This topic is designed to provide a comprehensive platform for cutting-edge research on the molecular dynamics governing host–microbial pathogen interactions. By leveraging molecular dynamics (MD) simulations, molecular modeling, and advanced in silico analyses—such as machine learning, deep learning, and artificial intelligence—we seek contributions that offer novel insights into the complex biomolecular processes driving pathogenesis and host responses during infection.

We welcome studies that simulate, visualize, and predict the functional consequences of biomolecular interactions—including protein–protein, protein–nucleic acid, and protein–lipid contacts—in infectious contexts. This encompasses mechanistic investigations into cell signaling pathways, metabolic reprogramming, cytoskeletal reorganization, membrane–protein interactions, regulation of gene expression, stress responses, and enzymatic or immunological reactions, all resolved at the molecular scale. Research that integrates computational approaches to interpret, predict, or experimentally validate molecular determinants of host–pathogen interplay, microbial adaptation, and disease progression is strongly encouraged.

Special emphasis will be placed on studies exploring:

• Molecular dynamics simulations of interactions involving microbial and host proteins, nucleic acids, or secondary metabolites during infection
• The impact of microbial genetic mutations and functional adaptations on virulence and host defense mechanisms
• Inhibition or activation of signal transduction pathways in host–pathogen interactions
• Remodeling of cytoskeletal and mechano-signaling networks during infection
• Host and microbial stress response pathways, including heat shock, oxidative stress, and immune reactions
• Membrane–protein interactions, intracellular trafficking, and their roles in pathogenesis
• Enzyme kinetics, structural and functional crosstalk, and systems-level analyses
• Artificial intelligence and machine learning approaches for modeling host–pathogen dynamics and predicting infection outcomes

We invite submissions of original research articles, reviews, and methodological papers spanning from fundamental molecular mechanisms to translational applications. Studies may address pathogens affecting human, animal, or plant hosts, thereby extending the scope beyond medical mycology. By integrating perspectives from biochemistry, cell biology, biophysics, computational biology, bioinformatics, and systems medicine, this issue aims to foster interdisciplinary dialogue and catalyze innovative strategies for combating infectious diseases.

Please contact Dr. Monsicha Pongpom, Dr. Tanaporn Wangsanut, or Dr. Narin Lawan if you have any questions.

Keywords

• microorganisms
• pathogenesis
• molecular dynamics simulation
• molecular modeling
• mutation effect
• signaling pathway
• heat shock response
• oxidative response
• stress response pathway
• enzyme reaction analysis
• host response
• immunologic response
• AI
• machine learning
• deep learning