Genomics and Bioinformatics Tools in Host-Pathogen Interactions

Dear Colleagues,

As one of the most significant public health challenges of our era, which include the SARS-CoV-2 pandemic and antibiotic resistance, host–pathogen interactions have garnered unprecedented attention. The study of host–pathogen interactions is crucial in understanding infection dynamics and developing therapeutic strategies. This includes the molecular and cellular dialogues occurring during infection, which involve complex signaling pathways and responses from both the host and pathogen. Computational resources and methodologies increasingly contribute to shaping our understanding of these intricate host–pathogen relationships, as well as deciphering the genomic and proteomic landscape of pathogens and their interactions with their hosts. This informs therapeutic interventions, advancing our broader comprehension of infectious diseases. Key areas of focus include the identification of the pathogen and host proteins involved, structural analyses to unveil the mechanisms of interaction and the role and pathogenicity of new variants, and the study of host immune responses. Next-generation sequencing and proteomic analyses elucidate the genomic and proteomic landscapes of pathogens and their hosts, and functional genomics shed light on the changes in gene expression, while immunoinformatics aids in predicting potential epitopes and vaccine candidates. Pathway and network analyses unravel the complex signaling pathways underlying these interactions, while machine learning applications model novel interactions.

This Special Issue aims to gather up-to-date computational studies of the interactions between pathogens and their hosts and examples of successful applications of bioinformatics tools in studying specific host–pathogen interactions, creating a comprehensive overview of the bioinformatics tools and resources available for studying host–pathogen interactions. It will cover the following topics and approaches:

• Resources and databases for host–pathogen interaction studies;
• Genomic and proteomic approaches for studying pathogen genomes and identifying the host and pathogen proteins involved in interactions;
• Structural bioinformatics for the prediction and analysis of protein structures related to host–pathogen interactions;
• How pathogen variants affect their interactions with the host;
• Gene expression analysis in host cells during infection;
• Pathway and network analysis of host–pathogen molecular interactions;
• Immunoinformatics for the prediction of antigenic epitopes;
• Antibiotic resistance;
• Vaccine design using computational approaches;
• Evolutionary analyses applied to the phylogenesis of pathogens and/or host–pathogen interactions. The study of the molecular evolution of virulence factors;
• Machine learning-based predictive modeling for identifying novel host–pathogen interactions, as well as classification and clustering approaches;
• Integration of multi-omics data: combining genomics, transcriptomics, and proteomics data to elucidate host–pathogen relationships;
• Systems biology approaches to the study of host–pathogen interactions.

Dr. Allegra Via
Prof. Dr. Stefano Pascarella
Dr. Rino Ragno
Guest Editors

Manuscript Submission Information

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• host–pathogen interactions
• bioinformatics
• genomics
• proteomics
• structural bioinformatics
• functional genomics
• immunoinformatics
• next-generation sequencing
• pathway analysis
• machine learning applications