ArticleJournal of computer-aided molecular design2017
Exploring sets of molecules from patents and relationships to other active compounds in chemical space networks.
Article in Journal of computer-aided molecular design, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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.
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Who cites it
5 citing papers in PubMed.
- Exploring SureChEMBL from a drug discovery perspective.Scientific data · 2024Article
- Making sense of chemical space network shows signs of criticality.Scientific reports · 2023Article
- Visualizing chemical space networks with RDKit and NetworkX.Journal of cheminformatics · 2022Article
- Progress on open chemoinformatic tools for expanding and exploring the chemical space.Journal of computer-aided molecular design · 2022Article
- Congenericity of Claimed Compounds in Patent Applications.Molecules (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patents from medicinal chemistry represent a rich source of novel compounds and activity data that appear only infrequently in the scientific literature. Moreover, patent information provides a primary focal point for drug discovery. Accordingly, text mining and image extraction approaches have become hot topics in patent analysis and repositories of patent data are being established. In this work, we have generated network representations using alternative similarity measures to systematically compare molecules from patents with other bioactive compounds, visualize similarity relationships, explore the chemical neighbourhood of patent molecules, and identify closely related compounds with different activities. The design of network representations that combine patent molecules and other bioactive compounds and view patent information in the context of current bioactive chemical space aids in the analysis of patents and further extends the use of molecular networks to explore structure-activity relationships.
Indexed as
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Registered trials
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.