Evidence map›Paper›PMID 32984733›Full record

ArticleACS omega2020

Quantitative Comparison of Three-Dimensional Activity Landscapes of Compound Data Sets Based upon Topological Features.

Javed Iqbal, Martin Vogt, Jürgen Bajorath

Abstract read
In one paragraph

Article in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Javed IqbalDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Martin VogtDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.
Jürgen BajorathDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visualization of structure-activity relationships (SARs) in compound data sets substantially contributes to their systematic analysis. For SAR visualization, different types of activity landscape (AL) representations have been introduced. Three-dimensional (3D) AL models in which an activity hypersurface is constructed in chemical space are particularly intuitive because these 3D ALs are reminiscent of "true" (geographical) landscapes. Accordingly, the topologies of 3D AL representations can be immediately associated with different SAR characteristics of compound data sets. However, the comparison of 3D ALs has thus far been confined to visual inspection and qualitative analysis. We have focused on image analysis as a possible approach to facilitate a quantitative comparison of 3D ALs, which would further increase their utility for SAR exploration. Herein, we introduce a new computational methodology for quantifying topological relationships between 3D ALs. Images of color-coded 3D ALs were converted into top-down views of these ALs. From transformed images, different categories of shape features were systematically extracted, and multilevel shape correspondence was determined as a measure of AL similarity. This made it possible to differentiate between 3D ALs in quantitative terms.

Identifiers

PMID32984733
PMCPMC7513547

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.