Presently, many studies have focused on exploring in silico approaches in the identification and development of alternative therapy for the treatment and management of cancer. Solute carrier family-2-member-4-gene (Slc2a4) which encodes glucose transporter 4 protein (GLUT4), has been identified as a promising therapeutic target for cancer. Though Slc2a4 is known to play a major regulatory role in the pathophysiology of type 2 diabetes, emerging evidence suggests that successful pharmacological inhibition of this protein may lead to the development of a novel drug candidate for the treatment of cancer. In this study, Slc2a4 protein sequence was retrieved and analysed using in silico approaches, and we identified seven putative antimicrobial peptides (AMPs; RAB1-RAB7) as anti-cancer. The structures of the protein and AMPs were modelled using I-TASSER server, and the overall quality of the Slc2a4 model was validated using PROCHECK. Subsequently, the probable motifs and active site of the protein were forecasted. Also, the molecular interaction between the AMPs and Slc2a4 was ascertained using PatchDock. The result revealed that, all the AMPs are good Slc2a4 inhibitors with RAB1 having the highest binding affinity of 12,392 and binding energy of -39.13 kcal/mol. Hence, this study reveals that all the generated AMPs can serve as therapeutic drug in treating cancer by inhibiting Slc2a4 which is responsible for the production of energy for cancer cells during angiogenesis. This is the first report on AMPs as inhibitors of Slc2a4 for the treatment of cancer.
Keywords: Slc2a4; antimicrobial peptides; cancer; docking; homology modelling.