AI-driven fungicide design: From target identification to field application

Area of Science:

• Agricultural Science
• Computational Biology
• Plant Pathology

Background:

• Plant pathogenic fungi cause significant agricultural yield losses and food contamination.
• Conventional fungicide development is costly, time-consuming, and challenged by evolving fungal resistance.
• Existing artificial intelligence (AI) applications in plant pathology lack integration of agricultural-specific constraints.

Purpose of the Study:

• To present the AI-driven fungicide design (AIFD) platform, a framework for accelerating fungicide discovery.
• To synthesize AI methodologies adapted for agrochemical requirements, focusing on agricultural constraints.
• To identify challenges and future directions for AI in fungicide development for sustainable agriculture.

Main Methods:

• Development of a comprehensive AIFD platform with four components: data ecosystem, technical architecture, development workflow, and resistance prediction workflow.
• Synthesis of AI advancements across the fungicide pipeline: target identification, virtual screening, molecular optimization, and field validation.
• Adaptation of AI methodologies for agrochemical needs, prioritizing field stability, ecological safety, and resistance management.

Main Results:

• The AIFD platform integrates agricultural-specific constraints into the AI-driven fungicide design process.
• Key AI advancements are highlighted for various stages of fungicide development, tailored for agrochemical applications.
• Persistent challenges include data scarcity, model adaptability, interpretability, and accessibility for researchers.

Conclusions:

• AI-driven fungicide design platforms can accelerate the discovery of effective, environmentally benign fungicides.
• Addressing challenges in data, model adaptability, and interpretability is crucial for regulatory acceptance and stakeholder trust.
• Future AIFD platforms should integrate real-time field data and employ explainable AI for bridging the lab-to-field gap and ensuring sustainable crop protection.