Host-transcriptomics maps MPOX activity to six key genes and repurposed antivirals
Monkeypox, now more often called MPOX in clinical and public health discussions, is still without an approved therapy. That gap drives the appeal of host-based transcriptomics: instead of chasing the virus alone, investigators can look for the human pathways the infection disrupts and then search for medicines that may blunt those changes. In this study, three transcriptomic datasets were combined to identify a shared host response signature in patients with MPOX compared with control groups. The result was a set of 166 common host differentially expressed genes, divided into 75 upregulated and 91 downregulated genes, then narrowed through protein-protein interaction analysis to six host key genes: ALB, HSP90AA1, CDH1, PTPRRC, IGF1, and ABL1.
The biology behind this approach is straightforward. Viral infections do not act in isolation; they reshape the host cell’s transcriptional state, altering inflammatory signaling, adhesion, protein folding, growth pathways, and immune control. By identifying nodes that sit near the center of the interaction network, the analysis tries to separate background noise from molecules that may matter more directly to disease biology. In MPOX, that matters because the virus already has a recognized ability to interfere with interferon signaling and other antiviral defenses, allowing persistence while the host response unfolds in parallel.
Six host genes sit at the center of the MPOX response network
Each of the six genes carries a plausible mechanistic role in infection biology. HSP90AA1 is tied to protein folding and stress responses, which can become highly relevant when infected cells are under replication pressure. CDH1 is a cell-adhesion gene, and disruption of adhesion biology can affect tissue integrity and the way infected cells interact with their neighbors. PTPRC is closely linked to immune-cell signaling, making it a logical marker of host defense remodeling. IGF1 and ABL1 are both involved in signaling pathways that can influence cellular survival and response to stress. ALB, although better known in clinical chemistry than viral biology, emerged from the interaction analysis as part of the core network.
The study did not stop at network ranking. Functional enrichment analysis mapped these genes to biological processes, molecular functions, cellular components, and KEGG pathways, giving a broader picture of what MPOX may be doing at the cellular level. Regulatory analysis also brought in transcription factors and miRNAs, adding another layer of control over the response. In practical terms, this kind of map is less about a single magic target and more about understanding which cellular circuits are being pushed off balance during infection.
One clear signal in the paper is the shift away from a purely virus-centered model.
Docking and simulation favored five repurposable drug candidates
With the host genes identified, the next step was molecular docking to see which available drugs might bind favorably to the prioritized targets. Five molecules ranked highest: Tecovirimat, Beclabuvir, Maraviroc, Raltegravir, and Brincidofovir. These are not presented as proven MPOX treatments; rather, they are candidates that emerged from an in silico repurposing pipeline. The logic is appealing because repurposed drugs already have known pharmacology, which can shorten the path from hypothesis to testing if the laboratory data and later clinical studies line up.
Pharmacokinetic screening added another filter. ADME/T and drug-likeness evaluations suggested favorable properties for the selected compounds, an important step because a molecule that binds in silico still has to be absorbed, distributed, metabolized, and tolerated in the human body. That does not guarantee clinical usefulness, but it does reduce the chance of chasing compounds with weak drug behavior. In a field where there is no approved MPOX-specific therapy, even a computational shortlist can help direct experimental effort.
The simulation results sharpened the picture further. The top three complexes — ALB-Tecovirimat, CDH1-Maraviroc, and PPARG-Beclabuvir — underwent 100 ns molecular dynamics simulations, and the binding stability was supported by RMSD, RMSF, and MM-GBSA results. Stability over time matters because docking is only a snapshot; dynamics asks whether the interaction can survive motion, solvent effects, and structural flexibility. In other words, the model tried to move from a static pose to a more realistic biochemical environment.
What the findings can and cannot say about MPOX treatment
These results offer a structured way to think about MPOX pathogenesis and drug repurposing, but they remain computational. No clinical efficacy has been demonstrated in patients, and no wet-lab validation appears in the data presented here. The most defensible reading is that the study generates hypotheses about host pathways and surfaces a small set of repurposable antivirals worth testing in experimental systems.
That distinction matters because MPOX already sits in a clinically urgent space. The infection is a recognized public health threat, and the current shortage of approved drugs leaves clinicians and researchers dependent on vaccines, supportive care, and indirect antiviral strategies. Host-transcriptomics does not solve that problem on its own, but it can help define which human pathways are most disrupted and which existing agents deserve closer scrutiny. For a virus that can evade immune detection and hijack host machinery, the host-response map may be as important as the viral genome itself.
The study also carries a methodological lesson. Transcriptomic analyses are only as strong as the datasets they combine, the assumptions built into the network pipeline, and the biological plausibility of the final targets. The authors explicitly call for experimental validation in wet lab settings, and that next step will be essential before any of these candidates can be considered beyond a computational signal. Until then, the work stands as a mechanistic map rather than a treatment answer, with Tecovirimat, Beclabuvir, Maraviroc, Raltegravir, and Brincidofovir emerging as the most visible repurposing leads from the analysis.