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      Effects of genetic variants in the TSPO gene on protein structure and stability

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          Abstract

          The 18 kDa translocator protein (TSPO) is an evolutionary conserved cholesterol binding protein localized in the outer mitochondrial membrane. Expression of TSPO is upregulated in activated microglia in various neuroinflammatory, neurodegenerative, and neoplastic disorders. Therefore, TSPO radioligands are used as biomarkers in positron emission tomography (PET) studies. In particular, a common A147T polymorphism in the TSPO gene affects binding of several high affinity TSPO radioligands. Given the relevance of TSPO as a diagnostic biomarker in disease processes, we systematically searched for mutations in the human TSPO gene by a wide array of evolution and structure based bioinformatics tools and identified potentially deleterious missense mutations. The two most frequently observed missense mutations A147T and R162H were further analysed in structural models of human wildtype and mutant TSPO proteins. The effects of missense mutations were studied on the atomic level using molecular dynamics simulations. To analyse putative effects of A147T and R162H variants on protein stability we established primary dermal fibroblast cultures from wt and homozygous A147T and R162H donors. Stability of endogenous TSPO protein, which is abundantly expressed in fibroblasts, was studied using cycloheximide protein degradation assay. Our data show that the A147T mutation significantly alters the flexibility and stability of the mutant protein. Furthermore both A147T and R162H mutations decreased the half-life of the mutant proteins by about 25 percent, which could in part explain its effect on reduced pregnenolone production and susceptibility to neuropsychiatric disorders. The present study is the first comprehensive bioinformatic analysis of genetic variants in the TSPO gene, thereby extending the knowledge about the clinical relevance of TSPO nsSNPs.

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          Most cited references28

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          Role of translocator protein density, a marker of neuroinflammation, in the brain during major depressive episodes.

          The neuroinflammatory hypothesis of major depressive disorder is supported by several main findings. First, in humans and animals, activation of the immune system causes sickness behaviors that present during a major depressive episode (MDE), such as low mood, anhedonia, anorexia, and weight loss. Second, peripheral markers of inflammation are frequently reported in major depressive disorder. Third, neuroinflammatory illnesses are associated with high rates of MDEs. However, a fundamental limitation of the neuroinflammatory hypothesis is a paucity of evidence of brain inflammation during MDE. Translocator protein density measured by distribution volume (TSPO VT) is increased in activated microglia, an important aspect of neuroinflammation.
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            Increasing the precision of comparative models with YASARA NOVA--a self-parameterizing force field.

            One of the conclusions drawn at the CASP4 meeting in Asilomar was that applying various force fields during refinement of template-based models tends to move predictions in the wrong direction, away from the experimentally determined coordinates. We have derived an all-atom force field aimed at protein and nucleotide optimization in vacuo (NOVA), which has been specifically designed to avoid this problem. NOVA resembles common molecular dynamics force fields but has been automatically parameterized with two major goals: (i) not to make high resolution X-ray structures worse and (ii) to improve homology models built by WHAT IF. Force-field parameters were not required to be physically correct; instead, they were optimized with random Monte Carlo moves in force-field parameter space, each one evaluated by simulated annealing runs of a 50-protein optimization set. Errors inherent to the approximate force-field equation could thus be canceled by errors in force-field parameters. Compared with the optimization set, the force field did equally well on an independent validation set and is shown to move in silico models closer to reality. It can be applied to modeling applications as well as X-ray and NMR structure refinement. A new method to assign force-field parameters based on molecular trees is also presented. A NOVA server is freely accessible at http://www.yasara.com/servers Copyright 2002 Wiley-Liss, Inc.
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              Mixed-affinity binding in humans with 18-kDa translocator protein ligands.

              11C-PBR28 PET can detect the 18-kDa translocator protein (TSPO) expressed within macrophages. However, quantitative evaluation of the signal in brain tissue from donors with multiple sclerosis (MS) shows that PBR28 binds the TSPO with high affinity (binding affinity [Ki], ∼4 nM), low affinity (Ki, ∼200 nM), or mixed affinity (2 sites with Ki, ∼4 nM and ∼300 nM). Our study tested whether similar binding behavior could be detected in brain tissue from donors with no history of neurologic disease, with TSPO-binding PET ligands other than 11C-PBR28, for TSPO present in peripheral blood, and with human brain PET data acquired in vivo with 11C-PBR28. The affinity of TSPO ligands was measured in the human brain postmortem from donors with a history of MS (n=13), donors without any history of neurologic disease (n=20), and in platelets from healthy volunteers (n=13). Binding potential estimates from thirty-five 11C-PBR28 PET scans from an independent sample of healthy volunteers were analyzed using a gaussian mixture model. Three binding affinity patterns were found in brains from subjects without neurologic disease in similar proportions to those reported previously from studies of MS brains. TSPO ligands showed substantial differences in affinity between subjects classified as high-affinity binders (HABs) and low-affinity binders (LABs). Differences in affinity between HABs and LABs are approximately 50-fold with PBR28, approximately 17-fold with PBR06, and approximately 4-fold with DAA1106, DPA713, and PBR111. Where differences in affinity between HABs and LABs were low (∼4-fold), distinct affinities were not resolvable in binding curves for mixed-affinity binders (MABs), which appeared to express 1 class of sites with an affinity approximately equal to the mean of those for HABs and LABs. Mixed-affinity binding was detected in platelets from an independent sample (HAB, 69%; MAB, 31%), although LABs were not detected. Analysis of 11C-PBR28 PET data was not inconsistent with the existence of distinct subpopulations of HABs, MABs, and LABs. With the exception of 11C-PK11195, all TSPO PET ligands in current clinical application recognize HABs, LABs, and MABs in brain tissue in vitro. Knowledge of subjects' binding patterns will be required to accurately quantify TSPO expression in vivo using PET.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Investigation
                Role: Formal analysisRole: Investigation
                Role: Formal analysisRole: Investigation
                Role: Methodology
                Role: Methodology
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                11 April 2018
                2018
                : 13
                : 4
                : e0195627
                Affiliations
                [1 ] Department of Psychiatry and Psychotherapy, Molecular Neurosciences, University of Regensburg, Regensburg, Germany
                [2 ] Institute of Human Genetics, University of Regensburg, Regensburg, Germany
                [3 ] Department of Ophthalmology, University Hospital Regensburg, Regensburg, Germany
                University of Michigan, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6050-8071
                http://orcid.org/0000-0002-7492-5183
                http://orcid.org/0000-0002-5762-0003
                Article
                PONE-D-18-01574
                10.1371/journal.pone.0195627
                5895031
                29641545
                969b8aed-b996-49f4-8e6b-f4cf7262df88
                © 2018 Milenkovic et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 16 January 2018
                : 25 March 2018
                Page count
                Figures: 5, Tables: 2, Pages: 20
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Protein Structure
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Structure
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Connective Tissue Cells
                Fibroblasts
                Biology and Life Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Connective Tissue Cells
                Fibroblasts
                Medicine and Health Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Connective Tissue Cells
                Fibroblasts
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Biology and Life Sciences
                Genetics
                Mutation
                Substitution Mutation
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Genetics
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Protein Structure
                Protein Structure Comparison
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Structure
                Protein Structure Comparison
                Biology and Life Sciences
                Genetics
                Mutation
                Deletion Mutation
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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