Structure-guided identification of antimicrobial peptides in the spathe transcriptome of the non-model plant, arum lily (Zantedeschia aethiopica).
Állan S PiresPietra O RigueirasStephan M DohmsWilliam Farias PortoOctávio Luiz FrancoPublished in: Chemical biology & drug design (2019)
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.
Keyphrases
- single cell
- rna seq
- genome wide
- protein kinase
- multidrug resistant
- gene expression
- electronic health record
- healthcare
- big data
- dna methylation
- mental health
- emergency department
- drug resistant
- genetic diversity
- machine learning
- pseudomonas aeruginosa
- cystic fibrosis
- data analysis
- gram negative
- deep learning
- single molecule