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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Implications of available design space for identification of non-immunogenic protein therapeutics
1Department of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA. lee.1996@osu.edu
Immunogenicity/antibody responses are major issues for parenteral proteins and nanotherapeutics (nanovectors, diagnostics, theranostics, etc.), and robust antibody responses require T-helper epitopes. T-helper epitopes consist of specific amino acids at specific positions (anchor positions) in immunogens which contact the major histocompatibility complex (MHC), provide most of the energy for MHC binding and constitute the binding motif for the corresponding MHC alleles. We developed an algorithm that considers motifs to design vaccines lacking unwanted T-cell epitopes, and found numbers of such vaccines can be astronomical (Lee et al. 2009). The algorithm can be used to design reduced immunogenicity proteins, and numbers of predicted proteins are also immense. Reducing T-helper epitope content reduces protein immunogenicity, but the depth of mutagensis needed to eliminate immunogenicity is commonly assumed to be too great for retention of protein bioactivity. However, very deep, but successful substitution, insertion and deletion mutagenesis have been reported. These reports and design space the algorithm reveals suggest development of non-immunogenic therapeutics might be more feasible than commonly assumed.
Immunogenicity/antibody responses are major issues for parenteral proteins and nanotherapeutics (nanovectors, diagnostics, theranostics, etc.), and robust antibody responses require T-helper epitopes. T-helper epitopes consist of specific amino acids at specific positions (anchor positions) in immunogens which contact the major histocompatibility complex (MHC), provide most of the energy for MHC binding and constitute the binding motif for the corresponding MHC alleles. We developed an algorithm that considers motifs to design vaccines lacking unwanted T-cell epitopes, and found numbers of such vaccines can be astronomical (Lee et al. 2009). The algorithm can be used to design reduced immunogenicity proteins, and numbers of predicted proteins are also immense. Reducing T-helper epitope content reduces protein immunogenicity, but the depth of mutagensis needed to eliminate immunogenicity is commonly assumed to be too great for retention of protein bioactivity. However, very deep, but successful substitution, insertion and deletion mutagenesis have been reported. These reports and design space the algorithm reveals suggest development of non-immunogenic therapeutics might be more feasible than commonly assumed.
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