Researchers have been extensively exploring unique avenues to identify novel chemotherapeutics, crucial for the advance- ment of oncology research. The current study delves into the unexplored realm of tRNA-Encoded Peptides (tREPs), which have recently emerged as a potential source of anticancer peptides (ACPs). By leveraging computational methods and verified data sources, this study utilizes in silico approaches to explore the tRNA-peptide space for identification of po- tential anticancer peptides. 2,284 peptides were screened using the ACPred tool and 224 potential anticancer peptides were identified based on physicochemical properties, which were then further filtered for ADMET properties, molecular docking and molecular dynamics studies (150 ns), followed by estimation of binding free energy, with cancer target pro- teins AF9 (PDB-ID:2N4Q), SPOP- Substrate (PDB-ID:3IVV) and Myosin-IXb (PDB-ID:5C5S). Two peptides, (Pep1: DWIAWRHH- NDIVSWLTCGPRFKSWS) and (Pep2 :GFIAWWSRHLELAQTR- FKSWWS), were identified as potential anticancer agents. Abbreviations: tREPs, tRNA-Encoded Peptides; tREACP, tRNA-Encoded Anticancer Peptides. Peptide1 exhibited a favorable binding energy with a dock- ing score of -105.1+/-1.0 and an RMSD value of 0.2 nm, in- dicating strong stability, and a strong binding free energy of -65.49 kcal/mol when interacting with the target AF9. Pep- tide 2 displayed a good binding energy with docking score of -123.0+/-12.4, an RMSD of 0.3 nm, and binding free en- ergies of -53.15 kcal/mol when binding to the SPOP- Sub- strate Complex. Therefore, this study suggests that Peptides 1 and 2, have the potential to function as anticancer tREPs and could serve as promising therapeutic candidates against the AF9 and SPOP Substrate cancer targets.