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

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Tarcisio Silva Melo, Bruno Silva Andrade
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引用次数: 0

Abstract

Context

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.

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.

Results

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.

Graphical abstract

Abstract Image

推进针对铃木果蝇的合理农药开发:生物信息学工具和应用--系统综述。
背景:铃木果蝇(Matsumura,1931 年)是一种广泛存在的农业害虫,对各种软皮水果寄主造成了严重危害。生物信息学在农业领域的革命性潜力来自于它能够提供有关害虫、真菌、抗药性、非目标物种的影响以及其他关键方面的广泛信息。这些丰富的信息使研究人员能够在面临这些挑战的不同农业领域开展项目和应用研究。在此背景下,生物信息学工具发挥了重要作用。害虫对农作物的负面影响造成了巨大的经济损失,这凸显了硅学方法的重要性:为此,我们以 "苏氏果蝇"、"生物农药"、"模拟计算 "和 "硅学 "为关键词,在科学数据库中进行了系统搜索。在应用相关性和出版日期过滤器后,我们对文章进行了整理,并优先考虑那些直接涉及与关键词和生物信息学工具的使用相匹配的文章。此外,我们还纳入了以生物农药的硅学检测(如分子对接)为重点的研究。我们的综述旨在介绍有关针对铃木果蝇的生物杀虫剂的最新文献集,其中强调了生物信息学方法。通过这项工作,我们努力为有关生物农药的开发和效率的新视角的文献做出贡献,同时推动可能改善害虫控制策略的研究:在系统综述的结果中,我们发现了 2734 篇与所选关键词相关的文章。其中有六篇文章直接涉及到了铃木果蝇以及生物信息学工具在寻找害虫控制替代品方面的应用。在所选研究中,我们注意到有两篇文章倾向于关注系统发生学方法,搜索基因序列、氨基酸并构建系统发生树。另外三篇文章利用分子建模和受体(如 GABA 和 TRP)与植物提取物和合成化合物的对接来研究分子间的相互作用。然而,我们发现了这些研究中的不足,这些不足可能会导致利用生物信息学工具进一步研究生物农药的生物开发。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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