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Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics

Overview of attention for article published in Perspectives in Drug Discovery and Design, May 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
2 blogs

Citations

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60 Dimensions

Readers on

mendeley
111 Mendeley
citeulike
2 CiteULike
Title
Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics
Published in
Perspectives in Drug Discovery and Design, May 2011
DOI 10.1007/s10822-011-9434-0
Pubmed ID
Authors

Wan F. Lau, Jane M. Withka, David Hepworth, Thomas V. Magee, Yuhua J. Du, Gregory A. Bakken, Michael D. Miller, Zachary S. Hendsch, Venkataraman Thanabal, Steve A. Kolodziej, Li Xing, Qiyue Hu, Lakshmi S. Narasimhan, Robert Love, Maura E. Charlton, Samantha Hughes, Willem P. van Hoorn, James E. Mills

Abstract

Fragment Based Drug Discovery (FBDD) continues to advance as an efficient and alternative screening paradigm for the identification and optimization of novel chemical matter. To enable FBDD across a wide range of pharmaceutical targets, a fragment screening library is required to be chemically diverse and synthetically expandable to enable critical decision making for chemical follow-up and assessing new target druggability. In this manuscript, the Pfizer fragment library design strategy which utilized multiple and orthogonal metrics to incorporate structure, pharmacophore and pharmacological space diversity is described. Appropriate measures of molecular complexity were also employed to maximize the probability of detection of fragment hits using a variety of biophysical and biochemical screening methods. In addition, structural integrity, purity, solubility, fragment and analog availability as well as cost were important considerations in the selection process. Preliminary analysis of primary screening results for 13 targets using NMR Saturation Transfer Difference (STD) indicates the identification of uM-mM hits and the uniqueness of hits at weak binding affinities for these targets.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Germany 1 <1%
Portugal 1 <1%
Russia 1 <1%
United Kingdom 1 <1%
Unknown 105 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 30%
Student > Ph. D. Student 26 23%
Student > Master 11 10%
Student > Bachelor 8 7%
Student > Doctoral Student 5 5%
Other 15 14%
Unknown 13 12%
Readers by discipline Count As %
Chemistry 47 42%
Agricultural and Biological Sciences 19 17%
Biochemistry, Genetics and Molecular Biology 15 14%
Computer Science 5 5%
Medicine and Dentistry 5 5%
Other 4 4%
Unknown 16 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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
#2,638,193
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#69
of 949 outputs
Outputs of similar age
#12,003
of 123,160 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#4
of 16 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% 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 92% 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 123,160 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 90% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.