Evidence map›Paper›PMID 33388027›Full record

ArticleBMC bioinformatics2021

Propedia: a database for protein-peptide identification based on a hybrid clustering algorithm.

Pedro M Martins, Lucianna H Santos, Diego Mariano, Felippe C Queiroz, Luana L Bastos, Isabela de S Gomes, Pedro H C Fischer, Rafael E O Rocha, Sabrina A Silveira, Leonardo H F de Lima and 3 more

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
11.8field-weighted citation impact, top 1% of its field
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

18 citing papers in PubMed, 182 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. State-Specific Peptide Design Targeting G Protein-Coupled Receptors.Journal of chemical information and modeling · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

13 authors at 3 institutions in 1 country.

Pedro M MartinsLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.ORCID http://orcid.org/0000-0002-2446-872X
Lucianna H SantosLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.
Diego MarianoLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.
Felippe C QueirozDepartment of Computer Science, Universidade Federal de Viçosa, Av Peter Henry Rolfs, Viçosa, MG, Brazil.
Luana L BastosLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.
Isabela de S GomesDepartment of Computer Science, Universidade Federal de Viçosa, Av Peter Henry Rolfs, Viçosa, MG, Brazil.
Pedro H C FischerLaboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del-Rei, Rua Sétimo Moreira Martins, Sete Lagoas, MG, Brazil.
Rafael E O RochaLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.
Sabrina A SilveiraDepartment of Computer Science, Universidade Federal de Viçosa, Av Peter Henry Rolfs, Viçosa, MG, Brazil.
Leonardo H F de LimaLaboratory of Molecular Modeling and Bioinformatics, Department of Exact and Biological Sciences, Universidade Federal de São João Del-Rei, Rua Sétimo Moreira Martins, Sete Lagoas, MG, Brazil.
Mariana T Q de MagalhãesMacromolecule Biophysics Laboratory (LBM), Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil.
Maria G A OliveiraDepartment of Biochemistry and Molecular Biology, Universidade Federal de Viçosa, Av Peter Henry Rolfs, Viçosa, MG, Brazil.
Raquel C de Melo-MinardiLaboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Universidade Federal de Minas Gerais, Av Pres. Antônio Carlos, Belo Horizonte, MG, 31720-901, Brazil. raquelcm@dcc.ufmg.br.
Universidade Federal de Minas Gerais · BRUniversidade Federal de Viçosa · BRFederal University of São João del-Rei · BR

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 51/2013 - 23038.004007/2014-82
6 · The paper itself

Abstract

backgroundProtein-peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein-peptide databases and tools that allow the retrieval, characterization and understanding of protein-peptide recognition and consequently support peptide design.

resultsWe introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein-peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein-peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation.

conclusionsPropedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein-peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia.

Indexed as

Database Management SystemsDatabases, ProteinAlgorithmsHumansPeptidesProteinsPeptidesProteinsClusteringDatabasePeptidesProtein designProtein–peptide complexesProtein structureWebserver

Identifiers

PMID33388027
PMCPMC7776311
OpenAlexW3120712761

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.