Evidence map›Paper›PMID 33479613›Full record

ArticleRSC medicinal chemistry2020

Introducing a new category of activity cliffs combining different compound similarity criteria.

Huabin Hu, Jürgen Bajorath

Abstract read
In one paragraph

Article in RSC medicinal chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Exposing the Limitations of Molecular Machine Learning with Activity Cliffs.Journal of chemical information and modeling · 2022
    Article
  3. Article
  4. Article
  5. Advances in exploring activity cliffs.Journal of computer-aided molecular design · 2020
    Article
  6. 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 , D-53115 Bonn , Germany . Email: bajorath@bit.uni-bonn.de ; ; Tel: +49 228 7369 100.
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 . Email: bajorath@bit.uni-bonn.de ; ; Tel: +49 228 7369 100.ORCID 0000-0002-0557-5714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Activity cliffs (ACs) are pairs of structurally similar or analogous active compounds with large differences in potency against the same target. For identifying and analyzing ACs, similarity and potency difference criteria must be determined and consistently applied. This can be done in various ways, leading to different types of ACs. In this work, we introduce a new category of ACs by combining different similarity criteria, including the formation of matched molecular pairs and structural isomer relationships. A systematic computational search identified such ACs in compounds with activity against a variety of targets. In addition to other ACs exclusively formed by structural isomers, the newly introduced category of ACs is rich in structure-activity relationship (SAR) information, straightforward to interpret from a chemical perspective, and further extends the current spectrum of ACs.

Identifiers

PMID33479613
PMCPMC7484988

What OpenQuestion holds

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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.