Hepatocellular carcinoma (HCC) is a deadly primary tumour that begins in hepatocytes. Tumour cell proliferation and progression is influenced by cellular components of the liver and their microenvironment. Pharmacodynamic (PD) biomarkers are biomolecules that demonstrate the effect of a therapeutic intervention on the affected organ and its microenvironment. PD biomarkers are used to study drug target interactions and their biological responses. High-throughput technologies and bioinformatics tools are critical for interpreting proteomics data and exploring new biological insights into cellular processes, disease pathogenesis, and biomarker discovery. We have developed an animal model of HCC using DEN with 2AAF as a carcinogen and treated it with multiple doses of sorafenib-silibinin combinational tablets. With proteomic studies, we have screened differently expressed protein signatures as pharmacodynamic biomarkers. The PPI network was created on the STRING platform and visualised on Cytoscape software. The MCODE plug-in was implied to identify the modules with the highest significant score. Later, the CytoHubba plug-in was used to filter the top ten hub genes in each module. Finally Drug-gene interaction was done using hub gene on the STITCH platform for molecular analysis of combinational treatments. We have identified a total of 11 differentially expressed proteins with MALDI-TOF-MS. Bioinformatics analysis of these biological factors is used to identify genes that are helpful in treatment. The PPI network complex resulted in 141 nodes with 1520 edges. The top ten hub gene list revealed the significance of three query proteins (HRas, RRas, and FOS) in the protein network, which was later validated with overall survival analysis using the GEPIA tool. Finally, drug–gene interaction predicted that combinational treatment has a significant effect at the molecular level and, out of 11 differentially expressed proteins, 3 could be potential pharmacodynamic biomarker. Based on computational and proteomic analysis, we have screened the expression and therapeutic value of potential pharmacodynamic biomarkers (HRas, RRas, and FOS) with sorafenib-silibinin formulation treatment in the HCC model.