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In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery

Overview of attention for article published in Perspectives in Drug Discovery and Design, September 2018
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Title
In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery
Published in
Perspectives in Drug Discovery and Design, September 2018
DOI 10.1007/s10822-018-0160-8
Pubmed ID
Authors

Noriyuki Yamaotsu, Shuichi Hirono

Abstract

Here, we propose an in silico fragment-mapping method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this method, we created a database named Canonical Subsite-Fragment DataBase (CSFDB) and developed a knowledge-based fragment-mapping program, Fsubsite. CSFDB consists of various pairs of subsite-fragments derived from X-ray crystal structures of known protein-ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-mapping method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-mapping method seems to be a useful tool for computational FBDD and SBDD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 25%
Student > Bachelor 4 11%
Researcher 4 11%
Student > Master 4 11%
Student > Postgraduate 2 6%
Other 3 8%
Unknown 10 28%
Readers by discipline Count As %
Chemistry 11 31%
Pharmacology, Toxicology and Pharmaceutical Science 5 14%
Biochemistry, Genetics and Molecular Biology 3 8%
Agricultural and Biological Sciences 1 3%
Computer Science 1 3%
Other 1 3%
Unknown 14 39%
Attention Score in Context

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 11 September 2018.
All research outputs
#16,639,647
of 25,959,914 outputs
Outputs from Perspectives in Drug Discovery and Design
#723
of 970 outputs
Outputs of similar age
#205,467
of 349,767 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#22
of 26 outputs
Altmetric has tracked 25,959,914 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 970 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 23rd percentile – i.e., 23% 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 349,767 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.