The DOI matches its Crossref record; 60 of the 62 references it cites were found in a registry or an index.
Chemical substructures that enrich for biological activity
Open accessAbstract
Motivation: Certain chemical substructures are present in many drugs. This has led to the claim of ‘privileged’ substructures which are predisposed to bioactivity. Because bias in screening library construction could explain this phenomenon, the existence of privilege has been controversial. Results: Using diverse phenotypic assays, we defined bioactivity for multiple compound libraries. Many substructures were associated with bioactivity even after accounting for substructure prevalence in the library, thus validating the privileged substructure concept. Determinations of privilege were confirmed in independent assays and libraries. Our analysis also revealed ‘underprivileged’ substructures and ‘conditional privilege’—rules relating combinations of substructure to bioactivity. Most previously reported substructures have been flat aromatic ring systems. Although we validated such substructures, we also identified three-dimensional privileged substructures. Most privileged substructures display a wide variety of substituents suggesting an entropic mechanism of privilege. Compounds containing privileged substructures had a doubled rate of bioactivity, suggesting practical consequences for pharmaceutical discovery. Contact: fritz_roth@hms.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“To bypass the limitations of MS/MS spectral libraries, an alternative computational approach translates MS/MS information directly into structural information as structural fingerprints.163”
From Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products (2024) · cites this paper as [163]
Experimental — accuracy not yet measured
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
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
The Combinatorial Synthesis of Bicyclic Privileged Structures or Privileged Substructures
Horton, D. A., Bourne, G. T., & Smythe, M. L. (2003) · Chemical Reviews · doi:10.1021/cr020033s · Cited by 3,032
The Properties of Known Drugs. 1. Molecular Frameworks
Bemis, G. W., & Murcko, M. A. (1996) · Journal of Medicinal Chemistry · doi:10.1021/jm9602928 · Cited by 2,501
Small Molecule Inhibitor of Mitotic Spindle Bipolarity Identified in a Phenotype-Based Screen
Mayer, T. U., Kapoor, T. M., Haggarty, S. J., King, R. W., Schreiber, S. L., & Mitchison, T. J. (1999) · Science · doi:10.1126/science.286.5441.971 · Cited by 1,752
Proceedings of the 20th conference on Uncertainty in artificial intelligence
Meek, C., Chickering, M., & Halpern, J. Y. (2004) · Cited by 1,548
Evans, B., Rittle, K. E., Bock, M. G., DiPardo, R. M., Freidinger, R. M., Whitter, W. L., Lundell, G. F., Veber, D. F., Anderson, P., Chang, R. S. L., et al. (1988) · Journal of Medicinal Chemistry · doi:10.1021/jm00120a002 · Cited by 1,460
A Selective Inhibitor of eIF2α Dephosphorylation Protects Cells from ER Stress
Boyce, M., Bryant, K. F., Jousse, C., Long, K., Harding, H. P., Scheuner, D. L., Kaufman, R. J., Ma, D., Coen, D. M., Ron, D., et al. (2005) · Science · doi:10.1126/science.1101902 · Cited by 1,403
McGaughey, G. B., Gagné, M., & Rappé, A. K. (1998) · Journal of Biological Chemistry · doi:10.1074/jbc.273.25.15458 · Cited by 1,163
Haggarty, S. J., Koeller, K. M., Wong, J. C., Grozinger, C. M., & Schreiber, S. L. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0430973100 · Cited by 1,066
A Common Mechanism Underlying Promiscuous Inhibitors from Virtual and High-Throughput Screening
McGovern, S. L., Caselli, E., Grigorieff, N., & Shoichet, B. K. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm010533y · Cited by 1,048
Flagged first, then by citations
2 of the 62 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Patchett, 2000, Privileged structures – an update, Annu. Rep. Med. Chem, 35, 289
Cited by
Sorted by citations
PaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints
Yap, C. W. (2010) · Journal of Computational Chemistry · doi:10.1002/jcc.21707 · Cited by 2,979
Searching molecular structure databases with tandem mass spectra using CSI:FingerID
Dührkop, K., Shen, H., Meusel, M., Rousu, J., & Böcker, S. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509788112 · Cited by 1,190
Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra
Dührkop, K., Nothias, L.-F., Fleischauer, M., Reher, R., Ludwig, M., Hoffmann, M. A., Petras, D., Gerwick, W. H., Rousu, J., Dorrestein, P. C., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0740-8 · Cited by 860
Molecular fingerprint similarity search in virtual screening
Cereto‐Massagué, A., Ojeda, M. J., Valls, C., Mulero, M., Garcı́a-Vallvé, S., & Pujadas, G. (2014) · Methods · doi:10.1016/j.ymeth.2014.08.005 · Cited by 881
Machine-learning approaches in drug discovery: methods and applications
Lavecchia, A. (2014) · Drug Discovery Today · doi:10.1016/j.drudis.2014.10.012 · Cited by 822
Metadata
- Authors
- Klekota, J., & Roth, F. P.
- Affiliations
- Harvard University (US)
- Corresponding author
- Roth, Frederick P.
- ORCID
- Roth, Frederick P.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-09-11
- Volume
- 24
- Issue
- 21
- Pages
- 2518-2525
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC2732283
- OpenAlex
- W2107081909
- Cited by
- 392
- References
- 62
- Citations by year
- 2026: 27 · 2025: 28 · 2024: 43 · 2023: 37 · 2022: 24 · 2021: 22 · 2020: 22 · 2019: 18 · 2018: 34 · 2017: 27 · 2016: 31 · 2015: 22 · 2014: 17 · 2013: 13 · 2012: 14
- FWCI
- 5.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Bioinformatics (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- Centre National de la Recherche Scientifique
- National Institute on Aging (R01AG017115)
- National Heart, Lung, and Blood Institute (U01HL081341)
- National Human Genome Research Institute (R01 HG0017115, R01HG003224, P50HG004233)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
- Keywords
- chemical substructures, bioactivity prediction, chemical libraries, phenotypic assays, aromatic ring systems, drug discovery, structure-activity relationship
- MeSH terms
- Animals, Cells, Cultured, Pharmaceutical Preparations, Humans, Ligands, Structure-Activity Relationship, Drug Design, Databases, Factual, Combinatorial Chemistry Techniques
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
