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Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pKa corrections

Overview of attention for article published in Perspectives in Drug Discovery and Design, September 2016
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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 (81st percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Citations

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Title
Blind prediction of distribution in the SAMPL5 challenge with QM based protomer and pKa corrections
Published in
Perspectives in Drug Discovery and Design, September 2016
DOI 10.1007/s10822-016-9955-7
Pubmed ID
Authors

Frank C. Pickard, Gerhard König, Florentina Tofoleanu, Juyong Lee, Andrew C. Simmonett, Yihan Shao, Jay W. Ponder, Bernard R. Brooks

Abstract

The computation of distribution coefficients between polar and apolar phases requires both an accurate characterization of transfer free energies between phases and proper accounting of ionization and protomerization. We present a protocol for accurately predicting partition coefficients between two immiscible phases, and then apply it to 53 drug-like molecules in the SAMPL5 blind prediction challenge. Our results combine implicit solvent QM calculations with classical MD simulations using the non-Boltzmann Bennett free energy estimator. The OLYP/DZP/SMD method yields predictions that have a small deviation from experiment (RMSD = 2.3 [Formula: see text] D units), relative to other participants in the challenge. Our free energy corrections based on QM protomer and [Formula: see text] calculations increase the correlation between predicted and experimental distribution coefficients, for all methods used. Unfortunately, these corrections are overly hydrophilic, and fail to account for additional effects such as aggregation, water dragging and the presence of polar impurities in the apolar phase. We show that, although expensive, QM-NBB free energy calculations offer an accurate and robust method that is superior to standard MM and QM techniques alone.

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X Demographics

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Mendeley readers

Mendeley readers

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.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 21 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 36%
Student > Ph. D. Student 6 27%
Professor 2 9%
Student > Doctoral Student 2 9%
Student > Bachelor 1 5%
Other 1 5%
Unknown 2 9%
Readers by discipline Count As %
Chemistry 6 27%
Computer Science 3 14%
Biochemistry, Genetics and Molecular Biology 2 9%
Agricultural and Biological Sciences 1 5%
Chemical Engineering 1 5%
Other 2 9%
Unknown 7 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 29 June 2021.
All research outputs
#3,795,801
of 25,457,297 outputs
Outputs from Perspectives in Drug Discovery and Design
#132
of 949 outputs
Outputs of similar age
#61,105
of 328,500 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#8
of 28 outputs
Altmetric has tracked 25,457,297 research outputs across all sources so far. Compared to these this one has done well and is in the 85th 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 well, scoring higher than 85% 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 328,500 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 81% of its contemporaries.
We're also able to compare this research output to 28 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 71% of its contemporaries.