| Title |
A comparison of the pharmacophore identification programs: Catalyst, DISCO and GASP
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, August 2002
|
| DOI | 10.1023/a:1021954728347 |
| Pubmed ID | |
| Authors |
Yogendra Patel, Valerie J. Gillet, Gianpaolo Bravi, Andrew R. Leach |
| Abstract |
Three commercially available pharmacophore generation programs, Catalyst/HipHop, DISCO and GASP, were compared on their ability to generate known pharmacophores deduced from protein-ligand complexes extracted from the Protein Data Bank. Five different protein families were included Thrombin, Cyclin Dependent Kinase 2, Dihydrofolate Reductase, HIV Reverse Transcriptase and Thermolysin. Target pharmacophores were defined through visual analysis of the data sets. The pharmacophore models produced were evaluated qualitatively through visual inspection and according to their ability to generate the target pharmacophores. Our results show that GASP and Catalyst outperformed DISCO at reproducing the five target pharmacophores. |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 4 | 4% |
| India | 3 | 3% |
| United Kingdom | 1 | <1% |
| France | 1 | <1% |
| Russia | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 96 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 23 | 21% |
| Researcher | 22 | 21% |
| Student > Ph. D. Student | 19 | 18% |
| Other | 9 | 8% |
| Professor > Associate Professor | 7 | 7% |
| Other | 17 | 16% |
| Unknown | 10 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 35 | 33% |
| Agricultural and Biological Sciences | 23 | 21% |
| Biochemistry, Genetics and Molecular Biology | 9 | 8% |
| Computer Science | 8 | 7% |
| Medicine and Dentistry | 5 | 5% |
| Other | 11 | 10% |
| Unknown | 16 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 13 July 2022.
All research outputs
#6,502,676
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#311
of 949 outputs
Outputs of similar age
#14,098
of 48,250 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#2
of 3 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
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 has gotten more attention than average, scoring higher than 67% of its peers.
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 48,250 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.