| Title |
In silico identification of EGFR-T790M inhibitors with novel scaffolds: start with extraction of common features
|
|---|---|
| Published in |
Drug Design, Development and Therapy, August 2013
|
| DOI | 10.2147/dddt.s41305 |
| Pubmed ID | |
| Authors |
Mingli Xiang, Kai Lei, Wenjie Fan, Yuchun Lin, Gu He, Mingli Yang, Lijuan Chen, Yirong Mo |
| Abstract |
Epidermal growth factor receptor (EGFR) is an attractive therapeutic target for a number of human tumors including non-small cell lung cancer (NSCLC). Most patients with NSCLC and somatic mutations have shown a dramatic initial clinical response to reversible EGFR inhibitors. The clinical efficacy of reversible inhibitors is, however, ultimately limited due to the emergence of drug resistance, which is usually conferred by the EGFR T790M mutation. Importantly, irreversible, synthetic small molecule inhibitors are currently evaluated and some of them have been shown to overcome the acquired resistance that is oftentimes observed in these patients. Thus far, irreversible EGFR inhibitors as a drug class have not received regulatory approval due in part to their poor effectiveness at clinically achievable concentrations. Therefore, there is an urgent need to discover and develop novel, potent irreversible inhibitors against the EGFR T790M mutation. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 31 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 18% |
| Researcher | 5 | 15% |
| Student > Master | 4 | 12% |
| Professor | 4 | 12% |
| Other | 3 | 9% |
| Other | 6 | 18% |
| Unknown | 5 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 11 | 33% |
| Biochemistry, Genetics and Molecular Biology | 4 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 9% |
| Agricultural and Biological Sciences | 3 | 9% |
| Mathematics | 1 | 3% |
| Other | 4 | 12% |
| Unknown | 7 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 November 2013.
All research outputs
#21,077,590
of 25,887,951 outputs
Outputs from Drug Design, Development and Therapy
#1,463
of 2,287 outputs
Outputs of similar age
#160,996
of 211,156 outputs
Outputs of similar age from Drug Design, Development and Therapy
#28
of 43 outputs
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