Title |
Hypoxia inducible factor (HIF) as a model for studying inhibition of protein–protein interactions
|
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Published in |
Chemical Science, January 2017
|
DOI | 10.1039/c7sc00388a |
Pubmed ID | |
Authors |
George M. Burslem, Hannah F. Kyle, Adam Nelson, Thomas A. Edwards, Andrew J. Wilson |
Abstract |
The modulation of protein-protein interactions (PPIs) represents a major challenge in modern chemical biology. Current approaches (e.g. high-throughput screening, computer aided ligand design) are recognised as having limitations in terms of identification of hit matter. Considerable success has been achieved in terms of developing new approaches to PPI modulator discovery using the p53/hDM2 and Bcl-2 family of PPIs. However these important targets in oncology might be considered as "low-hanging-fruit". Hypoxia inducible factor (HIF) is an emerging, but not yet fully validated target for cancer chemotherapy. Its role is to regulate the hypoxic response and it does so through a plethora of protein-protein interactions of varying topology, topography and complexity: its modulation represents an attractive approach to prevent development of new vasculature by hypoxic tumours. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 27% |
United States | 3 | 27% |
Unknown | 5 | 45% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 6 | 55% |
Members of the public | 4 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 2% |
Unknown | 102 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 24% |
Student > Master | 18 | 17% |
Researcher | 14 | 13% |
Student > Bachelor | 10 | 10% |
Professor > Associate Professor | 4 | 4% |
Other | 11 | 11% |
Unknown | 22 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 30 | 29% |
Biochemistry, Genetics and Molecular Biology | 19 | 18% |
Agricultural and Biological Sciences | 10 | 10% |
Medicine and Dentistry | 4 | 4% |
Immunology and Microbiology | 3 | 3% |
Other | 13 | 13% |
Unknown | 25 | 24% |