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Fragment-Based Drug Discovery and X-Ray Crystallography

Overview of attention for book
Attention for Chapter 180: Introduction to Fragment-Based Drug Discovery.
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 154)
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

blogs
2 blogs
wikipedia
5 Wikipedia pages

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
182 Mendeley
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Chapter title
Introduction to Fragment-Based Drug Discovery.
Chapter number 180
Book title
Fragment-Based Drug Discovery and X-Ray Crystallography
Published in
Topics in current chemistry, January 2012
DOI 10.1007/128_2011_180
Pubmed ID
Book ISBNs
978-3-64-227539-5, 978-3-64-227540-1
Authors

Daniel A. Erlanson, Erlanson DA, Erlanson, Daniel A.

Editors

Thomas G. Davies, Marko Hyvönen

Abstract

Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Italy 1 <1%
Canada 1 <1%
Unknown 179 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 43 24%
Student > Ph. D. Student 31 17%
Student > Master 24 13%
Researcher 13 7%
Student > Doctoral Student 11 6%
Other 19 10%
Unknown 41 23%
Readers by discipline Count As %
Chemistry 56 31%
Biochemistry, Genetics and Molecular Biology 25 14%
Pharmacology, Toxicology and Pharmaceutical Science 25 14%
Agricultural and Biological Sciences 9 5%
Computer Science 4 2%
Other 20 11%
Unknown 43 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 28 May 2023.
All research outputs
#2,372,544
of 26,017,215 outputs
Outputs from Topics in current chemistry
#9
of 154 outputs
Outputs of similar age
#16,941
of 255,923 outputs
Outputs of similar age from Topics in current chemistry
#3
of 12 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 154 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done particularly well, scoring higher than 94% 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 255,923 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 92% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.