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    Home > Biochemistry News > Biotechnology News > Tang Chun and his collaborators used structure prediction and cross-linked mass spectrometry to build the "missing" structure in cryo-EM

    Tang Chun and his collaborators used structure prediction and cross-linked mass spectrometry to build the "missing" structure in cryo-EM

    • Last Update: 2023-01-05
    • Source: Internet
    • Author: User
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    Them6Amethylation modification of RNA is the most abundant of all modifications to RNA, which is widely present in animals, plants and microorganisms, and is involved in regulating various biological processes
    such as biological development, disease, and physiology.
    Them6A"write" protein complex consists of METTL3, METTL14, WTAP, VIRMA, etc.
    , and performs methylation covalent modification
    of RNA sequence (RRA*CH).
    The structural elucidation of this complex helps to explain the sequence selectivity, site specificity, and spatiotemporal dynamics of "read-write"
    modifications.
    The entirem6Amethyl transfer complex is complex and structurally highly dynamic, and its full picture
    is difficult to see by cryo-EM or crystal diffraction alone 。 Because of this, Professor Yin Ping's research group of Professor Yin Ping of Huazhong Agricultural University observed mainly WTAP and VIRMA, two auxiliary proteins, WTAP and VIRMA (indicated in the filling part in A), but almost no METTL3 and METTL14 core catalytic enzymes
    were observed after reconstitution analysis of cryo-EM pictures.

    (A) RNAm6Amethyl transfer complex structure; (B) Mass spectrometry crosslinking between the four proteins experimentally obtained

    Tang Chun has been committed to the development of integrative structural biology methods
    .
    Chemical crosslinking of protein complexes, followed by high-resolution mass spectrometry, can obtain distance information between adjacent amino acids (shown in Figure B).

    With such a distance constraint, the approximate spatial relationship
    of the subunits and structural units inm6Amethyltransferase can be obtained by docking.
    On the other hand, using AlphaFold2 and Colabfold, various possible interactions between proteins in the complex can be obtained, and experiments and AI predictions can be compared, iterated and optimized with each other, and finally the structural model
    of RNAm6A methyl transfer complex can be obtained.
    This model can give a better attribution and explanation for electron density in cryo-EM, and the catalytic center of the core structural enzyme (shown in the cartoon in A) is on the side of VIRMA, providing an explanation
    for the specificity of the latter-mediated methylation modification.
    The modeling and calculation methods established here, based on limited experimental information, supplemented by artificial intelligence predictions, will also be used in more protein systems
    .

    Yan Xuhui and Dr.
    Guan Zeyuan, doctoral students of Huazhong Agricultural University, and Pei Kai, research assistant of the School of Chemistry and Molecular Engineering, Peking University, are the co-first authors of the paper, and Yin Ping of Huazhong Agricultural University and Tang Chun of Peking University are the corresponding authors
    .
    This work was supported
    by the Major Research Program of the National Natural Science Foundation of China and the Key R&D Project of the Ministry of Science and Technology.

    Article link: style="LINE-HEIGHT: 200%; text-indent: 2em; font-size: 16px;" _msthash="101743" _msttexthash="40715415">PI resume: Tang Chun, Professor, School of Chemistry and Molecular Engineering, Peking University, Peking University-Tsinghua Joint Center for Life Sciences, and Peking University Center for Quantitative Biology.

    Lab homepage: style="text-indent: 2em; font-family: , _GB2312, SimKai;" _istranslated="1">, http://tanglab.
    pku.
    edu.
    cn

    .

    Research field: Professor Tang Chun's research group is committed to the development of integrated calculation methods for biological macromolecular structures based on experimental data, including biomagnetic resonance methods and biophysical and chemical methods, to better characterize the dynamic ensemble of biological macromolecular structures in equilibrium or non-equilibrium states, analyze the regulation of macromolecular structures by complex cellular environments and chemical modifications, and the relationship between
    dynamic structural imbalance and disease occurrence.

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