Integrative single-cell transcriptomic analysis reveals immunomodulatory hub genes and candidate compounds for...

Despite significant advances in treatment and prevention, HIV remains a major global health challenge affecting millions worldwide. In this study, we developed a pipeline combining single-cell RNA sequencing (scRNA-seq) analysis with molecular modeling to identify potential biomarkers and therapeutic targets in HIV infection. Analysis of scRNA-seq data from individuals with HIV revealed 69 differentially expressed genes. Protein-protein interaction network analysis identified five hub genes (STAT1, ISG15, MX1, BCL2, and TNFSF10). Regulatory network analysis identified transcription factors and microRNAs governing the expression of these hub genes. Molecular docking simulations identified Dolutegravir and Luteolin as compounds capable of binding to STAT1, ISG15, and MX1, with favorable ADMET profiles. These compounds may potentially modulate chronic inflammation associated with persistent interferon signaling in HIV infection. Our study demonstrates an integrative approach to scRNA-seq data analysis, transforming transcriptomic data into actionable insights by identifying specific gene targets and potential candidate compounds that could inform the design of targeted experimental studies.