Evidence map›Paper›PMID 32500478›Full record

ArticleJournal of computer-aided molecular design2020

Simplified activity cliff network representations with high interpretability and immediate access to SAR information.

Huabin Hu, Jürgen Bajorath

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

2 authors.

Huabin HuDepartment of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, 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, 53115, Bonn, Germany. bajorath@bit.uni-bonn.de.ORCID 0000-0002-0557-5714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Activity cliffs (ACs) consist of structurally similar compounds with a large difference in potency against their target. Accordingly, ACs introduce discontinuity in structure-activity relationships (SARs) and are a prime source of SAR information. In compound data sets, the vast majority of ACs are formed by differently sized groups of structurally similar compounds with large potency variations. As a consequence, many of these compounds participate in multiple ACs. This coordinated formation of ACs increases their SAR information content compared to ACs considered as individual compound pairs, but complicates AC analysis. In network representations, coordinated ACs give rise to clusters of varying size and topology, which can be interactively and computationally analyzed. While AC networks are indispensable tools to study coordinated ACs, they become difficult to navigate and interpret in the presence of clusters of increasing size and complex topologies. Herein, we introduce reduced network representations that transform AC networks into an easily interpretable format from which SAR information in the form of R-group tables can be readily obtained. The simplified network variant greatly improves the interpretability of large and complex AC networks and substantially supports SAR exploration.

Indexed as

Chemistry, PharmaceuticalDrug DesignCluster AnalysisComputational BiologyHumansMolecular StructurePharmaceutical PreparationsStructure-Activity RelationshipPharmaceutical PreparationsActivity cliffsMatching molecular seriesReduced activity cliff networksR-group tablesSAR information

Identifiers

PMID32500478
PMCPMC7367913

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.