In silico construction and evaluation of anti-EGFR ScFv and IFN-β fusion protein as a novel immunocytokine for the treatment of HER1 positive breast cancer

Abstract

Abstract Context Human epidermal growth factor receptor 1 (HER1) positive breast cancer is characterized by overexpression of the HER1 receptor protein on cancer cells leading to aggressive disease and treatment resistance. Computational design can efficiently create immunocytokine that specifically target cancer cell antigens and modulate the immune response, making them a promising treatment for HER1-positive breast cancer. Methods The current work involves computational tools to design a novel immunocytokine, including the anti-epidermal growth factor single-chain variable fragment (ScFv) against HER1 receptor with a connection to the functional part of a cytokine INF-β. The amino acid sequences of ScFv region of antibody and IFN-β were retrieved from gene bank (accession no. AFF61391.1) and (ABS89222.1) respectively, and fused together to form a chimeric protein, called ScFv-IFN-β fusion protein. Physicochemical properties and solubility were analyzed using ProtParam and SOLpro, respectively. The ScFv-IFN-β fusion protein was modeled in 3D using alpha-fold and refined with GalaxyRefine and assessed using PROCHECK and RAMPAGE. Allergenicity and mRNA stability were predicted using the AlgPred and RNAfold servers, respectively. Docking and molecular dynamic simulations were performed using HDOCK and iMOD servers, respectively. Our computational analysis predicted that the ScFv-IFN-β fusion protein is anticipated to exhibit solubility, possess a sturdy 3D structure, maintain stable mRNA structure, and effectively bind to both HER1 and IFN receptors, thus making it a suitable candidate for breast cancer treatment. The current findings appear encouraging and hold promise for future experimental investigations.