| Title |
A reverse combination of structure-based and ligand-based strategies for virtual screening
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, March 2012
|
| DOI | 10.1007/s10822-012-9558-x |
| Pubmed ID | |
| Authors |
Álvaro Cortés-Cabrera, Federico Gago, Antonio Morreale |
| Abstract |
A new approach is presented that combines structure- and ligand-based virtual screening in a reverse way. Opposite to the majority of the methods, a docking protocol is first employed to prioritize small ligands ("fragments") that are subsequently used as queries to search for similar larger ligands in a database. For a given chemical library, a three-step strategy is followed consisting of (1) contraction into a representative, non-redundant, set of fragments, (2) selection of the three best-scoring fragments docking into a given macromolecular target site, and (3) expansion of the fragments' structures back into ligands by using them as queries to search the library by means of fingerprint descriptions and similarity criteria. We tested the performance of this approach on a collection of fragments and ligands found in the ZINC database and the directory of useful decoys, and compared the results with those obtained using a standard docking protocol. The new method provided better overall results and was several times faster. We also studied the chemical diversity that both methods cover using an in-house compound library and concluded that the novel approach performs similarly but at a much smaller computational cost. |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 6% |
| Russia | 1 | 3% |
| Romania | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 26 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 32% |
| Researcher | 5 | 16% |
| Student > Postgraduate | 4 | 13% |
| Other | 3 | 10% |
| Professor > Associate Professor | 2 | 6% |
| Other | 5 | 16% |
| Unknown | 2 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 9 | 29% |
| Computer Science | 7 | 23% |
| Agricultural and Biological Sciences | 3 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Physics and Astronomy | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 6 | 19% |
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 April 2012.
All research outputs
#17,348,916
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#736
of 949 outputs
Outputs of similar age
#110,667
of 168,717 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#11
of 11 outputs
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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 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.