AI-Driven Insights into Host-Pathogen Interactions and Antimicrobial Drug Discovery in a One Health Framework

The rapid emergence of antimicrobial resistance (AMR) and zoonotic pathogens underscores the urgent need for innovative, interdisciplinary strategies to understand and combat infectious diseases. The World Health Organization has identified AMR as a major and growing global health threat, highlighting the need for continued advances in research and development.This Research Topic aims to highlight cutting-edge research at the intersection of artificial intelligence (AI), systems biology, and translational medicine in the context of host-pathogen interactions and antimicrobial drug discovery within a One Health framework. By leveraging AI-driven approaches such as machine learning, deep learning, and network-based modeling, researchers can decode complex host-pathogen dynamics, predict virulence factors, and identify novel therapeutic targets with increasing precision.Within the One Health paradigm, which integrates human, animal, and environmental health, this Research Topic welcomes contributions exploring how AI can bridge data across diverse biological systems to improve our understanding of pathogen evolution, transmission, and resistance mechanisms. We particularly encourage submissions focusing on computational drug discovery for AMR, repurposing of antimicrobial agents, predictive modeling of host-pathogen interactions and immune responses, and the integration of multi-omics approaches.We welcome original research articles, reviews, and other article types that present recent advances and successful applications of AI-driven approaches to the host-pathogen interactome and antimicrobial drug discovery. By bringing together contributions across these areas, this Research Topic seeks to provide new insights that may accelerate the discovery of next-generation antimicrobials and inform global strategies to mitigate infectious disease threats.Topics of interest include, but are not limited to:- combating antimicrobial resistance through drug repurposing- identification of novel antimicrobial agents using AI-driven methods- uncovering new antimicrobial agents through structure-based drug discovery- screening potential lead molecules from natural products- AI-driven approaches to understanding the mutational effects of AMR- predictive modeling of host–pathogen interactions using AI and machine learning approaches- host-pathogen systems biology and network analysis- AI-driven approaches for zoonotic pathogens from a One Health perspectiveIf you are interested in submitting or have any questions, please contact the journal email: bacteriology@frontiersin.org. Topic editors: Nagendran Tharmalingam, Kulandaisamy Arulsamy Source: https://www.frontiersin.org/research-topics/80485/ai-driven-insights-into-host-pathogen-interactions-and-antimicrobial-drug-discovery-in-a-one-health-framework