Advancing rational pesticide development against Drosophila suzukii: bioinformatics tools and applications—a systematic review

Drosophila suzukii (Matsumura, 1931) is a widespread agricultural pest responsible for significant damage to various soft-skinned fruit hosts. The revolutionary potential of bioinformatics in agriculture emerges from its ability to provide extensive information on pests, fungi, chemical resistance, implications of non-target species, and other critical aspects. This wealth of information allows researchers to engage in projects and applied research in diverse agricultural domains that face these challenges. In this context, bioinformatics tools play a fundamental role. The negative impact of pests on crops, resulting in substantial economic losses, has highlighted the importance of in silico methods.

To achieve this, we conducted a systematic search in scientific databases using as keywords “Drosophila suzukii,” “biopesticides,” “simulations computational,” and “in-silico.” After applying the filters of relevance and publication date, we organized the articles and prioritized those that directly addressed that matched the keywords and the use of bioinformatics tools. Additionally, we included studies focusing on in silico assays of biopesticides, such as molecular docking. Our review aimed to present a collection of recent literature on biopesticides against Drosophila suzukii, emphasizing bioinformatics methods. Through this work, we strive to contribute to the literature of new perspectives on the development and efficiency of biopesticides, along with to advance research that may improve pest control strategies.

In the results of the systematic review, we found 2734 articles related to the selected keywords. Six of these articles directly address Drosophila suzukii and the use of bioinformatics tools in the search for alternatives in pest control. In the selected studies, we observed that two articles tend to focus on phylogenetic approaches, searching for gene sequences, amino acids, and constructing phylogenetic trees. The other three articles used molecular modeling and docking of receptors such as GABA and TRP with plant-derived and synthetic compounds to study intermolecular interactions. However, we identified gaps in these studies that could lead to further research in the biorational development of biopesticides using bioinformatics tools.