Laws of mechanics and function in proteins as evolved molecular machines
Laws of mechanics and function in proteins as evolved molecular machines
批准号:
10022123
负责人:
Lauren McGough
金额:
$6.53万
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:
2019-09-01 至 2021-08-31
关键词:
Allosteric SiteBiologicalBiological ModelsBiological ProcessChargeCommunitiesComparative StudyCrystallizationCrystallographyDataData AnalysesDimensionsDiseaseEnvironmentEvolutionExhibitsFamilyFreedomHeterogeneityHumanIndividualLawsLengthLifeLigand BindingLightMeasurementMeasuresMechanicsMethodsMicroscopicModelingMolecularMolecular MachinesMonte Carlo MethodMotionMutationPatternPerformancePositioning AttributeProcessPropertyProtein DynamicsProtein EngineeringProteinsReactionRecordsResearchResolutionRouteSiteSourceStructureSurfaceSystemTechniquesTemperatureTestingTheoretical StudiesTimeWorkX ray diffraction analysisX-Ray Crystallographychemical reactioncomparativedesignelectric fieldelectron densityengineering designevidence baseexpectationexperimental studyflexibilityhigh dimensionalityimprovedinnovationmacromoleculemanmathematical analysismechanical forcemembermolecular dynamicsmutantnovelpredictive testpressureprogramsprospectiveprotein functionprotein structureresponsesimulationtheoriestool
中文摘要
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英文摘要
PROJECT SUMMARY
Proteins are the "machines" that carry out the chemical reactions necessary for life. Unlike man-made
machines, proteins exhibit a unique combination of features: high performance with respect to specific
biological functions, and adaptability to changes in their environment. The coincidence of these two properties
suggests that there exist yet-unknown design principles which govern evolved machines. However, despite the
clear implications of this observation for our understanding of evolution, proteins, and engineering, these
design principles remain elusive due to the high-dimensionality of internal protein atomic motions and wide
range of length- and time-scales associated with the problem. At present, molecular dynamics simulations
have been the most useful tools for shedding light on the internal dynamics of proteins, but given the challenge
in measuring the time-dependent internal motions a protein undergoing some biological process, these
simulations are often not confirmable by experimental data. New experiments and analysis methods in our lab
are able to measure internal motions within proteins at Angstrom-resolution. This provides an opportunity: I will
carry out substantial experimentally-verified molecular dynamics simulations which model the new
experiments. By carrying out these simulations using several different force fields and comparing a variety of
quantities to their experimental values, I will construct new experimentally-motivated molecular dynamics “best
practices” such that simulations and experiment imply consistent properties of the given protein. Using these
“optimized” molecular dynamics methods along with data analysis methods such as dimensional reduction, I
will study protein dynamics in multiple contexts, including electric-field stimulated X-ray crystallography (EFX),
a novel technique by which an electric field is applied to a protein crystal and the resulting structure is
measured using X-ray crystallography, and room-temperature X-ray crystallography (RTX), a new way of
determining thermal ensembles of protein configurations at room temperature using static crystallography data.
These will enable me to reduce the measurements of atomic-scale motions of thousands of individual atoms to
a description of coordinated motions on different scales with the expectation of revealing a small number of
mechanical mechanisms dictating protein function and allostery. This mathematical analysis not only opens up
new experimental, computational and conceptual methods for understanding protein function from microscopic
structural information; its improved, evidence-based simulation methods can be used for predicting collective
motions when crystallography experiments are nonexistent or inaccessible. Overall, this research will develop
new quantitative tools for studying the connection between protein mechanics and function, and implement
these tools to extract a low-dimensional, ordered description of this seemingly high-dimensional, disordered
phenomenon.
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Laws of mechanics and function in proteins as evolved molecular machines
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批准号:10459896
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项目类别:
-
资助金额:$6.86万
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财政年份:2019
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负责人:Lauren McGough
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依托单位:
海外基金