The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Structure-Based Discovery of Novel Chemotypes for Adenosine A2AReceptor Antagonists
Open accessAbstract
The recent progress in crystallography of G-protein coupled receptors opens an unprecedented venue for structure-based GPCR drug discovery. To test efficiency of the structure-based approach, we performed molecular docking and virtual ligand screening (VLS) of more than 4 million commercially available "drug-like" and ''lead-like'' compounds against the A(2A)AR 2.6 A resolution crystal structure. Out of 56 high ranking compounds tested in A(2A)AR binding assays, 23 showed affinities under 10 microM, 11 of those had sub-microM affinities and two compounds had affinities under 60 nM. The identified hits represent at least 9 different chemical scaffolds and are characterized by very high ligand efficiency (0.3-0.5 kcal/mol per heavy atom). Significant A(2A)AR antagonist activities were confirmed for 10 out of 13 ligands tested in functional assays. High success rate, novelty, and diversity of the chemical scaffolds and strong ligand efficiency of the A(2A)AR antagonists identified in this study suggest practical applicability of receptor-based VLS in GPCR drug discovery.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Adenosine Receptors as Therapeutic Targets
Jacobson, K. A., & Gao, Z.-G. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd1983 · Cited by 1,431
Cited by
Ultra-large library docking for discovering new chemotypes
Lyu, J., Wang, S., Balius, T. E., Singh, I., Levit, A., Moroz, Y. S., O’Meara, M. J., Che, T., Algaa, E., Tolmachova, K., et al. (2019) · Nature · doi:10.1038/s41586-019-0917-9 · Cited by 998
Structure of the human histamine H1 receptor complex with doxepin
Shimamura, T., Shiroishi, M., Weyand, S., Tsujimoto, H., Winter, G., Katritch, V., Abagyan, R., Cherezov, V., Liu, W., Han, G. W., et al. (2011) · Nature · doi:10.1038/nature10236 · Cited by 804
Self-citationA practical guide to large-scale docking
Bender, B. J., Gahbauer, S., Luttens, A., Lyu, J., Webb, C. M., Stein, R. M., Fink, E. A., Balius, T. E., Carlsson, J., Irwin, J. J., et al. (2021) · Nature Protocols · doi:10.1038/s41596-021-00597-z · Cited by 546
“38 Dock the control set.”
Synthon-based ligand discovery in virtual libraries of over 11 billion compounds
Sadybekov, A. A., Sadybekov, A. V., Liu, Y., Iliopoulos-Tsoutsouvas, C., Huang, X.-P., Pickett, J., Houser, B., Patel, N., Tran, N. K., Tong, F., et al. (2022) · Nature · doi:10.1038/s41586-021-04220-9 · Cited by 417
Self-citationVirtual discovery of melatonin receptor ligands to modulate circadian rhythms
Stein, R. M., Kang, H. J., McCorvy, J. D., Glatfelter, G. C., Jones, A. J., Che, T., Slocum, S., Huang, X.-P., Savych, O., Moroz, Y. S., et al. (2020) · Nature · doi:10.1038/s41586-020-2027-0 · Cited by 298
Metadata
- Authors
- Katritch, V., Jaakola, V.-P., Lane, J. R., Lin, J., IJzerman, A. P., Yeager, M., Kufareva, I., Stevens, R. C., & Abagyan, R.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-01-22
- Volume
- 53
- Issue
- 4
- Pages
- 1799-1809
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W1976975058
- Cited by
- 245
- References
- 1
- FWCI
- 29.79
- Type
- journal article
- Language
- en
- Open access
- green
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
