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      A substrate‐based ontology for human solute carriers

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          Abstract

          Solute carriers (SLCs) are the largest family of transmembrane transporters in the human genome with more than 400 members. Despite the fact that SLCs mediate critical biological functions and several are important pharmacological targets, a large proportion of them is poorly characterized and present no assigned substrate. A major limitation to systems‐level de‐orphanization campaigns is the absence of a structured, language‐controlled chemical annotation. Here we describe a thorough manual annotation of SLCs based on literature. The annotation of substrates, transport mechanism, coupled ions, and subcellular localization for 446 human SLCs confirmed that ~30% of these were still functionally orphan and lacked known substrates. Application of a substrate‐based ontology to transcriptomic datasets identified SLC‐specific responses to external perturbations, while a machine‐learning approach based on the annotation allowed us to identify potential substrates for several orphan SLCs. The annotation is available at https://opendata.cemm.at/gsflab/slcontology/. Given the increasing availability of large biological datasets and the growing interest in transporters, we expect that the effort presented here will be critical to provide novel insights into the functions of SLCs.

          Abstract

          A thorough manual literature‐based annotation of human solute carriers (SLCs) is presented. Complemented by a substrate‐based ontology, it provides a comprehensive resource for the scientific community to get novel insights to the functions of SLCs.

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          SLC transporters as therapeutic targets: emerging opportunities.

          Solute carrier (SLC) transporters - a family of more than 300 membrane-bound proteins that facilitate the transport of a wide array of substrates across biological membranes - have important roles in physiological processes ranging from the cellular uptake of nutrients to the absorption of drugs and other xenobiotics. Several classes of marketed drugs target well-known SLC transporters, such as neurotransmitter transporters, and human genetic studies have provided powerful insight into the roles of more-recently characterized SLC transporters in both rare and common diseases, indicating a wealth of new therapeutic opportunities. This Review summarizes knowledge on the roles of SLC transporters in human disease, describes strategies to target such transporters, and highlights current and investigational drugs that modulate SLC transporters, as well as promising drug targets.
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            The ABCs of membrane transporters in health and disease (SLC series): Introduction☆☆☆

            The field of transport biology has steadily grown over the past decade and is now recognized as playing an important role in manifestation and treatment of disease. The SLC (solute carrier) gene series has grown to now include 52 families and 395 transporter genes in the human genome. A list of these genes can be found at the HUGO Gene Nomenclature Committee (HGNC) website (see www.genenames.org/genefamilies/SLC). This special issue features mini-reviews for each of these SLC families written by the experts in each field. The existing online resource for solute carriers, the Bioparadigms SLC Tables (www.bioparadigms.org), has been updated and significantly extended with additional information and cross-links to other relevant databases, and the nomenclature used in this database has been validated and approved by the HGNC. In addition, the Bioparadigms SLC Tables functionality has been improved to allow easier access by the scientific community. This introduction includes: an overview of all known SLC and “non-SLC” transporter genes; a list of transporters of water soluble vitamins; a summary of recent progress in the structure determination of transporters (including GLUT1/SLC2A1); roles of transporters in human diseases and roles in drug approval and pharmaceutical perspectives.
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              The in silico human surfaceome

              Significance Despite the fundamental importance of the surfaceome as a signaling gateway to the cellular microenvironment, it remains difficult to determine which proteoforms reside in the plasma membrane and how they interact to enable context-dependent signaling functions. We applied a machine-learning approach utilizing domain-specific features to develop the accurate surfaceome predictor SURFY and used it to define the human in silico surfaceome of 2,886 proteins. The in silico surfaceome is a public resource which can be used to filter multiomics data to uncover cellular phenotypes and surfaceome markers. By our domain-specific feature machine-learning approach, we show indirectly that the environment (extracellular, cytoplasm, or vesicle) is reflected in the biochemical properties of protein domains reaching into that environment.
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                Author and article information

                Contributors
                egirardi@cemm.oeaw.ac.at
                gsuperti@cemm.oeaw.ac.at
                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                10.1002/(ISSN)1744-4292
                MSB
                msb
                Molecular Systems Biology
                John Wiley and Sons Inc. (Hoboken )
                1744-4292
                22 July 2020
                July 2020
                : 16
                : 7 ( doiID: 10.1002/msb.v16.7 )
                : e9652
                Affiliations
                [ 1 ] CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria
                [ 2 ] Center for Physiology and Pharmacology Medical University of Vienna Vienna Austria
                Author notes
                [*] [* ] Corresponding author. Tel: +43 1 40160 70001; E‐mail: egirardi@ 123456cemm.oeaw.ac.at

                Corresponding author. Tel: +43 1 40160 70001; E‐mail: gsuperti@ 123456cemm.oeaw.ac.at

                Author information
                https://orcid.org/0000-0003-1120-6912
                https://orcid.org/0000-0003-3508-2723
                https://orcid.org/0000-0002-0570-1768
                Article
                MSB209652
                10.15252/msb.20209652
                7374931
                32697042
                a02a585d-34a8-488c-b9ca-76d9a3f7ef8a
                © 2020 The Authors. Published under the terms of the CC BY 4.0 license

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 22 April 2020
                : 24 June 2020
                : 26 June 2020
                Page count
                Figures: 7, Tables: 0, Pages: 9, Words: 5643
                Funding
                Funded by: EC|H2020|H2020 Priority Excellent Science|H2020 European Research Council (ERC) , open-funder-registry 10.13039/100010663;
                Award ID: 695214
                Funded by: Innovative Medicines Initiative (IMI)
                Award ID: 777372
                Categories
                Report
                Reports
                Custom metadata
                2.0
                July 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.5 mode:remove_FC converted:22.07.2020

                Quantitative & Systems biology
                annotation,de‐orphanization,ontology,slcs,solute carriers,membrane & intracellular transport,methods & resources,chemical biology

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