A Computational Investigation on Immunogenicity of Uricase from Aspergillus Flavus and Candida Utilis

Abstract

Uricase is a therapeutic enzyme that has applications in adjuvant chemotherapy and the management of treatment-resistance hyperuricemia. It is a key element in gout treatment, a type of arthritis affecting humans due to increased serum uric acid levels. Two available formulations of uricase from Bacillus fastidious and Arthrobacter globiformis were characterized by their high immunogenicity, resulting in the drug's inactivation and hypersensitivity reactions in many patients. This research focuses on protein engineering to find a substitute to PEGylated enzymes with less immunogenicity as an intrinsic characteristic of the protein. We used in silico techniques to spot and modify epitope areas of uricase from Aspergillus flavus (Af) and Candida utilis (Cu), and to decrease the immunogenicity. Both Uricase B-cell epitopes were predicted using surface accessibility and hydrophilicity. Mutations were made to the hot-spot residues to diminish the epitope's antigenicity. Also, molecular docking was used to examine the effect of mutation on uricase activity and stability. Immunoinformatic analysis was done to clarify the structural aspects of the immunogenicity of uricase. For this purpose, the prognostication of immunogenic and allergenic epitopes in uricase structure was performed by using immunogenic peptides relative frequency. To the best of our knowledge, this is the first report of an in silico investigation aimed at decreasing the immunogenicity of uricase from Aspergillus flavus and Candida utilis. © 2023, Physical Chemistry Research. All Rights Reserved.