Abstract
Dengue is a neglected disease, present mainly in tropical countries, with more than 5.2 million cases reported in 2019. Vector control remains the most effective protective measure against dengue and other arboviruses. Synthetic insecticides based on organophosphates, pyrethroids, carbamates, neonicotinoids and oxadiazines are unattractive due to their high degree of toxicity to humans, animals and the environment. Conversely, natural-product-based larvicides/insecticides, such as essential oils, present high efficiency, low environmental toxicity and can be easily scaled up for industrial processes. However, essential oils are highly complex and require modern analytical and computational approaches to streamline the identification of bioactive substances. This study combined the GC-MS spectral similarity network approach with larvicidal assays as a new strategy for the discovery of potential bioactive substances in complex biological samples, enabling the systematic and simultaneous annotation of substances in 20 essential oils through LC50 larvicidal assays. This strategy allowed rapid intuitive discovery of distribution patterns between families and metabolic classes in clusters, and the prediction of larvicidal properties of acyclic monoterpene derivatives, including citral, neral, citronellal and citronellol, and their acetate forms (LC50 < 50 µg/mL).
Highlights
Publisher’s Note: MDPI stays neutralDengue is a viral infection transmitted mainly by the female Aedes aegypti mosquito.This disease mainly affects tropical regions, depending on the rain precipitation rate, temperature, humidity and urbanization process [1–7]
We propose a strategy combining the spectral similarity networking approach with larvicidal activity tests against Ae. aegypti to approachoils withwith larvicidal activity tests against Ae
Larvicide/insecticide based on natural products (NP)traditional are scarce apin the scarce in the industry, revealingproducts some difficulties associated with applying industry, some difficulties associated with applying traditional approaches in proachesrevealing in NP [43,47,48]
Summary
Dengue is a viral infection transmitted mainly by the female Aedes aegypti mosquito. This disease mainly affects tropical regions, depending on the rain precipitation rate, temperature, humidity and urbanization process [1–7]. Most botanical insecticides are highly susceptible to photodegradation (e.g., pyrethrins), abiotic oxidation (azadiractins) or volatilization loss (essential oil terpenoids) when applied outside a controlled environment (e.g., indoors), requiring their reapplication when used on monocultures. Despite this limitation, certain botanical insecticides have proven records dating back 2–3 decades, confirming their effectiveness in the field [14,15]. The increased sharing of experimental MS/MS data and the growing number of spectral databases, such as NIST, METLIN, MassBank, MASST, NuBBEDB , Sumner/Bruker and ReSpect, have promoted the development of several bioinformatics approaches that help in the interpretation of large One of these approaches is the concept of spectral similarity networking (so-called molecular networks—MN) which is based on the organization and visualization of MS/MS data via spectral similarity (homologous fragments) [24,34–39]. Strategy for for the the discovery discovery of of potential potential bioactive Figure bioactive classes: classes: spectral spectralsimilarity similaritynetworking networking (GC-MS data) combined with biological assays (larvicidal assay—LC50 values)
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