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X Demographics
Mendeley readers
Attention Score in Context
| Title |
In silico design of small molecule inhibitors of CDK9/cyclin T1 interaction
|
|---|---|
| Published in |
Journal of Molecular Graphics & Modelling, April 2014
|
| DOI | 10.1016/j.jmgm.2014.04.002 |
| Pubmed ID | |
| Authors |
Jelena Randjelovic, Slavica Eric, Vladimir Savic |
| Abstract |
In order to design a small molecule which potentially may interfere with CDK9/cyclin T1 complex formation and therefore influence its physiological role, a computational study of dynamics and druggability of CDK9 binding surface was conducted. Druggability estimates and pocket opening analyses indicated binding regions of cyclin T1 residues, Phe 146 and Lys 6, as starting points for the design of small molecules with the potential to inhibit the CDK9/cyclin T1 association. A pharmacophore model was created, based on these two residues and used to select potential inhibitor structures. Binding energies of the inhibitors were estimated with MM-GBSA. A good correlation of MM-GBSA energies and FTMap druggability predictions was observed. Amongst studied compounds a derivative of 2-amino-8-hydroxyquinoline was identified as the best potential candidate to inhibit CDK9/cyclin T1 interactions. |
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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 5% |
| Unknown | 21 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 32% |
| Student > Master | 3 | 14% |
| Student > Doctoral Student | 2 | 9% |
| Professor | 2 | 9% |
| Other | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 6 | 27% |
| Agricultural and Biological Sciences | 4 | 18% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Medicine and Dentistry | 1 | 5% |
| Psychology | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 6 | 27% |
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 31 December 2014.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from Journal of Molecular Graphics & Modelling
#761
of 925 outputs
Outputs of similar age
#208,705
of 240,223 outputs
Outputs of similar age from Journal of Molecular Graphics & Modelling
#3
of 5 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 925 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 240,223 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.