The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Integration of virtual and high-throughput screening
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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
Cramer, R. D., Patterson, D. E., & Bunce, J. D. (1988) · Journal of the American Chemical Society · doi:10.1021/ja00226a005 · Cited by 3,931
Principles of docking: An overview of search algorithms and a guide to scoring functions
Halperin, I., Ma, B., Wolfson, H., & Nussinov, R. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10115 · Cited by 1,294
Do Structurally Similar Molecules Have Similar Biological Activity?
Martin, Y. C., Kofron, J. L., & Traphagen, L. M. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm020155c · Cited by 806
Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?
Ajay, Walters, W. P., & Murcko, M. A. (1998) · Journal of Medicinal Chemistry · doi:10.1021/jm970666c · Cited by 484
Why do we need so many chemical similarity search methods?
Sheridan, R. (2002) · Drug Discovery Today · doi:10.1016/s1359-6446(02)02411-x · Cited by 412
A Scoring Scheme for Discriminating between Drugs and Nondrugs
Sadowski, J., & Kubinyi, H. (1998) · Journal of Medicinal Chemistry · doi:10.1021/jm9706776 · Cited by 392
A model binding site for testing scoring functions in molecular docking.
Wei, B. Q., Baase, W. A., Weaver, L. H., Matthews, B. W., & Shoichet, B. K. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00777-5 · Cited by 237
Cited by
Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery
Meng, X.-Y., Zhang, H.-X., Mezei, M., & Cui, M. (2011) · Current Computer Aided-Drug Design · doi:10.2174/157340911795677602 · Cited by 3,771
Similarity-based virtual screening using 2D fingerprints
Willett, P. (2006) · Drug Discovery Today · doi:10.1016/j.drudis.2006.10.005 · Cited by 849
Role of computer-aided drug design in modern drug discovery
Macalino, S. J. Y., Gosu, V., Hong, S., & Choi, S. (2015) · Archives of Pharmacal Research · doi:10.1007/s12272-015-0640-5 · Cited by 762
Lessons Learnt from Assembling Screening Libraries for Drug Discovery for Neglected Diseases
Brenk, R., Schipani, A., James, D., Krasowski, A., Gilbert, I. H., Frearson, J., & Wyatt, P. G. (2008) · ChemMedChem · doi:10.1002/cmdc.200700139 · Cited by 709
Triballeau, N., Acher, F., Brabet, I., Pin, J.-P., & Bertrand, H.-O. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm049092j · Cited by 631
Metadata
- Authors
- Bajorath, J.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2002-11
- Volume
- 1
- Issue
- 11
- Pages
- 882-894
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W1970651561
- Cited by
- 930
- References
- 8
- FWCI
- 2.46
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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- CoChat. (2026). Citation check: Integration of virtual and high-throughput screening. https://app.cochat.ai/papers/10.1038/nrd941
- The paper
- Bajorath, J. (2002). Integration of virtual and high-throughput screening. Nature Reviews Drug Discovery. https://doi.org/10.1038/nrd941
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.
