The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
The Druggable Genome: Evaluation of Drug Targets in Clinical Trials Suggests Major Shifts in Molecular Class and Indication
Abstract
The largest innovations within pharmaceutical development come through new compounds that have unique and novel modes of action. These innovations commonly involve expanding the protein space targeted by pharmaceutical agents. At present, information about drugs and drug targets is available online via public databases such as DrugBank and the Therapeutic Targets Database. However, this information is biased, understandably so, toward established drugs and drug-target interactions. To gain a better overview of the drug-targeted portion of the human proteome and the directions of current drug development, we developed a data set of clinical trial drug-target interactions based on CenterWatch's Drugs in Clinical Trials Database, one of the largest databases of its kind. Our curation identified 475 potentially novel clinical trial drug targets. This review aims to identify trends in drug development based on the potentially novel targets currently being explored in clinical trials.
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“Although the research of small molecule drug delivery has established a solid foundation, the target of small molecule drugs accounts for only 2–5% of the human genome, so the development of other alternative therapies is necessary.293”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [293]
Citations
Cites
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
Goodman & Gilman's The Pharmacological Basis of Therapeutics
Brunton, L. L. (1985) · Cited by 7,321
DrugBank: a comprehensive resource for in silico drug discovery and exploration
Wishart, D. S. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj067 · Cited by 3,892
How to improve R&D productivity: the pharmaceutical industry's grand challenge
Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., & Schacht, A. L. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3078 · Cited by 3,566
How many drug targets are there?
Overington, J. P., Al-Lazikani, B., & Hopkins, A. L. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2199 · Cited by 3,505
Hopkins, A. L., & Groom, C. R. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd892 · Cited by 3,305
Targeting cancer with small molecule kinase inhibitors
Zhang, J., Yang, P. L., & Gray, N. S. (2008) · Nature reviews. Cancer · doi:10.1038/nrc2559 · Cited by 2,648
Protein kinases — the major drug targets of the twenty-first century?
Cohen, P. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd773 · Cited by 2,232
DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs
Knox, C., Law, V., Jewison, T., Liu, P., Ly, S., Frolkis, A., Pon, A., Banco, K., Mak, C., Neveu, V., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1126 · Cited by 1,832
Interleukin-1-receptor antagonist in type 2 diabetes mellitus
Larsen, C. M., Faulenbach, M., Vaag, A., Vølund, A., Ehses, J. A., Seifert, B., Mandrup-Poulsen, T., & Donath, M. Y. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa065213 · Cited by 1,798
Cited by
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Trends in GPCR drug discovery: new agents, targets and indications
Hauser, A. S., Attwood, M. M., Rask‐Andersen, M., Schiöth, H. B., & Gloriam, D. E. I. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2017.178 · Cited by 2,714
Self-citationThe evolution of commercial drug delivery technologies
Vargason, A. M., Anselmo, A. C., & Mitragotri, S. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00698-w · Cited by 1,361
G Protein-Coupled Receptors as Targets for Approved Drugs: How Many Targets and How Many Drugs?
Sriram, K., & Insel, P. A. (2018) · Molecular Pharmacology · doi:10.1124/mol.117.111062 · Cited by 1,258
Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation
Zhou, H., & Pang, X. (2018) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00305 · Cited by 1,214
Smart nanoparticles for cancer therapy
Sun, L., Liu, H., Ye, Y., Lei, Y., Islam, R., Tan, S., Tong, R., Miao, Y.-B., & Cai, L. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01642-x · Cited by 1,073
Metadata
- Authors
- Rask-Andersen, M., Masuram, S., & Schiöth, H. B.
- Affiliations
- Department of Neuroscience and Uppsala Biomedical Center, Uppsala University, 75124 Uppsala, Sweden;
- Uppsala Monitoring Centre (SE)
- Uppsala University (SE)
- ORCID
- Schiöth, Helgi B.
- Venue
- Annual Review of Pharmacology and Toxicology
- Publisher
- Annual Reviews
- Published
- 2014-01-06
- Volume
- 54
- Issue
- 1
- Pages
- 9-26
- ISSN
- 0362-1642 (ISSN-L)
- 1545-4304
- OpenAlex
- W2147241078
- Cited by
- 282
- References
- 35
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 12 · 2023: 23 · 2022: 23 · 2021: 25 · 2020: 25 · 2019: 22 · 2018: 22 · 2017: 34 · 2016: 34 · 2015: 27 · 2014: 13
- FWCI
- 2.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Annual Review of Pharmacology and Toxicology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- 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
- druggable genome, therapeutic target, new drug development, human proteome, treatment indications, drug development trends, DrugBank
- MeSH terms
- Alzheimer Disease, Anti-Inflammatory Agents, Antineoplastic Agents, Appetite Regulation, Clinical Trials as Topic, Evaluation Studies as Topic, Humans, Hypoglycemic Agents, Genome, Human, Databases, Factual, Proteome, G-Protein-Coupled Receptor Kinases, Molecular Targeted Therapy
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