The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Receptor- and heparin-binding domains of basic fibroblast growth factor.
Open accessAbstract
Two functional domains in the primary structure of basic fibroblast growth factor (FGF) have been identified on the basis of their ability to interact with the FGF receptor, bind radiolabeled heparin, and modulate the cellular response to FGF. Peptides derived from these two functional domains can act as partial agonists and antagonists in biological assays of FGF activity. Peptides related to the sequences of FGF-(24-68)-NH2 and FGF-(106-115)-NH2 inhibit thymidine incorporation into 3T3 fibroblasts when they are stimulated by FGF but have no effect when the cells are treated with either platelet-derived growth factor or epidermal growth factor. They also possess partial agonist activity and can stimulate DNA synthesis when tested in the absence of exogenous FGF. The active peptides have no effect on the binding of epidermal growth factor to its receptor on A431 cells and they can modulate the effects of FGF, but not fibronectin, on endothelial cell adhesion. The results suggest the possibility of designing specific analogs of FGF that are capable of inhibiting the biological effects of FGF.
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Cites
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Cited by
Fibroblast growth factors, their receptors and signaling
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Three-Dimensional Structures of Acidic and Basic Fibroblast Growth Factors
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Metadata
- Authors
- Baird, A., Schubert, D., Ling, N., & Guillemin, R.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 1988-04
- Volume
- 85
- Issue
- 7
- Pages
- 2324-2328
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2040537095
- Cited by
- 320
- References
- 25
- FWCI
- 8.51
- Type
- journal article
- Language
- en
- Open access
- green
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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.
