Evidence map›Paper›PMID 28224019›Full record

ArticleJournal of cheminformatics2017

Database fingerprint (DFP): an approach to represent molecular databases.

Eli Fernández-de Gortari, César R García-Jacas, Karina Martinez-Mayorga, José L Medina-Franco

Abstract read
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Article in Journal of cheminformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Article
  2. Review
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  6. Article
  7. iSIM: instant similarity.Digital discovery · 2024
    Article
  8. Chemical Multiverse and Diversity of Food Chemicals.Journal of chemical information and modeling · 2024
    Article
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  10. Review
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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.

Eli Fernández-de GortariDepartamento de Farmacia, Facultad de Química, Universidad Nacional Autónoma de México, Avenida Universidad 3000, 04510 Mexico City, Mexico.
César R García-JacasInstituto de Química, Universidad Nacional Autónoma de México, Avenida Universidad 3000, 04510 Mexico City, Mexico.
Karina Martinez-MayorgaInstituto de Química, Universidad Nacional Autónoma de México, Avenida Universidad 3000, 04510 Mexico City, Mexico.
José L Medina-FrancoDepartamento de Farmacia, Facultad de Química, Universidad Nacional Autónoma de México, Avenida Universidad 3000, 04510 Mexico City, Mexico.ORCID 0000-0003-4940-1107

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMolecular fingerprints are widely used in several areas of chemoinformatics including diversity analysis and similarity searching. The fingerprint-based analysis of chemical libraries, in particular of large collections, usually requires the molecular representation of each compound in the library that may lead to issues of storage space and redundant calculations. In fact, information redundancy is inherent to the data, resulting on binary digit positions in the fingerprint without significant information.

resultsHerein is proposed a general approach to represent an entire compound library with a single binary fingerprint. The development of the database fingerprint (DFP) is illustrated first using a short fingerprint (MACCS keys) for 10 data sets of general interest in chemistry. The application of the DFP is further shown with PubChem fingerprints for the data sets used in the primary example but with a larger number of compounds, up to 25,000 molecules. The performance of DFP were studied through differential Shannon entropy, k-mean clustering, and DFP/Tanimoto similarity.

conclusionsThe DFP is designed to capture key information of the compound collection and can be used to compare and assess the diversity of molecular libraries. This Preliminary Communication shows the potential of the novel fingerprint to conduct inter-library relationships. A major future goal is to apply the DFP for virtual screening and developing DFP for other data sets based on several different type of fingerprints.Graphical AbstractDatabase fingerprint captures the key information of molecular databases to perform chemical space characterization and virtual screening.

Indexed as

DiversityInformation contentMolecular fingerprintsShannon entropySimilarity

Identifiers

PMID28224019
PMCPMC5293704

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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.