Design and in Silico Construction of New Efficient Antibodies Against Gastric Tumor-associated Antigens Towards Introducing Combined Strategy for Vaccine Tumor Therapy

Abstract

Introduction: Gastric cancer, as the second reason of cancer mortality around the world, is defined as one of the serious health problems and a wide range of current research is focused to overcome the challenges relevant to its successful therapy. Employing recent approaches in the field of vaccine tumor therapy and immunotherapic strategies such as utilization of monoclonal antibodies can play significant roles in achieving efficient therapeutic means to combat the disease. Methods and Results: In this study, computational methods including three-dimensional modeling, based on sequence combinational pattern identification together with docking procedures have been employed for design and in silico construction of prolific and effective antibody structures against HER-2 and MAGE-3 antigens. These methods led to introduction of novel and efficient anti-HER2 and anti-MAGE3 antibodies. For instance, combinational pattern of bH1 antibody (light chain) and IGG1-KAPPA 4D5 antibody (heavy chain) which obtained an exceptional score of 844.83 KJ/mol as the new candidate for cancer vaccine therapy, whereas Herceptin scored 453.4 KJ/mol. In addition, the suggested pattern for designing antibody against MAGE-3 with combination of bH1 antibody (heavy chain) and HLA-A 0201 (light chain) achieved acceptable score of 640.8 KJ/mol. Conclusion: It is envisaged that the results obtained from the current research could be utilized to develop efficient combined strategies for vaccine therapy of gastric cancer.

Keywords

• gastric cancer
• vaccine therapy
• antibody
• her-2
• mage-3
• in silico
• docking