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Home / Equine Research Bank / Mol Divers / In silico prediction of prolactin molecules as a tool for eq...
Molecular diversity2019; 23(4); 1019-1028; doi: 10.1007/s11030-018-09914-3

In silico prediction of prolactin molecules as a tool for equine genomics reproduction.

Abstract: The prolactin hormone is involved in several biological functions, although its main role resides on reproduction. As it interferes on fertility changes, studies focused on human health have established a linkage of this hormone to fertility losses. Regarding animal research, there is still a lack of information about the structure of prolactin. In case of horse breeding, prolactin has a particular influence; once there is an individualization of these animals and equines are known for presenting several reproductive disorders. As there is no molecular structure available for the prolactin hormone and receptor, we performed several bioinformatics analyses through prediction and refinement softwares, as well as manual modifications. Aiming to elucidate the first computational structure of both molecules and analyse structural and functional aspects related to these proteins, here we provide the first known equine model for prolactin and prolactin receptor, which obtained high global quality scores in diverse software's for quality assessment. QMEAN overall score obtained for ePrl was (- 4.09) and QMEANbrane for ePrlr was (- 8.45), which proves the structures' reliability. This study will implement another tool in equine genomics in order to give light to interactions of these molecules, structural and functional alterations and therefore help diagnosing fertility problems, contributing in the selection of a high genetic herd.
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Publication Date: 2019-02-10 PubMed ID: 30740642DOI: 10.1007/s11030-018-09914-3Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research explores the development of an in silico model for prolactin and prolactin receptor molecules, which are important in equine reproduction. More specifically, the study provides a prediction of their structures, which could help in understanding and diagnosing fertility problems in horses.

Research Goals

  • The main aim of the research was to provide a computational structure for prolactin and prolactin receptor molecules given their crucial role in the reproductive functions of horses.
  • The study seeks to illuminate the interactions of these vital proteins and elucidate any structural and functional abnormalities.

Methodology

  • The researchers employed various bioinformatics analyses through prediction, refinement software, and manual modifications.
  • This approach was necessary since there’s currently no molecular structure available for the prolactin hormone and receptor.

Findings

  • The study successfully predicted the molecular structure of these proteins and the constructed models received high quality scores in several software for quality assessment.
  • The QMEAN overall score for the equine prolactin (ePrl) was -4.09, while the prolactin receptor (ePrlr) scored -8.45 on the QMEANbrane. These scores indicate the reliability of the structures.

Implications

  • Understanding the structure and function of these molecules will be beneficial for diagnosing fertility problems and contributing to the selection of a genetically superior herd.
  • The findings present a new tool in equine genomics that could enhance the study of prolactin-related reproductive disorders in other animal species as well.

Cite This Article

APA
Neis A, Kremer FS, Pinto LS, Leon PMM. (2019). In silico prediction of prolactin molecules as a tool for equine genomics reproduction. Mol Divers, 23(4), 1019-1028. https://doi.org/10.1007/s11030-018-09914-3

Publication

Molecular diversity
ISSN: 1573-501X
NlmUniqueID: 9516534
Country: Netherlands
Language: English
Volume: 23
Issue: 4
Pages: 1019-1028

Researcher Affiliations

Neis, A
  • Grupo de Pesquisa em Genômica de Equinos - GenE, Núcleo de Biotecnologia, Centro de Desenvolvimento Tecnológico, Campus Universitário, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Caixa Postal 96010-900, Brazil.
Kremer, F S
  • Laboratório de Bioinformática e Proteômica, Núcleo de Biotecnologia, Centro de Desenvolvimento Tecnológico, Campus Universitário, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Caixa Postal 96010-900, Brazil.
Pinto, L S
  • Laboratório de Bioinformática e Proteômica, Núcleo de Biotecnologia, Centro de Desenvolvimento Tecnológico, Campus Universitário, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Caixa Postal 96010-900, Brazil.
Leon, P M M
  • Grupo de Pesquisa em Genômica de Equinos - GenE, Núcleo de Biotecnologia, Centro de Desenvolvimento Tecnológico, Campus Universitário, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Caixa Postal 96010-900, Brazil. primleon@gmail.com.

MeSH Terms

  • Animals
  • Computer Simulation
  • Genomics
  • Horses
  • Models, Molecular
  • Prolactin / chemistry
  • Receptors, Prolactin / chemistry
  • Reproducibility of Results
  • Reproduction
  • Software

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