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The multiple roles of computational chemistry in fragment-based drug design

Overview of attention for article published in Perspectives in Drug Discovery and Design, June 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#41 of 949)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

blogs
2 blogs
patent
1 patent

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
172 Mendeley
citeulike
3 CiteULike
Title
The multiple roles of computational chemistry in fragment-based drug design
Published in
Perspectives in Drug Discovery and Design, June 2009
DOI 10.1007/s10822-009-9284-1
Pubmed ID
Authors

Richard Law, Oliver Barker, John J. Barker, Thomas Hesterkamp, Robert Godemann, Ole Andersen, Tara Fryatt, Steve Courtney, Dave Hallett, Mark Whittaker

Abstract

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 2%
Brazil 2 1%
Germany 2 1%
Switzerland 1 <1%
India 1 <1%
Denmark 1 <1%
Russia 1 <1%
United States 1 <1%
Unknown 159 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 46 27%
Student > Ph. D. Student 40 23%
Student > Master 20 12%
Student > Bachelor 14 8%
Professor > Associate Professor 8 5%
Other 26 15%
Unknown 18 10%
Readers by discipline Count As %
Chemistry 53 31%
Agricultural and Biological Sciences 43 25%
Biochemistry, Genetics and Molecular Biology 14 8%
Medicine and Dentistry 13 8%
Pharmacology, Toxicology and Pharmaceutical Science 8 5%
Other 18 10%
Unknown 23 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 22 May 2016.
All research outputs
#2,191,943
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#41
of 949 outputs
Outputs of similar age
#7,341
of 122,558 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#1
of 17 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
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 done particularly well, scoring higher than 95% 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 122,558 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.