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Protein–ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3

Overview of attention for article published in Perspectives in Drug Discovery and Design, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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Title
Protein–ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3
Published in
Perspectives in Drug Discovery and Design, August 2018
DOI 10.1007/s10822-018-0148-4
Pubmed ID
Authors

Panagiotis I. Koukos, Li C. Xue, Alexandre M. J. J. Bonvin

Abstract

We report the performance of HADDOCK in the 2018 iteration of the Grand Challenge organised by the D3R consortium. Building on the findings of our participation in last year's challenge, we significantly improved our pose prediction protocol which resulted in a mean RMSD for the top scoring pose of 3.04 and 2.67 Å for the cross-docking and self-docking experiments respectively, which corresponds to an overall success rate of 63% and 71% when considering the top1 and top5 models respectively. This performance ranks HADDOCK as the 6th and 3rd best performing group (excluding multiple submissions from a same group) out of a total of 44 and 47 submissions respectively. Our ligand-based binding affinity predictor is the 3rd best predictor overall, behind only the two leading structure-based implementations, and the best ligand-based one with a Kendall's Tau correlation of 0.36 for the Cathepsin challenge. It also performed well in the classification part of the Kinase challenges, with Matthews Correlation Coefficients of 0.49 (ranked 1st), 0.39 (ranked 4th) and 0.21 (ranked 4th) for the JAK2, vEGFR2 and p38a targets respectively. Through our participation in last year's competition we came to the conclusion that template selection is of critical importance for the successful outcome of the docking. This year we have made improvements in two additional areas of importance: ligand conformer selection and initial positioning, which have been key to our excellent pose prediction performance this year.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 30%
Student > Ph. D. Student 5 14%
Student > Master 4 11%
Student > Doctoral Student 3 8%
Student > Bachelor 2 5%
Other 4 11%
Unknown 8 22%
Readers by discipline Count As %
Chemistry 10 27%
Biochemistry, Genetics and Molecular Biology 5 14%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Agricultural and Biological Sciences 2 5%
Computer Science 2 5%
Other 4 11%
Unknown 12 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 04 May 2019.
All research outputs
#3,062,128
of 25,461,852 outputs
Outputs from Perspectives in Drug Discovery and Design
#93
of 949 outputs
Outputs of similar age
#58,862
of 342,215 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#2
of 27 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. Compared to these this one has done well and is in the 87th 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 90% 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 342,215 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 82% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.