme-catalyzed acylation of acetylcholine. The second barrier (8.5 kcal/mol) is rate-limiting for the acylation reaction and in good agreement with experiment.

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