↓ Skip to main content

Dead-End Elimination with a Polarizable Force Field Repacks PCNA Structures

Overview of attention for article published in Biophysical Journal, August 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
2 X users
facebook
1 Facebook page
q&a
1 Q&A thread

Readers on

mendeley
22 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.
Article details
Title
Dead-End Elimination with a Polarizable Force Field Repacks PCNA Structures
Published in
Biophysical Journal, August 2015
DOI 10.1016/j.bpj.2015.06.062
Pubmed ID
Authors
Abstract

A balance of van der Waals, electrostatic, and hydrophobic forces drive the folding and packing of protein side chains. Although such interactions between residues are often approximated as being pairwise additive, in reality, higher-order many-body contributions that depend on environment drive hydrophobic collapse and cooperative electrostatics. Beginning from dead-end elimination, we derive the first algorithm, to our knowledge, capable of deterministic global repacking of side chains compatible with many-body energy functions. The approach is applied to seven PCNA x-ray crystallographic data sets with resolutions 2.5-3.8 Å (mean 3.0 Å) using an open-source software. While PDB_REDO models average an Rfree value of 29.5% and MOLPROBITY score of 2.71 Å (77th percentile), dead-end elimination with the polarizable AMOEBA force field lowered Rfree by 2.8-26.7% and improved mean MOLPROBITY score to atomic resolution at 1.25 Å (100th percentile). For structural biology applications that depend on side-chain repacking, including x-ray refinement, homology modeling, and protein design, the accuracy limitations of pairwise additivity can now be eliminated via polarizable or quantum mechanical potentials.

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 9%
Portugal 1 5%
Unknown 19 86%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 10 45%
Researcher 5 23%
Student > Bachelor 1 5%
Professor 1 5%
Professor > Associate Professor 1 5%
Other 1 5%
Unknown 3 14%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 23%
Agricultural and Biological Sciences 5 23%
Chemistry 3 14%
Computer Science 2 9%
Physics and Astronomy 1 5%
Other 2 9%
Unknown 4 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 November 2019.
All research outputs
#8,505,267
of 29,164,447 outputs
Outputs from Biophysical Journal
#2,844
of 10,855 outputs
Outputs of similar age
#82,558
of 281,042 outputs
Outputs of similar age from Biophysical Journal
#17
of 92 outputs
Altmetric has tracked 29,164,447 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 10,855 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 73% 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 281,042 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.