| Title |
Fragment-based drug discovery using NMR spectroscopy
|
|---|---|
| Published in |
Journal of Biomolecular NMR, May 2013
|
| DOI | 10.1007/s10858-013-9740-z |
| Pubmed ID | |
| Authors |
Mary J. Harner, Andreas O. Frank, Stephen W. Fesik |
| Abstract |
Nuclear magnetic resonance (NMR) spectroscopy has evolved into a powerful tool for fragment-based drug discovery over the last two decades. While NMR has been traditionally used to elucidate the three-dimensional structures and dynamics of biomacromolecules and their interactions, it can also be a very valuable tool for the reliable identification of small molecules that bind to proteins and for hit-to-lead optimization. Here, we describe the use of NMR spectroscopy as a method for fragment-based drug discovery and how to most effectively utilize this approach for discovering novel therapeutics based on our experience. |
Mendeley readers
The data shown below were compiled from readership statistics for 362 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | <1% |
| Germany | 1 | <1% |
| Switzerland | 1 | <1% |
| United Kingdom | 1 | <1% |
| Norway | 1 | <1% |
| Canada | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 354 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 105 | 29% |
| Researcher | 54 | 15% |
| Student > Master | 39 | 11% |
| Student > Bachelor | 39 | 11% |
| Student > Doctoral Student | 15 | 4% |
| Other | 47 | 13% |
| Unknown | 63 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 115 | 32% |
| Biochemistry, Genetics and Molecular Biology | 69 | 19% |
| Agricultural and Biological Sciences | 49 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 36 | 10% |
| Engineering | 5 | 1% |
| Other | 18 | 5% |
| Unknown | 70 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 21 July 2016.
All research outputs
#3,470,002
of 25,837,817 outputs
Outputs from Journal of Biomolecular NMR
#31
of 563 outputs
Outputs of similar age
#28,797
of 211,645 outputs
Outputs of similar age from Journal of Biomolecular NMR
#2
of 5 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 563 research outputs from this source. They receive a mean Attention Score of 3.2. 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 211,645 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.