Mos-Gen: A Generative Molecular Framework for Mosquito Insecticide Design

2026-06-01

AI Summary

Traditional mosquito insecticides urgently require novel alternatives due to widespread resistance. This work proposes Mos-Gen, a motif-aware de novo molecular generation framework specifically designed for mosquito insecticides, thereby addressing the critical gap in AI-driven scaffold design for this domain. The approach integrates Uni-Mol pretrained molecular representations with a variational autoencoder and enables targeted generation of allicin derivatives containing disulfide bonds. Experimental validation involved the synthesis of 14 generated molecules, achieving a 78% hit rate among those predicted as active, while all compounds predicted as inactive showed no activity, demonstrating the framework’s high predictive accuracy and practical utility.

Abstract

Mosquito-borne infectious diseases cause more than 700000 deaths worldwide each year. The long-term use of conventional chemical insecticides has induced serious resistance problems, creating an urgent need to develop novel, highly effective, and ecologically sustainable alternatives. While existing artificial intelligence approaches in this domain have focused primarily on activity prediction and classification, they leave a critical gap in the de~novo generation of novel molecular scaffolds. In this study, we propose Mos-Gen, a motif-aware generative collaborative framework that couples the pretrained molecular representation model Uni-Mol with a variational autoencoder (VAE), specifically tailored for the design of disulfide-containing allicin derivatives as mosquito insecticides. Among the generated candidates, fourteen compounds -- comprising nine predicted positives and five predicted negatives -- were selected for chemical synthesis and experimental validation. The hit rate among the predicted positives reached 78%, whereas none of the predicted negatives exhibited mosquitocidal activity. These experimental results fully validated the high-precision screening capability of the Mos-Gen framework.

Problem

• mosquito insecticide
• de novo molecular generation
• insecticide resistance
• molecular scaffold
• allicin derivatives

Innovation

• molecular generation
• motif-aware
• variational autoencoder
• Uni-Mol
• de novo design