| Title |
Homology Modeling of 5-alpha-Reductase 2 Using Available Experimental Data
|
|---|---|
| Published in |
Interdisciplinary Sciences: Computational Life Sciences, January 2018
|
| DOI | 10.1007/s12539-017-0280-1 |
| Pubmed ID | |
| Authors |
Jamal Shamsara |
| Abstract |
5-Alpha-reductase 2 is an interesting pharmaceutical target for the treatment of several diseases, including prostate cancer, benign prostatic hyperplasia, male pattern baldness, acne, and hirsutism. One of the main approaches in computer aided drug design is structure-based drug discovery. However, the experimental 3D structure of 5-alpha-reductase 2 is not available at present. Therefore, a homology modeling method and molecular dynamics simulation were used to develop a reliable model of 5-alpha-reductase 2 for inhibitor pose prediction and virtual screening. Despite the low sequence identity between the target and template sequences, a useful 3D model of 5-alpha-reductase 2 was generated by the inclusion of experimental data. |
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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 27% |
| Student > Ph. D. Student | 2 | 13% |
| Student > Master | 2 | 13% |
| Professor | 1 | 7% |
| Unspecified | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 3 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 13% |
| Nursing and Health Professions | 1 | 7% |
| Unspecified | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 4 | 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 06 February 2018.
All research outputs
#18,585,544
of 23,020,670 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#166
of 297 outputs
Outputs of similar age
#329,830
of 440,328 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#3
of 6 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 297 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 30th percentile – i.e., 30% 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 440,328 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.