Evidence map›Paper›PMID 29122012›Full record

ArticleJournal of biomedical semantics2017

Drug target ontology to classify and integrate drug discovery data.

Yu Lin, Saurabh Mehta, Hande Küçük-McGinty, John Paul Turner, Dusica Vidovic, Michele Forlin, Amar Koleti, Dac-Trung Nguyen, Lars Juhl Jensen, Rajarshi Guha and 12 more

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical semantics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
3.7field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 75 citations in OpenAlex.

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  7. Autophagy dark genes: Can we find them with machine learning?Natural sciences (Weinheim, Germany) · 2023
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  10. Genomic and proteomic biomarker landscape in clinical trials.Computational and structural biotechnology journal · 2023
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  11. AlphaFold illuminates half of the dark human proteins.Current opinion in structural biology · 2022
    Review
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  16. TIGA: target illumination GWAS analytics.Bioinformatics (Oxford, England) · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 5 institutions in 3 countries.

Yu LinCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Saurabh MehtaCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Hande Küçük-McGintyCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
John Paul TurnerDepartment of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, USA.
Dusica VidovicCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Michele ForlinCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Amar KoletiCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Dac-Trung NguyenNational Center for Advancing Translational Science, Rockville, MD, USA.
Lars Juhl JensenNovo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Rajarshi GuhaNational Center for Advancing Translational Science, Rockville, MD, USA.
Stephen L MathiasDepartment of Internal Medicine, Translational Informatics Division, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Oleg UrsuDepartment of Internal Medicine, Translational Informatics Division, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Vasileios StathiasDepartment of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, FL, USA.
Jianbin DuanCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Nooshin NabizadehCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Caty ChungCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Christopher MaderCenter for Computational Science, University of Miami, Coral Gables, FL, USA.
Ubbo VisserDepartment of Computer Science, University of Miami, Coral Gables, FL, USA.
Jeremy J YangDepartment of Internal Medicine, Translational Informatics Division, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Cristian G BologaDepartment of Internal Medicine, Translational Informatics Division, University of New Mexico School of Medicine, Albuquerque, NM, USA.
Tudor I OpreaDepartment of Internal Medicine, Translational Informatics Division, University of New Mexico School of Medicine, Albuquerque, NM, USA. toprea@salud.unm.edu.
Stephan C SchürerCenter for Computational Science, University of Miami, Coral Gables, FL, USA. sschurer@miami.edu.
University of Miami · USUniversity of New Mexico · USNational Center for Advancing Translational Sciences · USDelhi Technological University · INNovo Nordisk Foundation · DK

Funding

WOMEN'S CANCERS RESEARCH PROGRAMP30CA118100 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Yolanda Sanchez · 2005 to 2026
$57.1M
Data Coordination and Integration Center for LINCS-BD2KU54HL127624 · NHLBI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MA'AYAN, AVI, SCHURER, STEPHAN C · 2014 to 2019
$23.5M
Illuminating the Druggable Genome Knowledge Management Center (IDG KMC)U54CA189205 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI OPREA, TUDOR I · 2014 to 2017
$5.7M
NCI NIH HHS P30 CA118100NCI NIH HHS U54 CA189205NHLBI NIH HHS U54 HL127624NIH HHS U54CA189205NIH HHS U54HL127624
6 · The paper itself

Abstract

backgroundOne of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome.

resultsAs part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships.

conclusionsDTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

Indexed as

Biological OntologiesComputational BiologyDrug Delivery SystemsDrug DiscoveryHumansProteinsSemanticsSoftwareProteins

Identifiers

PMID29122012
PMCPMC5679337
OpenAlexW2952200877

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.