The DOI matches its Crossref record.
SPR-based Fragment Screening: Advantages and Applications
Abstract
Fragment-based screening has recently evolved into a promising strategy in drug discovery, and a range of biophysical methods can be employed for fragment library screening. Relevant approaches, such as X-ray, NMR and tethering are briefly introduced focussing on their suitability for fragment-based drug discovery. In particular the application of surface plasmon resonance (SPR) techniques to the primary screening of large libraries comprising small molecules is discussed in detail. SPR is known to be a powerful tool for studying biomolecular interactions in a sensitive and label-free detection format. Advantages of SPR methods over more traditional assay formats are discussed and the application of available channel and array based SPR systems to biosensing are reviewed. Today, SPR protocols have been applied to secondary screening of compound libraries and hit conformation, but primary screening of large fragment libraries for drug discovery is often hampered by the throughput of available systems. Chemical microarrays, in combination with SPR imaging, can simultaneously generate affinity data for protein targets with up to 9,216 immobilized fragments per array. This approach has proven to be suitable for screening fragment libraries of up to 110,000 compounds in a high throughput fashion. The design of fragment libraries and appropriate immobilization chemistries are discussed, as well as suitable follow-up strategies for fragment hit optimization. Finally, described case studies demonstrate the successful identification of selective low molecular weight inhibitors for pharmacologically relevant drug targets through the SPR screening of fragment libraries.
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
Cited by
Network pharmacology: the next paradigm in drug discovery
Hopkins, A. L. (2008) · Nature Chemical Biology · doi:10.1038/nchembio.118 · Cited by 4,622
Surface Plasmon Resonance: A Versatile Technique for Biosensor Applications
Nguyen, H., Park, J., Kang, S., & Kim, M. (2015) · Sensors · doi:10.3390/s150510481 · Cited by 1,357
SPR Biosensors: Historical Perspectives and Current Challenges
Singh, P. (2016) · Sensors and Actuators B: Chemical · doi:10.1016/j.snb.2016.01.118 · Cited by 608
Fragment-Based Approaches in Drug Discovery and Chemical Biology
Scott, D. E., Coyne, A. G., Hudson, S. A., & Abell, C. (2012) · Biochemistry · doi:10.1021/bi3005126 · Cited by 460
Patching, S. G. (2014) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2013.04.028 · Cited by 458
Metadata
- Authors
- Neumann, T., Junker, H.-D., Schmidt, K., & Sekul, R.
- Venue
- Current Topics in Medicinal Chemistry
- Publisher
- Bentham Science Publishers Ltd.
- Published
- 2007-08-01
- Volume
- 7
- Issue
- 16
- Pages
- 1630-1642
- ISSN
- 1568-0266 (ISSN-L)
- OpenAlex
- W2159701165
- Cited by
- 189
- References
- 0
- FWCI
- 5.39
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SPR-based Fragment Screening: Advantages and Applications. https://app.cochat.ai/papers/10.2174/156802607782341073
- The paper
- Neumann, T., Junker, H.-D., Schmidt, K., & Sekul, R. (2007). SPR-based Fragment Screening: Advantages and Applications. Current Topics in Medicinal Chemistry. https://doi.org/10.2174/156802607782341073
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.