↓ Skip to main content

Determination of ligand binding modes in weak protein–ligand complexes using sparse NMR data

Overview of attention for article published in Journal of Biomolecular NMR, October 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
45 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Determination of ligand binding modes in weak protein–ligand complexes using sparse NMR data
Published in
Journal of Biomolecular NMR, October 2016
DOI 10.1007/s10858-016-0067-4
Pubmed ID
Authors

Biswaranjan Mohanty, Martin L. Williams, Bradley C. Doak, Mansha Vazirani, Olga Ilyichova, Geqing Wang, Wolfgang Bermel, Jamie S. Simpson, David K. Chalmers, Glenn F. King, Mehdi Mobli, Martin J. Scanlon

Abstract

We describe a general approach to determine the binding pose of small molecules in weakly bound protein-ligand complexes by deriving distance constraints between the ligand and methyl groups from all methyl-containing residues of the protein. We demonstrate that using a single sample, which can be prepared without the use of expensive precursors, it is possible to generate high-resolution data rapidly and obtain the resonance assignments of Ile, Leu, Val, Ala and Thr methyl groups using triple resonance scalar correlation data. The same sample may be used to obtain Met (ε)CH3 assignments using NOESY-based methods, although the superior sensitivity of NOESY using [U-(13)C,(15)N]-labeled protein makes the use of this second sample more efficient. We describe a structural model for a weakly binding ligand bound to its target protein, DsbA, derived from intermolecular methyl-to-ligand nuclear Overhauser enhancements, and demonstrate that the ability to assign all methyl resonances in the spectrum is essential to derive an accurate model of the structure. Once the methyl assignments have been obtained, this approach provides a rapid means to generate structural models for weakly bound protein-ligand complexes. Such weak complexes are often found at the beginning of programs of fragment based drug design and can be challenging to characterize using X-ray crystallography.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 33%
Student > Bachelor 6 13%
Student > Ph. D. Student 5 11%
Professor > Associate Professor 4 9%
Professor 2 4%
Other 5 11%
Unknown 8 18%
Readers by discipline Count As %
Chemistry 17 38%
Biochemistry, Genetics and Molecular Biology 12 27%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Agricultural and Biological Sciences 3 7%
Engineering 1 2%
Other 0 0%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 November 2016.
All research outputs
#4,170,095
of 22,901,818 outputs
Outputs from Journal of Biomolecular NMR
#51
of 615 outputs
Outputs of similar age
#69,770
of 313,860 outputs
Outputs of similar age from Journal of Biomolecular NMR
#3
of 8 outputs
Altmetric has tracked 22,901,818 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 615 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done particularly well, scoring higher than 91% 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 313,860 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 77% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.