| Title |
Blinded evaluation of farnesoid X receptor (FXR) ligands binding using molecular docking and free energy calculations
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, September 2017
|
| DOI | 10.1007/s10822-017-0054-1 |
| Pubmed ID | |
| Authors |
Edithe Selwa, Eddy Elisée, Agustin Zavala, Bogdan I. Iorga |
| Abstract |
Our participation to the D3R Grand Challenge 2 involved a protocol in two steps, with an initial analysis of the available structural data from the PDB allowing the selection of the most appropriate combination of docking software and scoring function. Subsequent docking calculations showed that the pose prediction can be carried out with a certain precision, but this is dependent on the specific nature of the ligands. The correct ranking of docking poses is still a problem and cannot be successful in the absence of good pose predictions. Our free energy calculations on two different subsets provided contrasted results, which might have the origin in non-optimal force field parameters associated with the sulfonamide chemical moiety. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Spain | 1 | 33% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 24% |
| Student > Ph. D. Student | 2 | 12% |
| Student > Bachelor | 2 | 12% |
| Student > Master | 2 | 12% |
| Other | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 5 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 24% |
| Chemistry | 4 | 24% |
| Agricultural and Biological Sciences | 2 | 12% |
| Medicine and Dentistry | 1 | 6% |
| Physics and Astronomy | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 5 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 14 September 2017.
All research outputs
#16,044,345
of 25,461,852 outputs
Outputs from Perspectives in Drug Discovery and Design
#697
of 949 outputs
Outputs of similar age
#183,443
of 324,671 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#7
of 16 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 26th percentile – i.e., 26% 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 324,671 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.