↓ Skip to main content

Flexible CDOCKER: Development and application of a pseudo‐explicit structure‐based docking method within CHARMM

Overview of attention for article published in Journal of Computational Chemistry, December 2015
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

twitter
4 X users

Citations

dimensions_citation
90 Dimensions

Readers on

mendeley
73 Mendeley
citeulike
1 CiteULike
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
Flexible CDOCKER: Development and application of a pseudo‐explicit structure‐based docking method within CHARMM
Published in
Journal of Computational Chemistry, December 2015
DOI 10.1002/jcc.24259
Pubmed ID
Authors

Jessica K Gagnon, Sean M Law, Charles L Brooks

Abstract

Protein-ligand docking is a commonly used method for lead identification and refinement. While traditional structure-based docking methods represent the receptor as a rigid body, recent developments have been moving toward the inclusion of protein flexibility. Proteins exist in an interconverting ensemble of conformational states, but effectively and efficiently searching the conformational space available to both the receptor and ligand remains a well-appreciated computational challenge. To this end, we have developed the Flexible CDOCKER method as an extension of the family of complete docking solutions available within CHARMM. This method integrates atomically detailed side chain flexibility with grid-based docking methods, maintaining efficiency while allowing the protein and ligand configurations to explore their conformational space simultaneously. This is in contrast to existing approaches that use induced-fit like sampling, such as Glide or Autodock, where the protein or the ligand space is sampled independently in an iterative fashion. Presented here are developments to the CHARMM docking methodology to incorporate receptor flexibility and improvements to the sampling protocol as demonstrated with re-docking trials on a subset of the CCDC/Astex set. These developments within CDOCKER achieve docking accuracy competitive with or exceeding the performance of other widely utilized docking programs. © 2015 Wiley Periodicals, Inc.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Italy 1 1%
Unknown 71 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 18%
Researcher 13 18%
Student > Bachelor 7 10%
Student > Doctoral Student 5 7%
Professor 5 7%
Other 13 18%
Unknown 17 23%
Readers by discipline Count As %
Chemistry 22 30%
Agricultural and Biological Sciences 12 16%
Biochemistry, Genetics and Molecular Biology 8 11%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Engineering 2 3%
Other 4 5%
Unknown 21 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 July 2017.
All research outputs
#14,098,507
of 24,571,708 outputs
Outputs from Journal of Computational Chemistry
#1,021
of 2,153 outputs
Outputs of similar age
#188,424
of 399,998 outputs
Outputs of similar age from Journal of Computational Chemistry
#17
of 58 outputs
Altmetric has tracked 24,571,708 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,153 research outputs from this source. They receive a mean Attention Score of 3.8. This one has gotten more attention than average, scoring higher than 51% 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 399,998 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 52% of its contemporaries.
We're also able to compare this research output to 58 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 67% of its contemporaries.