Novel drug targets in 2021
Open accessThe claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Analysis of novel MoA drug targets published annually in Nature Reviews Drug Discovery with data pulled from DrugCentral shows, on average, an enrichment rate of 15 novel drug targets per year.
“The analysis of novel MoA drug targets (targets that an approved drug had not previously perturbed) published annually in the Nature Reviews Drug Discovery series (33,34,41,42) with data pulled from DrugCentral, shows, on average, an enrichment rate of 15 novel drug targets per year”
From DrugCentral 2023 extends human clinical data and integrates veterinary drugs (2023) · cites this paper as [42]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cited by
Sorted by citations
Pharos 2023: an integrated resource for the understudied human proteome
Kelleher, K. J., Sheils, T. K., Mathias, S. L., Yang, J. J., Metzger, V. T., Siramshetty, V. B., Nguyen, D.-T., Jensen, L. J., Vidović, D., Schürer, S. C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1033 · Cited by 137 · see citing works
Self-citationDrugCentral 2023 extends human clinical data and integrates veterinary drugs
Avram, S., Wilson, T. B., Curpan, R., Halip, L., Borota, A., Bora, A., Bologa, C. G., Holmes, J., Knockel, J., Yang, J. J., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1085 · Cited by 101 · see citing works
“The analysis of novel MoA drug targets (targets that an approved drug had not previously perturbed) published annually in the Nature Reviews Drug Discovery series (33,34,41,42) with data pulled from DrugCentral, shows, on average, an enrichment rate of 15 novel drug targets per year (some of the data overlap with Tabl…”
BackgroundSelf-citationStructural and functional annotation of solute carrier transporters: implication for drug discovery
Dvorak, V., & Superti‐Furga, G. (2023) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2023.2244760 · Cited by 33 · see citing works
“Also, the number of SLC targeting drugs is constantly increasing, even though it still lags behind other classes of similar relevance [102,103].”
BackgroundTherapeutic Target Identification and Drug Discovery Driven by Chemical Proteomics
Zou, M., Zhou, H., Gu, L., Zhang, J., & Fang, L. (2024) · Biology · doi:10.3390/biology13080555 · Cited by 28 · see citing works
Udrescu, M., Ardelean, S. M., & Udrescu, L. (2022) · GigaScience · doi:10.1093/gigascience/giad011 · Cited by 18 · see citing works
“We need more accurate drug–target interaction prediction tools, particularly for the DTIs involving new targets (e.g., introduced each new year by the FDA [42]).”
Exploring DrugCentral: from molecular structures to clinical effects
Halip, L., Avram, S. I., Curpan, R. F., et al. (2023) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-023-00529-x · Cited by 14 · see citing works
Self-citationMeena, D., Huang, J., Smith, A., Yarmolinsky, J., Wu, S., Koskeridis, F., Ko, Y.-H., Dib, M., Antonatos, C., Vasilopoulos, Y., et al. (2025) · European Heart Journal · doi:10.1093/eurheartj/ehaf725 · Cited by 12 · see citing works
“5,6 In the context of BP, they may act as mediators of high BP (e.g. through vasoconstriction or vascular remodelling) or as plasma-based markers of cellular dysfunction linked to hypertensive physiology.”
Ru, Z., Wu, Y., Shao, J., Yin, J., Qian, L., & Miao, X. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad271 · Cited by 6 · see citing works
Temporal trends in evidence supporting novel drug target discovery
Falaguera, M. J., McDonagh, E. M., Ochoa, D., Rusina, P. V., Roldán‐Romero, J. M., Hulcoop, D. G., Leach, A. R., & Dunham, I. (2025) · Nature Communications · doi:10.1038/s41467-025-67180-y · Cited by 6 · see citing works
Novel Drug Targets for Small Molecule‐based Drug Discovery
Achar, R. R., Panigrahi, I., Singh, A., Chandana, N. V., & Swamy, S. N. (2024) · Wiley eBooks · doi:10.1002/9781394249190.ch3 · Cited by 1 · see citing works
Falaguera, M. J., McDonagh, E. M., Ochoa, D., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5669559/v1 · Cited by 1 · see citing works
SAR Knowledge Bases for Driving Drug Discovery
Kandepedu, N., Manchala, A. K., & Azoulay, N. (2024) · doi:10.1002/9783527840748.ch17
CNS Drug Discovery in “The Century of Biology”
Doller, D. (2025) · doi:10.1002/9783527844678.ch1
The evolving landscape of drug targets
Halip, L., Avram, S. I., Overington, J. P., Al‐Lazikani, B., Curpan, R. F., Sirimulla, S., Pushechnikov, A. O., Beccari, A. R., Savchuk, N., & Oprea, T. I. (2026) · Nature Reviews Drug Discovery · doi:10.1038/s41573-026-01530-3
Self-citationTemporally Validated Models for Target “Tclin-likeness”
Quazi, M. A., Sirimulla, S., Bologa, C., Pushechnikov, A. O., Farley, B., Savchuk, N., & Oprea, T. I. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c03088
Self-citation
- Authors
- Avram, S., Halip, L., Curpan, R., & Oprea, T. I.
- Affiliations
- Roivant Sciences (United States) (US)
- Corresponding author
- Oprea, Tudor I.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2022-03-31
- Volume
- 21
- Issue
- 5
- Pages
- 328-328
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W4220784339
- Cited by
- 15
- References
- 0
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 3
- FWCI
- 1.76
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- Common Fund
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
- Keywords
- novel drug targets, new drug approvals, mechanism of action, monoclonal antibodies, SARS-CoV-2 spike protein, COVID-19 treatment, thymic stromal lymphopoietin, IL-17F, IL-13, ANGPTL3, neonatal Fc receptor, NPR2, pegcetacoplan, paroxysmal nocturnal hemoglobinuria, rare diseases, drug labels
- MeSH terms
- Antimalarials, Humans, 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 ›
Are you an author, or do you see a problem with this page? Request a review