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      Structural and functional analyses of Barth syndrome-causing mutations and alternative splicing in the tafazzin acyltransferase domain

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          Abstract

          Tafazzin is a mitochondrial phospholipid transacylase, and its mutations cause Barth syndrome (BTHS). Human tafazzin gene produces four distinct alternatively spliced transcripts. To understand the molecular mechanisms of tafazzin deficiency, we performed an atomic resolution analysis of the influence of the BTHS mutations and of alternative splicing on the structure and function of tafazzin. From the three-dimensional (3D) homology modeling of tafazzin, we identified candidate amino acid residues that contribute to cardiolipin binding and to mitochondrial membrane associations that facilitate acyl-transfer reactions. Primate specific exon 5, which is alternatively spliced, is predicted to correspond to an intrinsically unstructured region in the protein. We proposed that this region should change the substrate-binding affinity and/or contribute to primate-specific molecular interactions. Exon 7, another alternatively spliced exon, encodes a region forming a part of the putative substrate-binding cleft, suggesting that the gene products lacking exon 7 will lose their substrate-binding ability. We demonstrate a clear localization of the BTHS mutations at residues responsible for membrane association, substrate binding, and the conformational stability of tafazzin. These findings provide new insights into the function of defective tafazzin and the pathogenesis of BTHS at the level of protein 3D structure and the evolution of alternatively spliced exons in primates.

          Highlights

          • We predicted a 3D structure model of tafazzin with reasonable reliability.

          • The model structure accounts for differences in function of splice variants.

          • The exon acquired in the primate lineage encodes an intrinsically unstructured region.

          • The mutations associated with Barth syndrome were found on functionally important residues of tafazzin.

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          Most cited references38

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          Protein structure prediction and structural genomics.

          Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.
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            Theoretical studies of protein folding.

            N. Go (1983)
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              TOPCONS: consensus prediction of membrane protein topology

              TOPCONS (http://topcons.net/) is a web server for consensus prediction of membrane protein topology. The underlying algorithm combines an arbitrary number of topology predictions into one consensus prediction and quantifies the reliability of the prediction based on the level of agreement between the underlying methods, both on the protein level and on the level of individual TM regions. Benchmarking the method shows that overall performance levels match the best available topology prediction methods, and for sequences with high reliability scores, performance is increased by ∼10 percentage points. The web interface allows for constraining parts of the sequence to a known inside/outside location, and detailed results are displayed both graphically and in text format.
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                Author and article information

                Contributors
                Journal
                Meta Gene
                Meta Gene
                Meta Gene
                Elsevier
                2214-5400
                22 April 2015
                June 2015
                22 April 2015
                : 4
                : 92-106
                Affiliations
                [a ]Nagahama Institute of Bio-Science and Technology, 1266 Tamura-cho, Nagahama, Shiga 526-0829, Japan
                [b ]Graduate School of Humanities and Sciences, Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, Tokyo 112-8610, Japan
                [c ]Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
                [d ]Department of Technology Development, Kazusa DNA Research Institute, 2-6-7 Kazusa-Kamatari, Kisarazu, Chiba 292-0818, Japan
                [e ]Research Organization of Information and Systems, 4-3-13, Toranomon, Minatoku, Tokyo 105-0001, Japan
                Author notes
                [* ]Corresponding author. Tel.: + 81 749 64 8100; fax: + 81 749 64 8140. a_hijikata@ 123456nagahama-i-bio.ac.jp
                Article
                S2214-5400(15)00018-3
                10.1016/j.mgene.2015.04.001
                4412953
                25941633
                084a3a37-5439-42ea-83a2-2d316b7bd59c
                © 2015 The Authors. Published by Elsevier B.V.

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

                History
                : 4 March 2015
                : 3 April 2015
                Categories
                Article

                taz gene,x-linked recessive disease,disease-causing mutations,homology modeling,immunodeficiency,intrinsically unstructured region

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