Despite the availability of Pap tests and HPV vaccines, Cervical Cancer continues to be a significant factor contributing to women's deaths. It poses severe consequences to women's health. The disease's severity lies in its potential to progress silently in its early stages, mainly detected in its advanced stage, and clinical treatment is challenging due to drug resistance. This study aims to identify multitargeted lead molecules based on the interactome of Cervical Cancer-related crucial genes, which can help develop drug-resistant therapies. We have considered 9 crucial Cervical Cancer genes, namely BUBR1, CCNB1, FEN1, MAD2, MCM10, MCM6, ITGB8, POLE, and TPX2, to perform gene network analysis and Gene Ontology enrichment studies to identify the potential hub genes and their role. Further, we performed multitarget screening using multisampling algorithms HTVS, SP, and XP to screen the protein products of the 9 genes for their binding affinity for the FDA-approved drugs library. The binding affinities of the compounds were evaluated using MM\GBSA that identified multitargeted potential inhibitor as a Levophed for Cervical Cancer, and the docking results showed a range of MM/GBSA scores, varying from -8.35 to -5.38 kcal/mol for docking, and -43.41 to -19.37 kcal/mol for MM/GBSA scoring. The protein residues that interact the most with Levophed are ALA, THR, ILE, ASN, GLY, ASP, LEU, LYS, VAL, GLN, PRO, CYS, GLU, and TYR. The pharmacokinetic properties and WaterMap computations also support the idea that the compound can potentially become a drug candidate. Furthermore, all 9 complexes were simulated for 100ns, resulting in cumulative deviation and fluctuation of <2 Å, with many intermolecular interactions and binding free energy computations supporting the studies. The study shows that Levophed could treat Cervical Cancer without encountering drug resistance- however, experimental studies are needed to confirm the accuracy.