From transcriptomics to structural modelling with AlphaFold: analysis of the central response to stress in bacteria using machine learning and structural bioinformatics

José Molina Mora presents an integrative study of the core stress-response mechanisms, or perturbome, of Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Transcriptomic data are analysed using machine learning, systems biology, functional enrichment and ortholog comparisons to prioritise stress-associated genes. Experimentally determined protein structures are combined with AlphaFold predictions where structural data are missing. Molecular docking and further computational analyses then identify preliminary compounds and conditions that might inhibit selected targets. These results are a proof of concept awaiting experimental validation. The talk connects gene-expression analysis with structural modelling for antimicrobial research and is aimed at researchers, graduate students and professionals in microbiology, bioinformatics and related biomedical fields.