This project includes a simple Java program that produces a TSV file, listing thousand of known target protein available ids that could be found in target databases.
In particular, we start from retrieving the drug information included in the latest Therapeutic Target Database [1] (VERSION 7.1.01, RELEASED ON 2019.07.14) in a file. We then enrich the drug fields by querying the UMLS Metathesaurus vocabulary Database[2], using the MetamorphoSys tool and by parsing the DisGenet_uniprot_mapping file, provided by DisGeNET [3].
For any use of the drug-mappings.tsv file in your work, a citation to the following paper is expected:
Aisopos, F., Paliouras, G. Comparing methods for drug–gene interaction prediction on the biomedical literature knowledge graph: performance versus explainability. BMC Bioinformatics 24, 272 (2023), DOI.
target_id_mapping - NCSR Demokritos module Copyright 2021 Fotis Aisopos The Java code and TSV file are provided only for academic/research use and are licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at: https://www.apache.org/licenses/LICENSE-2.0 .
The resulting file (target-mappings_latest.tsv) includes a tab-separated entry for each target, including multiple ids that could be found and crossed-checked from the aforementioned sources. For ids not found in none of the above sources, 'null' string is added. Multiple TTD ids/gene names for a specific target are separated with a comma separator(,). An example of the format of the TSV data file is as follows:
CUI Uniprot_Name Uniprot_id Gene_name EnsembleGeneId TTD_id disgenet_gene_id
C1420086 NTCP_HUMAN Q14973 SLC10A1 ENSG00000100652 T99189,T71907 6554
C1442506 MTR1B_HUMAN P49286 MTNR1B ENSG00000134640 T48268 4544
C1417177 MKRN1_HUMAN Q9UHC7 MKRN1 ENSG00000133606 T86877 23608
C1416588 KCNJ6_HUMAN P48051 KCNJ6 ENSG00000157542 T17721 3763
C1413043 CAH2_HUMAN P00918 CA2 ENSG00000104267 T20401 760
...The code includes the CreateTargetMappings class (main class), and the auxiliary TargetEntry class, representing a target object with the various properties. To run the aforementioned Java project, it is obvious that we need to have access to the following sources:
- TTD (to download the targets' information file in raw format)
- Entrez Programming Utilities (E-utilities) API (query PUG for PubChem ids and obtain a token to query for a TGT and an API key) and also include needed jar libraries in the CLASSPATH.
[1]: Y. X. Wang, S. Zhang, F. C. Li, Y. Zhou, Y. Zhang, R. Y. Zhang, J. Zhu, Y. X. Ren, Y. Tan, C. Qin, Y. H. Li, X. X. Li, Y. Z. Chen* and F. Zhu*. Therapeutic Target Database 2020: enriched resource for facilitating research and early development of targeted therapeutics. Nucleic Acids Research. 48(D1): D1031-D1041 (2020). PubMed ID: 31691823
[2]: Bodenreider, O. (2004). The unified medical language system (UMLS): integrating biomedical terminology. Nucleic acids research, 32(suppl_1), D267-D270.
[3]: Janet Piñero, Juan Manuel Ramírez-Anguita, Josep Saüch-Pitarch, Francesco Ronzano, Emilio Centeno, Ferran Sanz, Laura I Furlong. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucl. Acids Res. (2019) doi:10.1093/nar/gkz1021