The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Ligand efficiency and fragment-based drug discovery
Abstract
The use of fragment-based drug discovery (FBDD) has increased in recent years since it is more likely to produce a better optimized compound of lower molecular weight. Ligand efficiency (LE) has become important for assessing fragments, HTS hits, and resulting optimized ligands. LE is useful for comparing ligands of equal molecular weight, but is ineffective for comparisons of ligands of differing molecular weight. LE has a strong dependence on molecular size, which has led us to develop a size-independent efficiency score termed fit quality. Evaluating FBDD examples from the literature using LE and fit quality, we find that, in general, the LEs of starting fragments are greater than those of larger, more elaborated, structures. Fit quality scores, however, tend to improve upon optimization of the fragments.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Fragment-based ligand discovery (FBLD) has emerged as a versatile approach for the discovery of atom-efficient, small-molecule binders for a wide range of proteins10–12.”
From Expedited mapping of the ligandable proteome using fully functionalized enantiomeric probe pairs (2019) · cites this paper as [10]
Citations
Cites
Lead- and drug-like compounds: the rule-of-five revolution
Lipinski, C. A. (2004) · Drug Discovery Today Technologies · doi:10.1016/j.ddtec.2004.11.007 · Cited by 6,455
Discovering High-Affinity Ligands for Proteins: SAR by NMR
Shuker, S. B., Hajduk, P. J., Meadows, R. P., & Fesik, S. W. (1996) · Science · doi:10.1126/science.274.5292.1531 · Cited by 2,045
Ligand efficiency: a useful metric for lead selection
Hopkins, A. L., Groom, C. R., & Alex, A. (2004) · Drug Discovery Today · doi:10.1016/s1359-6446(04)03069-7 · Cited by 1,895
Green, N. M. (1975) · Advances in protein chemistry · doi:10.1016/s0065-3233(08)60411-8 · Cited by 1,472
A decade of fragment-based drug design: strategic advances and lessons learned
Hajduk, P., & Greer, J. (2007) · Nature reviews. Drug discovery · doi:10.1038/nrd2220 · Cited by 1,004
On the attribution and additivity of binding energies
Jencks, W. P. (1981) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.78.7.4046 · Cited by 938
Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery
Hann, M. M., Leach, A. R., & Harper, G. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000403i · Cited by 904
The maximal affinity of ligands
Kuntz, I. D., Chen, K., Sharp, K. A., & Kollman, P. A. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.18.9997 · Cited by 859
Rees, D. C., Congreve, M., Murray, C. W., & Carr, R. A. E. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1467 · Cited by 812
Erlanson, D. A., McDowell, R. S., & O'Brien, T. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm040031v · Cited by 645
Cited by
Sorted by citations
Items 201–223 of 223
BindingDB (2011) · UC San Diego · doi:10.7270/q2z038d4
BindingDB (2014) · UC San Diego · doi:10.7270/q2dv1mb8
BindingDB (2010) · UC San Diego · doi:10.7270/q2348kdc
BindingDB (2013) · UC San Diego · doi:10.7270/q21j9bs9
BindingDB (2011) · UC San Diego · doi:10.7270/q22807wj
BindingDB (2012) · UC San Diego · doi:10.7270/q2c53m9c
BindingDB (2010) · UC San Diego · doi:10.7270/q2ws8tdz
BindingDB (2017) · UC San Diego · doi:10.7270/q2p84drx
BindingDB (2020) · UC San Diego · doi:10.7270/q2251mpr
BindingDB (2020) · UC San Diego · doi:10.7270/q2cc13cc
Metadata
- Authors
- Bembenek, S. D., Tounge, B. A., & Reynolds, C. H.
- Affiliations
- Janssen Research & Development (United States) (US)
- Corresponding author
- Bembenek, Scott D.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2009-03
- Volume
- 14
- Issue
- 5-6
- Pages
- 278-283
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W2086070714
- Cited by
- 196
- References
- 23
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 8 · 2023: 6 · 2022: 4 · 2021: 13 · 2020: 2 · 2019: 12 · 2018: 8 · 2017: 10 · 2016: 12 · 2015: 13 · 2014: 15 · 2013: 15 · 2012: 19
- FWCI
- 21.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Drug Discovery Today (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
- Keywords
- ligand efficiency, fragment-based drug discovery, molecular weight, fragment optimization, hit-to-lead optimization, molecular size dependence
- MeSH terms
- Humans, Ligands, Molecular Weight, Protein Binding, Drug Delivery Systems, Small Molecule Libraries, 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