Antimicrobial activity predictors benchmarking analysis using shuffled and designed synthetic peptides

Porto, William F.; Pires, Állan S.; Franco, Octávio L.

doi:10.1016/j.jtbi.2017.05.011

Cited by 34 publications

(37 citation statements)

References 51 publications

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“…Besides, the protein‐rich fraction of aurum lily floral tissues present antimicrobial activity against Escherichia coli , which could be a good sign of the possible application of peptides from this family as antibacterial substances (Cândido, Fernandes et al., ). Moreover, despite the antimicrobial activity prediction algorithms are not quite accurate for synthetic peptides (Porto, Pires, & Franco, 2017b), they have a reasonable performance to natural peptides (Mandal et al., ), and ZaLTP7 presents antimicrobial prediction in almost all predictors used in the study (Table ).…”

Section: Discussionmentioning

confidence: 98%

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

et al. 2019

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Antimicrobial peptides (AMPs) are small molecules present in all living beings. Despite their huge sequence variability, AMPs present great structural conservation, mainly in cysteine‐stabilized families. Moreover, in non‐model plants, it is possible to detect cysteine‐stabilized AMPs (cs‐AMPs) with different sequences not covered by conventional searches. Here, we described a threading application for cs‐AMP identification in the non‐model arum lily (Zantedeschia aethiopica) plant, exploring the spathe transcriptome. By using the predicted proteins from the Z. aethiopica transcriptome as our primary source of sequences, we have filtered by using structural alignments of 12 putative cs‐AMP sequences. The two unreported sequences were submitted to PCR validation, and ZaLTP7 gene was confirmed. By using the structure alignments, we classified ZaLTP7 as an LTP type 2‐like. The successful threading application for cs‐AMP identification is an important advance in transcriptomic and proteomic data mining. Besides, the same approach could be applied to the use of NGS public data to discover molecules to combat multidrug‐resistant bacteria.

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Section: Discussionmentioning

confidence: 98%

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

et al. 2019

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“…QUARK ab initio modeling server (36) was used for generating the three-dimensional models of the designed sequences. This server was one of the best ranked servers for free modeling in the last four CASP editions and has been successfully used for predicting the structure-function relationship of short peptides, as described earlier (37–39). Because the minimum input length is 20 amino acid residues, glycine residues were added to the C-terminus of sequences of smaller size.…”

Section: Methodsmentioning

confidence: 99%

EcDBS1R6: A new broad-spectrum cationic antibacterial peptide derived from a signal peptide sequence

Porto

Irazazabal²,

Humblot

et al. 2019

Preprint

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Bacterial infections represent a major worldwide health problem, with an special highlight on Gram-negative bacteria, which were assigned by the World Health Organization (WHO) as the most critical priority for development of novel antimicrobial compounds. Antimicrobial peptides (AMPs) have been considered as potential alternative agents for treating these infections. Here we demonstrated the broad-spectrum activity of EcDBS1R6, a peptide derived from a signal peptide sequence of Escherichia coli that we previously turned into an AMP by making changes predicted through the Joker algorithm.Signal peptides are known to naturally interact with membranes; however, the modifications introduced by Joker made this peptide capable of killing bacteria. Membrane damage of the bacterial cells was observed by measuring membrane integrity using fluorescent probes and through scanning electron microscopy imaging. Structural analysis revealed that the C-terminus was unable to fold into an α -helix, indicating that the EcDBS1R6 antibacterial activity core was located at the N-terminus, corresponding to the signal peptide portion of the parent peptide. Therefore, the strategy of transforming signal peptides into AMPs seems to be promising and could be used for producing novel antimicrobial agents.

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“…Several approaches for the prediction of active peptides from natural templates have been reported over the last decades. 27 Bioinformatics tools have contributed substantially to unravelling the role of descriptors in structure-activity studies and natural motifs leading to important biological functions 28 (Fig. 3).…”

Section: Bioprospection Of Anti-infective Peptidesmentioning

confidence: 99%

Reprogramming biological peptides to combat infectious diseases

Torres

Fuente-Núñez

2019

Chem. Commun.

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Antimicrobial activity predictors benchmarking analysis using shuffled and designed synthetic peptides

Cited by 34 publications

References 51 publications

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

Structure‐guided identification of antimicrobial peptides in the spathe transcriptome of the non‐model plant, arum lily (Zantedeschia aethiopica)

EcDBS1R6: A new broad-spectrum cationic antibacterial peptide derived from a signal peptide sequence

Reprogramming biological peptides to combat infectious diseases

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