Harnessing the Potential of Natural Products in Insecticide Discovery: A Cheminformatics Approach

Developing new insecticides is a vital necessity for modern agriculture. Problems such as toxicity, bioaccumulation, and application difficulties significantly impact the safety and usage of these compounds. Exploring new options with volatile molecules derived from natural resources offers the possibility of utilizing these compounds in large-scale agriculture. In this study, we utilized insecticide data, volatile compounds, and insecticide target-associated compounds (ITAC) to perform a cheminformatic comparison and identify similar molecules in natural products that exhibit volatility and insecticidal activity characteristics. Our findings showed convergence between volatility, insecticidal properties, and the natural origin of multiple compounds. Additionally, various scaffolds and substructures found in insecticidal compounds were identified in natural products with potential volatility. These shared compounds exhibited high normalized spatial score values, emphasizing their structural complexity. Results that, from an enhanced perspective, show the feasibility of using natural products for agriculture and their capacity to address multiple problems simultaneously.

Authors

Institutions

Publication Details

Journal
Journal of Agricultural and Food Chemistry
Published
2025-12-18
DOI
https://doi.org/10.1021/acs.jafc.5c03553
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Harnessing the Potential of Natural Products in Insecticide Discovery: A Cheminformatics Approach

César A. Sierra, Oliver Koch, Norberto Sánchez‐Cruz, Felipe Victoria-Muñoz et al.
Journal of Agricultural and Food Chemistry
Computational Drug Discovery Methods
article

Harnessing the Potential of Natural Products in Insecticide Discovery: A Cheminformatics Approach

César A. Sierra, Oliver Koch, Norberto Sánchez‐Cruz, Felipe Victoria-Muñoz, Alexander Espinosa García
article en

Abstract

Developing new insecticides is a vital necessity for modern agriculture. Problems such as toxicity, bioaccumulation, and application difficulties significantly impact the safety and usage of these compounds. Exploring new options with volatile molecules derived from natural resources offers the possibility of utilizing these compounds in large-scale agriculture. In this study, we utilized insecticide data, volatile compounds, and insecticide target-associated compounds (ITAC) to perform a cheminformatic comparison and identify similar molecules in natural products that exhibit volatility and insecticidal activity characteristics. Our findings showed convergence between volatility, insecticidal properties, and the natural origin of multiple compounds. Additionally, various scaffolds and substructures found in insecticidal compounds were identified in natural products with potential volatility. These shared compounds exhibited high normalized spatial score values, emphasizing their structural complexity. Results that, from an enhanced perspective, show the feasibility of using natural products for agriculture and their capacity to address multiple problems simultaneously.

Journal of Agricultural and Food ChemistryVol. 73(52)
University of Münster (DE), Universidad Nacional de Colombia (CO), Centre de Recherches sur les Macromolécules Végétales (FR), Universidad Marista de Mérida (MX), Laboratoire des Biomolécules (FR), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 60%
Computational Drug Discovery Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.