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      Reconstitution of 3′ end processing of mammalian pre-mRNA reveals a central role of RBBP6

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          Abstract

          Here, Schmidt et al. reconstituted the endonucleolytic cleavage of an extended precursor followed by the addition of a poly(A) tail reaction from overproduced and purified proteins, and provide a minimal list of 14 polypeptides that are essential and two that are stimulatory for RNA processing.

          Abstract

          The 3′ ends of almost all eukaryotic mRNAs are generated in an essential two-step processing reaction: endonucleolytic cleavage of an extended precursor followed by the addition of a poly(A) tail. By reconstituting the reaction from overproduced and purified proteins, we provide a minimal list of 14 polypeptides that are essential and two that are stimulatory for RNA processing. In a reaction depending on the polyadenylation signal AAUAAA, the reconstituted system cleaves pre-mRNA at a single preferred site corresponding to the one used in vivo. Among the proteins, cleavage factor I stimulates cleavage but is not essential, consistent with its prominent role in alternative polyadenylation. RBBP6 is required, with structural data showing it to contact and presumably activate the endonuclease CPSF73 through its DWNN domain. The C-terminal domain of RNA polymerase II is dispensable. ATP, but not its hydrolysis, supports RNA cleavage by binding to the hClp1 subunit of cleavage factor II with submicromolar affinity.

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          Most cited references73

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          Highly accurate protein structure prediction with AlphaFold

          Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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            cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

            A software tool, cryoSPARC, addresses the speed bottleneck in cryo-EM image processing, enabling automated macromolecular structure determination in hours on a desktop computer without requiring a starting model.
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              UCSF ChimeraX : Structure visualization for researchers, educators, and developers

              UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.
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                Author and article information

                Journal
                Genes Dev
                Genes Dev
                genesdev
                GAD
                Genes & Development
                Cold Spring Harbor Laboratory Press
                0890-9369
                1549-5477
                1 February 2022
                : 36
                : 3-4
                : 195-209
                Affiliations
                [1 ]Institute of Biochemistry and Biotechnology, Charles Tanford Protein Center, Martin Luther University Halle-Wittenberg, 06099 Halle, Germany;
                [2 ]Department of Structural Cell Biology, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany;
                [3 ]Institute of Pharmacy, Martin Luther University Halle-Wittenberg, 06099 Halle, Germany
                Author notes
                [4]

                Present address: ZIK HALOmem, Institute of Biochemistry and Biotechnology, Martin Luther University Halle-Wittenberg, 06099 Halle, Germany.

                [5]

                These authors contributed equally to this work.

                Article
                8711660
                10.1101/gad.349217.121
                8887130
                35177537
                4b661db4-ce12-4e7f-99b9-70c94cdc5ccc
                © 2022 Schmidt et al.; Published by Cold Spring Harbor Laboratory Press

                This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genesdev.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 17 November 2021
                : 21 January 2022
                Page count
                Pages: 15
                Funding
                Funded by: German Research Foundation , doi 10.13039/501100001659;
                Funded by: Max Planck Gesellschaft, the European Commission
                Award ID: EXORICO
                Funded by: Novo Nordisk Foundation , doi 10.13039/501100009708;
                Funded by: German Research Foundation , doi 10.13039/501100001659;
                Funded by: DFG Sonderforschungsbereich 1035
                Award ID: 201302640
                Award ID: SFB/TRR 237
                Categories
                Research Paper

                3′ processing,cpsf,poly(a) polymerase,rbbp6,rna cleavage,rna processing,polyadenylation

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