User:Francielle Aguiar Gomes/Sandbox 1

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'''Cryogenic electron microscopy''' (cryo-EM) is a cryomicroscopy technique applied to samples cooled to cryogenic temperatures. For biological samples, structure is preserved by embedding in a glassy ice environment. An aqueous sample is applied to a mesh grid and frozen by immersion in liquid ethane or a mixture of liquid ethane and propane <ref>10.1017/S1431927608080781</ref>. This technique has advanced dramatically to become a viable tool for high-resolution structural biology research. The ultimate outcome of a cryo-EM study is an atomic model of a macromolecule or its complex with interacting partners. Recent advances in direct electron detectors as well as reconstruction single particle algorithms have led to the determination of the structure of macromolecular complexes ranging from 2 to 5 Å resolution. At these resolutions, also known as “near atomic” resolution, it is possible to infer all-atom structures de novo.
'''Cryogenic electron microscopy''' (cryo-EM) is a cryomicroscopy technique applied to samples cooled to cryogenic temperatures. For biological samples, structure is preserved by embedding in a glassy ice environment. An aqueous sample is applied to a mesh grid and frozen by immersion in liquid ethane or a mixture of liquid ethane and propane <ref>10.1017/S1431927608080781</ref>. This technique has advanced dramatically to become a viable tool for high-resolution structural biology research. The ultimate outcome of a cryo-EM study is an atomic model of a macromolecule or its complex with interacting partners. Recent advances in direct electron detectors as well as reconstruction single particle algorithms have led to the determination of the structure of macromolecular complexes ranging from 2 to 5 Å resolution. At these resolutions, also known as “near atomic” resolution, it is possible to infer all-atom structures de novo.
The first step in cryo-EM structure determination is de novo structure determination, where an initial model can be built, given only one sequence and a reconstruction, when no other limited structural information is known. In the second stage, the model is optimized, where a wide range of class of methods for improving the fit of a model to the data and improving the geometry of a model. Finally, tools for model validation are described, in attempt to quantify the overall accuracy of a model given a reconstruction.
The first step in cryo-EM structure determination is de novo structure determination, where an initial model can be built, given only one sequence and a reconstruction, when no other limited structural information is known. In the second stage, the model is optimized, where a wide range of class of methods for improving the fit of a model to the data and improving the geometry of a model. Finally, tools for model validation are described, in attempt to quantify the overall accuracy of a model given a reconstruction.
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[[Image:Structure1.png]]
[[Image:Structure1.png]]
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An overview of three steps of atomic model determination from near-atomic resolution data. (Left) De novo building methods take primary sequence and map, and automatically produce a backbone model with sequence registered, identifying which regions in the map correspond to particular sequences. (Center) Model optimization takes an initial model—either produced from de novo building, or from a highresolution homologue—and optimizes the coordinates to better agree with the map, as well as adopt more physically realistic geometry. (Right) Model validation aims to assess—both globally and locally—the accuracy of a model, given experimental data. Such tools are useful not only for assessing overall accuracy but also for tuning parameters of optimization <ref>10.1016/bs.mie.2016.06.003</ref>.
An overview of three steps of atomic model determination from near-atomic resolution data. (Left) De novo building methods take primary sequence and map, and automatically produce a backbone model with sequence registered, identifying which regions in the map correspond to particular sequences. (Center) Model optimization takes an initial model—either produced from de novo building, or from a highresolution homologue—and optimizes the coordinates to better agree with the map, as well as adopt more physically realistic geometry. (Right) Model validation aims to assess—both globally and locally—the accuracy of a model, given experimental data. Such tools are useful not only for assessing overall accuracy but also for tuning parameters of optimization <ref>10.1016/bs.mie.2016.06.003</ref>.
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[[Image:Con.png|300px|right|thumb| '''Fig. 4.''' (a) Two structural subunits with different configurations for the BChl aG dimers. Color codes in the subunits: LH1-α, green; LH1-β, slate-blue; BChl aG, cyan; spirilloxanthin, yellow. Other polypeptides and pigments are shown in gray. (b) Structure of the face-to-face subunit showing coordination and cross hydrogen bonding of the His residues to BChl aG molecules. (c) Major interactions in the Nterminal region within a face-to-face subunit. (d) Major interactions in the C-terminal region within a face-to-face subunit. Dashed lines indicate distances shorter than 3.5 Å.]]
[[Image:Con.png|300px|right|thumb| '''Fig. 4.''' (a) Two structural subunits with different configurations for the BChl aG dimers. Color codes in the subunits: LH1-α, green; LH1-β, slate-blue; BChl aG, cyan; spirilloxanthin, yellow. Other polypeptides and pigments are shown in gray. (b) Structure of the face-to-face subunit showing coordination and cross hydrogen bonding of the His residues to BChl aG molecules. (c) Major interactions in the Nterminal region within a face-to-face subunit. (d) Major interactions in the C-terminal region within a face-to-face subunit. Dashed lines indicate distances shorter than 3.5 Å.]]
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== References ==
== References ==
<references/>
<references/>

Revision as of 17:46, 19 June 2023

Photosynthetic LH1-RC Super-complex of Rhodospirillum rubrum

PDB ID 7EQD

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Francielle Aguiar Gomes

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