Even before the perception or interaction with pathogens, plants rely on constitutively guardian molecules, often specific to tissue or stage, with further expression after contact with the pathogen. These guardians include small molecules as antimicrobial peptides (AMPs), generally cysteine-rich, functioning to prevent pathogen establishment. Some of these AMPs are shared among eukaryotes (eg, defensins and cyclotides), others are plant specific (eg, snakins), while some are specific to certain plant families (such as heveins). When compared with other organisms, plants tend to present a higher amount of AMP isoforms due to gene duplications or polyploidy, an occurrence possibly also associated with the sessile habit of plants, which prevents them from evading biotic and environmental stresses. Therefore, plants arise as a rich resource for new AMPs. As these molecules are difficult to retrieve from databases using simple sequence alignments, a description of their characteristics and in silico (bioinformatics) approaches used to retrieve them is provided, considering resources and databases available. The possibilities and applications based on tools versus database approaches are considerable and have been so far underestimated.

Snakins are plant antimicrobial peptides (AMPs) of the Snakin/GASA family, formed by three distinct regions: an N-terminal signal peptide; a variable site; and the GASA domain in the Cterminal region composed by twelve conserved cysteine residues that contribute to the biochemical stability of the molecule. These peptides are known to play different roles in response to a variety of biotic (i.e., induced by bacteria, fungi and nematode pathogens) and abiotic (salinity, drought and ROS) stressors, as well as in crosstalk promoted by plant hormones, with emphasis on abscisic and salicylic acid (ABA and SA, respectively). Such properties make snakin/GASA members promising biotechnological sources for potential therapeutic and agricultural applications. However, information regarding their tertiary structure, mode of action and function are not yet completely elucidated. The present review presents aspects of snakin structure, expression, functional studies and perspectives about the potential applications for agricultural and medical purposes.

Lipid transfer proteins (LTPs) are among the most promising plant-exclusive antimicrobial peptides (AMPs). They figure among the most challenging AMPs from the point of view of their structural diversity, functions and biotechnological applications. This review presents a current picture of the LTP research, addressing not only their structural, evolutionary and further predicted functional aspects. Traditionally, LTPs have been identified by their direct isolation by biochemical techniques, whereas omics data and bioinformatics deserve special attention for their potential to bring new insights. In this context, new possible functions have been identified revealing that LTPs are actually multipurpose, with many additional predicted roles. Despite some challenges due to the toxicity and allergenicity of LTPs, a systematic review and search in patent databases, indicate promising perspectives for the biotechnological use of LTPs in human health and also plant defense.

Background: The amount of published full-text articles has increased dramatically. Text mining tools configure an essential approach to building biological networks, updating databases and providing annotation for new pathways. PESCADOR is an online web server based on LAITOR and NLProt text mining tools, which retrieves protein-protein co-occurrences in a tabular-based format, adding a network schema. Here we present an HPC-oriented version of PESCADOR's native text mining tool, renamed to LAITOR4HPC, aiming to access an unlimited abstract amount in a short time to enrich available networks, build new ones and possibly highlight whether fields of research have been exhaustively studied. Results: By taking advantage of parallel computing HPC infrastructure, the full collection of MEDLINE abstracts available until June 2017 was analyzed in a shorter period (6 days) when compared to the original online implementation (with an estimated 2 years to run the same data). Additionally, three case studies were presented to illustrate LAITOR4HPC usage possibilities. The first case study targeted soybean and was used to retrieve an overview of published co-occurrences in a single organism, retrieving 15,788 proteins in 7894 cooccurrences. In the second case study, a target gene family was searched in many organisms, by analyzing 15 species under biotic stress. Most co-occurrences regarded Arabidopsis thaliana and Zea mays. The third case study concerned the construction and enrichment of an available pathway. Choosing A. thaliana for further analysis, the defensin pathway was enriched, showing additional signaling and regulation molecules, and how they respond to each other in the modulation of this complex plant defense response. Conclusions: LAITOR4HPC can be used for an efficient text mining based construction of biological networks derived from big data sources, such as MEDLINE abstracts. Time consumption and data input limitations will depend on the available resources at the HPC facility. LAITOR4HPC enables enough flexibility for different approaches and data amounts targeted to an organism, a subject, or a specific pathway. Additionally, it can deliver comprehensive results where interactions are classified into four types, according to their reliability.