The Amounts of Thermal Vibrations and Static Disorder in Protein X-ray Crystallographic B-factors

Na, Hyuntae; Hinsen, Konrad; Song, Guang

doi:10.22541/au.160075279.96631305

Cited by 5 publications

(22 citation statements)

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“…In our recent work 31 , we have shown that the amount of thermal vibrations is small in most proteins but is significantly large (50% or higher) for structures determined at both high resolution and high temperature (that is, room temperature). Unfortunately such structures are rare in the PDB, as most structures in the PDB are determined at cryogenic temperature to reduce the radiation damage 43 .…”

Section: Resultsmentioning

confidence: 95%

“…The magnitudes of thermal vibrations of a whole protein is defined as the mass-weighted averages of over all the nodes 31 , i.e., where i is the index of nodes, which include both protein atoms and added molecular surface nodes. m i are the mass of node i.…”

Section: Methodsmentioning

confidence: 99%

“…By circumventing the cumbersome step of energy minimization, it can be applied directly to experimental structures. Extensive studies have demonstrated its accuracy 31,32,34–36 . The entire sbNMA code is publicly available at https://github.com/htna/sbNMA-Matlab.…”

Section: Methodsmentioning

confidence: 99%

“…The magnitude of mean-square displacement of a whole protein is defined as the mass-weighted averages of over all the atoms 31 , i.e., where i is the atom index.…”

Section: Methodsmentioning

confidence: 99%

“…X-ray crystallography that is widely used in protein structure determination produces also dynamical information in so-called B-factors. Since B-factors contain also a significant amount of static disorder 31 , the magnitude of mean-square displacement obtained from B-factors thus represents an upper bound of the actual magnitude of fluctuations of proteins.…”

Section: Methodsmentioning

confidence: 99%

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Bridging Between Material Properties Of Proteins And The Underlying Molecular Interactions

Song

2021

Preprint

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In this work, we develop a novel method that bridges between material properties of proteins, particularly the modulus of elasticity, and the underlying molecular interactions. To this end, we employ both an all-atom normal mode analysis (NMA) model with the CHARMM force field and an elastic solid model for proteins and protein interfaces. And the "bridge" between the two models is a common physical property that they both can predict: the magnitude of thermal vibrations. This connection allows one to calibrate the Young's moduli of proteins and protein interface regions. We find that the elastic moduli of proteins are mostly in the range of a few Gpa to 10 Gpa, while the elastic moduli of the interface regions are about an order smaller. The work is significant as it represents the first attempt to systematically compute the moduli of elasticity of proteins from molecular interactions.

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Section: Resultsmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The magnitude of mean-square displacement of a whole protein is defined as the mass-weighted averages of over all the atoms 31 , i.e., where i is the atom index.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Bridging Between Material Properties Of Proteins And The Underlying Molecular Interactions

Song

2021

Preprint

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HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

Laine

Grudinin

2021

J. Phys. Chem. B

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In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures.

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HOPMA: Boosting protein functional dynamics with colored contact maps

Laine

Grudinin

2021

Preprint

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In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches.We present HOPMA, a novel method to predict protein functional states and transitions using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures.The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.

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The Amounts of Thermal Vibrations and Static Disorder in Protein X-ray Crystallographic B-factors

Cited by 5 publications

References 0 publications

Bridging Between Material Properties Of Proteins And The Underlying Molecular Interactions

Bridging Between Material Properties Of Proteins And The Underlying Molecular Interactions

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

HOPMA: Boosting protein functional dynamics with colored contact maps

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