Aedes aegypti is the main transmitter of several arboviruses, mainly dengue. It occurs, recently, in more than 100 countries and majority of the world population lives in areas of mosquito incidence, marking its control relevant and necessary. Presently, the main form of vector control is the use of synthetic insecticides; however, its continuous application has led to inefficiency due to resistance development. Based on this fact, the insecticides from natural sources appear as a friendly alternative for man and the environment. This study provides an overview of the larvicidal compounds isolated from plant extracts while controlling A. aegypti, in the previous 6 years (2013-2018), and aims to impart more knowledge regarding the described metabolites and to encourage the search for new bioactive compounds. In addition, the proposals for mechanisms of action and structure-activity relationships that may justify the larvicidal potential are also discussed.
Introduction: This paper proposes DBsimilarity to organize structural databases into Similarity Networks to better understand the rich information available. Method: DBsimilarity was written in Jupyter Notebooks to be easy to follow and values readability. It converts SDF files into CSV files, adds chemoinformatics data, constructs a MZMine custom database file and a NMRfilter candidate list of compounds for rapid dereplication of MS and 2D NMR data, calculates similarities between compounds, and constructs CSV files to be converted to Similarity Networks using Cytoscape. Results: The Lotus database was used as source for Ginkgo biloba compounds and DBsimilarity was used to create Similarity Networks that includes NPClassifier classification to indicate biosynthesis pathways. Following, a database of validated antibiotics natural products was combined with the G. biloba database to indicate promising compounds. The presence of 11 compounds in both datasets points to a possible antibiotic property of G. biloba, and 122 other compounds similar to those known antibiotics is found. Next, DBsimilarity was used to filter the NPAtlas database (selecting only those with MIBIG reference) to identify potential antibacterial compounds using the ChEMBL database as reference. It was possible to promptly identify 5 compounds found in both databases, and 167 other worth investigating compounds similar to those known antibiotics. Conclusion: Chemical and biological properties are determined by molecular structures. DBsimilarity enables the creation of interactive Similarity Networks using Cytoscape. It is also in line with recent review that highlights significant sources of errors in compound identification: poor biological plausibility and unrealistic chromatographic behaviors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.