2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The Structural Biology of Septins and Their Filaments: An Update

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          In order to fully understand any complex biochemical system from a mechanistic point of view, it is necessary to have access to the three-dimensional structures of the molecular components involved. Septins and their oligomers, filaments and higher-order complexes are no exception. Indeed, the spontaneous recruitment of different septin monomers to specific positions along a filament represents a fascinating example of subtle molecular recognition. Over the last few years, the amount of structural information available about these important cytoskeletal proteins has increased dramatically. This has allowed for a more detailed description of their individual domains and the different interfaces formed between them, which are the basis for stabilizing higher-order structures such as hexamers, octamers and fully formed filaments. The flexibility of these structures and the plasticity of the individual interfaces have also begun to be understood. Furthermore, recently, light has been shed on how filaments may bundle into higher-order structures by the formation of antiparallel coiled coils involving the C-terminal domains. Nevertheless, even with these advances, there is still some way to go before we fully understand how the structure and dynamics of septin assemblies are related to their physiological roles, including their interactions with biological membranes and other cytoskeletal components. In this review, we aim to bring together the various strands of structural evidence currently available into a more coherent picture. Although it would be an exaggeration to say that this is complete, recent progress seems to suggest that headway is being made in that direction.

          Related collections

          Most cited references151

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Inference of macromolecular assemblies from crystalline state.

            We discuss basic physical-chemical principles underlying the formation of stable macromolecular complexes, which in many cases are likely to be the biological units performing a certain physiological function. We also consider available theoretical approaches to the calculation of macromolecular affinity and entropy of complexation. The latter is shown to play an important role and make a major effect on complex size and symmetry. We develop a new method, based on chemical thermodynamics, for automatic detection of macromolecular assemblies in the Protein Data Bank (PDB) entries that are the results of X-ray diffraction experiments. As found, biological units may be recovered at 80-90% success rate, which makes X-ray crystallography an important source of experimental data on macromolecular complexes and protein-protein interactions. The method is implemented as a public WWW service.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Distantly related sequences in the alpha- and beta-subunits of ATP synthase, myosin, kinases and other ATP-requiring enzymes and a common nucleotide binding fold.

              The alpha- and beta-subunits of membrane-bound ATP synthase complex bind ATP and ADP: beta contributes to catalytic sites, and alpha may be involved in regulation of ATP synthase activity. The sequences of beta-subunits are highly conserved in Escherichia coli and bovine mitochondria. Also alpha and beta are weakly homologous to each other throughout most of their amino acid sequences, suggesting that they have common functions in catalysis. Related sequences in both alpha and beta and in other enzymes that bind ATP or ADP in catalysis, notably myosin, phosphofructokinase, and adenylate kinase, help to identify regions contributing to an adenine nucleotide binding fold in both ATP synthase subunits.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                19 November 2021
                2021
                : 9
                : 765085
                Affiliations
                [ 1 ]São Carlos Institute of Physics, University of São Paulo, São Carlos, Brazil
                [ 2 ]São Carlos Institute of Chemistry, University of São Paulo, São Carlos, Brazil
                [ 3 ]Department of Cellular Biology, University of Brasília, Brasília, Brazil
                Author notes

                Edited by: Matthias Gaestel, Hannover Medical School, Germany

                Reviewed by: Helge Ewers, Freie Universität Berlin, Germany

                Thomas Gronemeyer, University of Ulm, Germany

                *Correspondence: Richard C. Garratt, richard@ 123456ifsc.usp.br

                This article was submitted to Signaling, a section of the journal Frontiers in Cell and Developmental Biology

                Article
                765085
                10.3389/fcell.2021.765085
                8640212
                34869357
                cee1133e-d155-4ab8-922c-90e735e30e74
                Copyright © 2021 Cavini, Leonardo, Rosa, Castro, D’Muniz Pereira, Valadares, Araujo and Garratt.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 August 2021
                : 27 October 2021
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo , doi 10.13039/501100001807;
                Award ID: 2020/02897-1 2014/15546-1 2018/19992-7 2016/04658-9 2019/22000-9
                Funded by: Conselho Nacional de Desenvolvimento Científico e Tecnológico , doi 10.13039/501100003593;
                Award ID: 142394/2018-1
                Categories
                Cell and Developmental Biology
                Review

                septin,structural biology,cytoskeletal protein,protein filament,hetero-oligomeric complex,gtp-binding domain,coiled coil

                Comments

                Comment on this article