Evidence map›Paper›PMID 41361326›Full record

ArticleJournal of cheminformatics2025

SMARTS-RX: a SMARTS-based representation of chemical functions for reactivity analysis.

Thierry Kogej, Christos Kannas, Samuel Genheden, Eike Caldeweyher, Mikhail Kabeshov

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2025. 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

5 authors.

Thierry KogejMolecular AI, Discovery Sciences, R&D AstraZeneca, 431 83, Gothenburg, Sweden. thierry.kogej@astrazeneca.com.
Christos KannasMolecular AI, Discovery Sciences, R&D AstraZeneca, 431 83, Gothenburg, Sweden.
Samuel GenhedenMolecular AI, Discovery Sciences, R&D AstraZeneca, 431 83, Gothenburg, Sweden.
Eike CaldeweyherAugmented DMTA Engineering, R&D IT, AstraZeneca, 43183, Gothenburg, Sweden.
Mikhail KabeshovMolecular AI, Discovery Sciences, R&D AstraZeneca, 431 83, Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chemical functional group annotation provides a mechanistically meaningful framework to interpret model outcomes and guide synthetic strategies. Here, we present SMARTS-RX-a curated, hierarchical ontology of 406 SMARTS-based functional group descriptors-designed to characterize chemically relevant and reactive functionalities in small molecules. SMARTS-RX achieves a balance between granularity and computational efficiency by focusing on functional groups central to pharmaceutical synthesis and medicinal chemistry. We describe the development of SMARTS-RX, including its systematic nomenclature and SMARTS encoding, which enable precise tracking of chemical environments. The utility of SMARTS-RX for mapping chemical reactivity is demonstrated through analyses of functional group distributions across major reaction types, using large-scale datasets from AstraZeneca's Electronic Lab Notebooks and Reaxys. Finally, we illustrate how this SMARTS library can be applied to guide building-block selection from commercial catalogues. A public GitHub repository has been created aiming for a continuous improvement of the current SMARTS_RX.Scientific Contribution: SMARTS-RX introduces a curated, hierarchical ontology of 406 SMARTS-based descriptors prioritizing pharmaceutical relevance and mechanistic interpretability. Distinct from prior efforts, SMARTS-RX encodes detailed chemical environments to improve reactivity mapping and feature extraction for both expert analysis and computational modelling. This resource advances functional group annotation by balancing chemical specificity and computational performance, supporting reproducible and scalable cheminformatics research.

Indexed as

CheminformaticsOrganic chemistrySMARTS patternsSubstructure search

Identifiers

PMID41361326
PMCPMC12690859

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.