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      Lipid switches in the immunological synapse

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          Abstract

          Adaptive immune responses comprise the activation of T cells by peptide antigens that are presented by proteins of the Major Histocompatibility Complex (MHC) on the surface of an antigen-presenting cell. As a consequence of the T cell receptor interacting productively with a certain peptide-MHC complex, a specialized cell-cell junction known as the immunological synapse forms and is accompanied by changes in the spatiotemporal patterning and function of intracellular signaling molecules. Key modifications occurring at the cytoplasmic leaflet of the plasma and internal membranes in activated T cells comprise lipid switches that affect the binding and distribution of proteins within or near the lipid bilayer. Here, we describe two major classes of lipid switches that act at this critical water/membrane interface. Phosphoinositides are derived from phosphatidylinositol, an amphiphilic molecule that contains two fatty acid chains and a phosphate group that bridges the glycerol backbone to the carbohydrate inositol. The inositol ring can be variably (de-)phosphorylated by dedicated kinases and phosphatases, thereby creating phosphoinositide signatures that define the composition and properties of signaling molecules, molecular complexes, or whole organelles. Palmitoylation refers to the reversible attachment of the fatty acid palmitate to a substrate protein’s cysteine residue. DHHC enzymes, named after the four conserved amino acids in their active site, catalyze this post-translational modification and thereby change the distribution of proteins at, between, and within membranes. T cells utilize these two types of molecular switches to adjust their properties to an activation process that requires changes in motility, transport, secretion, and gene expression.

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          Most cited references126

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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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            ColabFold: making protein folding accessible to all

            ColabFold offers accelerated prediction of protein structures and complexes by combining the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold’s 40−60-fold faster search and optimized model utilization enables prediction of close to 1,000 structures per day on a server with one graphics processing unit. Coupled with Google Colaboratory, ColabFold becomes a free and accessible platform for protein folding. ColabFold is open-source software available at https://github.com/sokrypton/ColabFold and its novel environmental databases are available at https://colabfold.mmseqs.com . ColabFold is a free and accessible platform for protein folding that provides accelerated prediction of protein structures and complexes using AlphaFold2 or RoseTTAFold.
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              Membrane fusion: grappling with SNARE and SM proteins.

              The two universally required components of the intracellular membrane fusion machinery, SNARE and SM (Sec1/Munc18-like) proteins, play complementary roles in fusion. Vesicular and target membrane-localized SNARE proteins zipper up into an alpha-helical bundle that pulls the two membranes tightly together to exert the force required for fusion. SM proteins, shaped like clasps, bind to trans-SNARE complexes to direct their fusogenic action. Individual fusion reactions are executed by distinct combinations of SNARE and SM proteins to ensure specificity, and are controlled by regulators that embed the SM-SNARE fusion machinery into a physiological context. This regulation is spectacularly apparent in the exquisite speed and precision of synaptic exocytosis, where synaptotagmin (the calcium-ion sensor for fusion) cooperates with complexin (the clamp activator) to control the precisely timed release of neurotransmitters that initiates synaptic transmission and underlies brain function.
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                Author and article information

                Contributors
                Journal
                J Biol Chem
                J Biol Chem
                The Journal of Biological Chemistry
                American Society for Biochemistry and Molecular Biology
                0021-9258
                1083-351X
                30 May 2024
                July 2024
                30 May 2024
                : 300
                : 7
                : 107428
                Affiliations
                [1 ]Cambridge Institute for Medical Research, Cambridge, UK
                [2 ]Heidelberg University Biochemistry Center (BZH), Heidelberg, Germany
                [3 ]Laboratory of Protein Biochemistry, Institute of Chemistry & Biochemistry, Freie Universität Berlin, Berlin, Germany
                Author notes
                []For correspondence: Christian Freund christian.freund@ 123456fu-berlin.de
                Article
                S0021-9258(24)01929-X 107428
                10.1016/j.jbc.2024.107428
                11259711
                38823638
                d407c22d-8e47-4a41-bd01-e35e47e7dae1
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 14 November 2023
                : 7 May 2024
                Categories
                JBC Reviews

                Biochemistry
                t cell,immunological synapse,phosphoinositides,s-acylation,palmitoylation,dhhc enzymes
                Biochemistry
                t cell, immunological synapse, phosphoinositides, s-acylation, palmitoylation, dhhc enzymes

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