Evidence map›Paper›PMID 34143323›Full record

ArticleJournal of computer-aided molecular design2022

Progress on open chemoinformatic tools for expanding and exploring the chemical space.

José L Medina-Franco, Norberto Sánchez-Cruz, Edgar López-López, Bárbara I Díaz-Eufracio

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Growth vs Diversity: A Time-Evolution Analysis of the Chemical Space.Journal of chemical information and modeling · 2025
    Article
  9. Article
  10. Machine learning-based bioactivity prediction of porphyrin derivatives: molecular descriptors, clustering, and model evaluation.Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2025
    Article
  11. Article
  12. Molecular similarity: Theory, applications, and perspectives.Artificial intelligence chemistry · 2024
    Article
  13. Article
  14. Article
  15. One chiral fingerprint to find them all.Journal of cheminformatics · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

José L Medina-FrancoDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico. medinajl@unam.mx.ORCID 0000-0003-4940-1107
Norberto Sánchez-CruzDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico.ORCID 0000-0003-2707-3966
Edgar López-LópezDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico.ORCID 0000-0002-7422-6059
Bárbara I Díaz-EufracioDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico.ORCID 0000-0001-6219-5972

Funding

Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México IN201321
6 · The paper itself

Abstract

The concept of chemical space is a cornerstone in chemoinformatics, and it has broad conceptual and practical applicability in many areas of chemistry, including drug design and discovery. One of the most considerable impacts is in the study of structure-property relationships where the property can be a biological activity or any other characteristic of interest to a particular chemistry discipline. The chemical space is highly dependent on the molecular representation that is also a cornerstone concept in computational chemistry. Herein, we discuss the recent progress on chemoinformatic tools developed to expand and characterize the chemical space of compound data sets using different types of molecular representations, generate visual representations of such spaces, and explore structure-property relationships in the context of chemical spaces. We emphasize the development of methods and freely available tools focusing on drug discovery applications. We also comment on the general advantages and shortcomings of using freely available and easy-to-use tools and discuss the value of using such open resources for research, education, and scientific dissemination.

Indexed as

CheminformaticsDrug DiscoveryDrug DesignChemoinformaticsDrug discoveryMolecular representationOpen-sourceStructure–activity relationshipsWebserver

Identifiers

PMID34143323
PMCPMC8211976

What OpenQuestion holds

Textmetadata
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.