Multiscale Modeling of Enzymatic Reactions and Firefly Bioluminescence
Multiscale Modeling of Enzymatic Reactions and Firefly Bioluminescence
批准号:
10021018
负责人:
Yihan Shao
金额:
$25.52万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-20 至 2023-08-31
关键词:
AdoptedBiochemical ReactionBioluminescenceCalibrationCommunitiesComputer SimulationComputer softwareComputer-Aided DesignComputing MethodologiesDNA biosynthesisDNA-Directed DNA PolymeraseElectrostaticsEnvironmentEnzymesEvaluationFirefliesFree EnergyFreedomGenerationsGoalsHourIonsLifeMachine LearningMechanicsMethodologyMethodsModelingMolecularMultienzyme ComplexesOutcomePathway interactionsPolymeraseProcessProtocols documentationQuantum MechanicsReactionResourcesRoleSamplingSite-Directed MutagenesisSystemTemperatureThermodynamicsTimebasecomputerized toolscostdesignexperimental groupimprovedinnovationinsightmulti-scale modelingmutantquantumsimulationtheories
中文摘要
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英文摘要
Abstract
Enzyme functionality is a critical component of all life systems. Whereas advances in
experimental methodology have enabled a better understanding of factors that control
enzyme function, critical components of the reaction space such as highly unstable
intermediates and transition states are best accessed for evaluation through
computational simulations. Similarly, computational methodology continues to provide a
key resource for probing excited-state processes such as bioluminescence.
Combined ab initio quantum mechanical molecular mechanical (ai-QM/MM) simulations
are, in principle, the preferred choice in the modeling of both processes. But ai-QM/MM
modeling of enzymatic reactions is now severely limited by its computational cost, where
a direct ai-QM/MM free energy simulation of an enzymatic reaction can take 500,000 or
more CPU hours. Meanwhile, ai-QM/MM modeling of firefly bioluminescence is also
hindered by the computational accuracy, where it has yet to produce quantitatively
correct predictions for the bioluminescence spectral shift with site-directed mutagenesis.
The goal of this proposal is to accelerate ai-QM/MM simulations of enzymatic reaction
free energy and to improve the quality of ai-QM/MM-simulated bioluminescence spectra,
so that ai-QM/MM simulations can be routinely performed by experimental groups. This
will be achieved via a) using a lower-level (semi-empirical QM/MM) Hamiltonian for
sampling; b) an enhancement to the similarity between the two Hamiltonians by
calibrating the low-level Hamiltonian using the reaction pathway force matching
approach, in conjunction with several other methods.
The expected outcomes of this collaborative effort include: a) advanced methodologies
for accelerated reaction free energy simulations and accurate bioluminescence spectra
predictions, which will be released through multiple software platforms; b) a fundamental
understanding of reactions such as Kemp elimination and polymerase-eta catalyzed
DNA replication; c) a deeper insight into the role of macromolecular environment in the
modulation of enzyme catalytic activities or bioluminescence wavelengths, which can
further enhance our capability of designing new enzymes and bioluminescence probes.
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Efficient double hybrid density functional theory algorithms for conformational a
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批准号:8714619
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项目类别:
-
资助金额:$48.02万
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财政年份:2011
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负责人:Yihan Shao
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依托单位:
海外基金