Otimização computacional de um conjunto de fragmentos de anticorpos específicos para terapia da infecção pelo vírus da Hepatite B

Abstract

Currently, hepatitis B virus infection is one of the major health problems worldwide, diagnosed by the detection of hepatitis B surface antigen. Patients with chronic forms of the disease may require a liver transplant, which is followed by treatment with immunosuppressants given in combination with monoclonal antibodies. Single chain variable fragments (scFv) have become antibody products suitable for this type of treatment. The aim of this study is to continue the humanization process of two murine monoclonal antibodies clones 19DD1AE3 and 19CC6CG2, provided by the Monoclonal Antibody Technology Laboratory of the Oswaldo Cruz Foundation. From these, six scFvs were generated, and it was found, in preliminary rigid docking results, data indicating the coupling of the scFv fragment with intermediate specificity, pointing to structural evidence such as hydrogen bonds, salt bridges and electrostatic complementarity that could be modified to achieve clones with increased specificity and affinity. In order to optimize such parameters, it was necessary to first identify the hot-spots residues of the interaction, which was accompshied using seven webservers, that use several different prediction methodologies. For the computational mutagenesis step, two programs were used, which performed an energy analysis of the differences in binding energy caused by the mutations. Physicochemical analyzes of the antigen residues that made contact with the scFvs were also performed, and the stability of the monomers upon mutations was analyzed. As results and conclusion, the residues that contributed the most to the binding energy in the formation of the complexes were identified; in addition, it was also possible to identify the best targets within the interface of each antibody fragment to perform computational mutagenesis, a step that was guided by energetic and physicochemical parameters; finally, the stabilizing or non-stabilizing character of the suggested mutations was analyzed, and optimized sequences were generated for the analyzed models. However, the complexes were analyzed in static models, and it’s still necessary to perform future steps of molecular dynamics, in order to ensure that they remain stable when submitted to physiological conditions. In addition, it is already possible to envisage the use of sequences in expression steps using biological models.