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Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011984","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T17:33:25Z","timestamp":1711560805000},"page":"e1011984","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma 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