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Computer aided identification of a Hevein-like antimicrobial peptide of bell pepper leaves for biotechnological use

Overview of attention for article published in BMC Genomics, December 2016
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Title
Computer aided identification of a Hevein-like antimicrobial peptide of bell pepper leaves for biotechnological use
Published in
BMC Genomics, December 2016
DOI 10.1186/s12864-016-3332-8
Pubmed ID
Authors

Patrícia Dias Games, Elói Quintas Gonçalves daSilva, Meire de Oliveira Barbosa, Hebréia Oliveira Almeida-Souza, Patrícia Pereira Fontes, Marcos Jorge deMagalhães-Jr, Paulo Roberto Gomes Pereira, Maura Vianna Prates, Gloria Regina Franco, Alessandra Faria-Campos, Sérgio Vale Aguiar Campos, Maria Cristina Baracat-Pereira

Abstract

Antimicrobial peptides from plants present mechanisms of action that are different from those of conventional defense agents. They are under-explored but have a potential as commercial antimicrobials. Bell pepper leaves ('Magali R') are discarded after harvesting the fruit and are sources of bioactive peptides. This work reports the isolation by peptidomics tools, and the identification and partially characterization by computational tools of an antimicrobial peptide from bell pepper leaves, and evidences the usefulness of records and the in silico analysis for the study of plant peptides aiming biotechnological uses. Aqueous extracts from leaves were enriched in peptide by salt fractionation and ultrafiltration. An antimicrobial peptide was isolated by tandem chromatographic procedures. Mass spectrometry, automated peptide sequencing and bioinformatics tools were used alternately for identification and partial characterization of the Hevein-like peptide, named HEV-CANN. The computational tools that assisted to the identification of the peptide included BlastP, PSI-Blast, ClustalOmega, PeptideCutter, and ProtParam; conventional protein databases (DB) as Mascot, Protein-DB, GenBank-DB, RefSeq, Swiss-Prot, and UniProtKB; specific for peptides DB as Amper, APD2, CAMP, LAMPs, and PhytAMP; other tools included in ExPASy for Proteomics; The Bioactive Peptide Databases, and The Pepper Genome Database. The HEV-CANN sequence presented 40 amino acid residues, 4258.8 Da, theoretical pI-value of 8.78, and four disulfide bonds. It was stable, and it has inhibited the growth of phytopathogenic bacteria and a fungus. HEV-CANN presented a chitin-binding domain in their sequence. There was a high identity and a positive alignment of HEV-CANN sequence in various databases, but there was not a complete identity, suggesting that HEV-CANN may be produced by ribosomal synthesis, which is in accordance with its constitutive nature. Computational tools for proteomics and databases are not adjusted for short sequences, which hampered HEV-CANN identification. The adjustment of statistical tests in large databases for proteins is an alternative to promote the significant identification of peptides. The development of specific DB for plant antimicrobial peptides, with information about peptide sequences, functional genomic data, structural motifs and domains of molecules, functional domains, and peptide-biomolecule interactions are valuable and necessary.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 53 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 17%
Student > Master 7 13%
Student > Doctoral Student 6 11%
Student > Ph. D. Student 5 9%
Researcher 3 6%
Other 9 17%
Unknown 15 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 33%
Agricultural and Biological Sciences 12 22%
Medicine and Dentistry 2 4%
Unspecified 1 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 4 7%
Unknown 16 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 August 2017.
All research outputs
#20,444,703
of 22,999,744 outputs
Outputs from BMC Genomics
#9,320
of 10,692 outputs
Outputs of similar age
#355,894
of 421,671 outputs
Outputs of similar age from BMC Genomics
#196
of 242 outputs
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So far Altmetric has tracked 10,692 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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