A substrate‐based ontology for human solute carriers - Meixner, Eva; Goldmann, Ulrich; Sedlyarov, Vitaly; Scorzoni, Stefania; Rebsamen, Manuele; Girardi, Enrico; Superti‐Furga, Giulio (Molecular systems biology, 2020)
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. Synopsis 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. The study provides a careful manual annotation of substrates, transport mechanism, coupled ions and subcellular localization for 446 human solute carriers. Substrates are organized in a convenient ontological structure, based on ChEBI (Chemical Entities of Biological Interest). Substrate‐based ontology is applied in interpreting large datasets and de‐orphanizing SLCs using a machine learning approach. Graphical 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.