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Trends in the exploitation of novel drug targets
Abstract
The discovery and exploitation of new drug targets is a key focus for both the pharmaceutical industry and academic biomedical research. To provide an insight into trends in the exploitation of new drug targets, we have analysed the drugs that were approved by the US Food and Drug Administration during the past three decades and examined the interactions of these drugs with therapeutic targets that are encoded by the human genome, using the DrugBank database and extensive manual curation. We have identified 435 effect-mediating drug targets in the human genome, which are modulated by 989 unique drugs, through 2,242 drug-target interactions. We also analyse trends in the introduction of drugs that modulate previously unexploited targets, and discuss the network pharmacology of the drugs in our data set.
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“However the experiment failed to confirm the vibrational theory of neuroreception as they report that selective deuteration had no influence on binding affinity or activation 116 .”
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Metadata
- Authors
- Rask-Andersen, M., Almén, M. S., & Schiöth, H. B.
- Affiliations
- Uppsala University (SE)
- Corresponding author
- Schiöth, Helgi B.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2011-08
- Volume
- 10
- Issue
- 8
- Pages
- 579-590
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W2029335938
- Cited by
- 853
- References
- 18
- Citations by year
- 2026: 15 · 2025: 35 · 2024: 40 · 2023: 35 · 2022: 50 · 2021: 36 · 2020: 45 · 2019: 63 · 2018: 80 · 2017: 83 · 2016: 82 · 2015: 91 · 2014: 71 · 2013: 69 · 2012: 45
- FWCI
- 59.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Brain Research Foundation
- Vetenskapsrådet
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Keywords
- novel drug targets, drug-target interactions, FDA-approved drugs, network pharmacology, DrugBank
- MeSH terms
- Humans, United States, United States Food and Drug Administration, Genome, Human, Databases, Factual, Drug Approval, Receptors, G-Protein-Coupled, Drug Discovery
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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