Neurotoxic mechanisms of the pesticide myclobutanil: integration of network toxicology, transcriptomics, and molecular simulation

Myclobutanil, a pesticide commonly employed in agricultural practices for fruits, vegetables, and crops, is capable of crossing the blood-brain barrier (BBB) and persisting in cerebrospinal fluid, posing significant risks to human health. Consequently, it is crucial to systematically explore the molecular toxicological mechanisms underlying its neurotoxic effects.This study employed a systems-level approach that integrated weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network construction, followed by molecular docking and molecular dynamics (MD) simulations for validation.A total of 75 key targets were identified using cheminformatics tools (SEA, SwissTargetPrediction, TargetNet) and disease databases (GeneCards, OMIM, DisGeNET). Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed that Myclobutanil exposure induces neurotoxicity through multiple signalling pathways, particularly the Pathways of neurodegeneration-multiple diseases and PI3K-Akt signalling pathway.Transcriptomic analysis and WGCNA identified RAF1 as a significantly correlated target with Myclobutanil exposure. Molecular docking and MD simulations further confirmed a strong binding affinity between RAF1 and Myclobutanil, suggesting that RAF1 plays a pivotal role in Myclobutanil exposure neurotoxicity.This prospective study yields predictive insight into the molecular events underlying Myclobutanil exposure neurotoxicity and highlights candidate therapeutic targets that remain to be validated <i>in vivo</i>. Myclobutanil, a pesticide commonly employed in agricultural practices for fruits, vegetables, and crops, is capable of crossing the blood-brain barrier (BBB) and persisting in cerebrospinal fluid, posing significant risks to human health. Consequently, it is crucial to systematically explore the molecular toxicological mechanisms underlying its neurotoxic effects. This study employed a systems-level approach that integrated weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network construction, followed by molecular docking and molecular dynamics (MD) simulations for validation. A total of 75 key targets were identified using cheminformatics tools (SEA, SwissTargetPrediction, TargetNet) and disease databases (GeneCards, OMIM, DisGeNET). Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis revealed that Myclobutanil exposure induces neurotoxicity through multiple signalling pathways, particularly the Pathways of neurodegeneration-multiple diseases and PI3K-Akt signalling pathway. Transcriptomic analysis and WGCNA identified RAF1 as a significantly correlated target with Myclobutanil exposure. Molecular docking and MD simulations further confirmed a strong binding affinity between RAF1 and Myclobutanil, suggesting that RAF1 plays a pivotal role in Myclobutanil exposure neurotoxicity. This prospective study yields predictive insight into the molecular events underlying Myclobutanil exposure neurotoxicity and highlights candidate therapeutic targets that remain to be validated <i>in vivo</i>.