Abstract

Allergic and autoimmune diseases are forms of immune hypersensitivity that increasingly cause chronic ill health. Most current therapies treat symptoms rather than addressing underlying immunological mechanisms. The ability to modify antigen-specific pathogenic responses by therapeutic vaccination offers the prospect of targeted therapy resulting in long-term clinical improvement without nonspecific immune suppression. Examples of specific immune modulation can be found in nature and in established forms of immune desensitization. Allergic and autoimmune diseases are forms of immune hypersensitivity that increasingly cause chronic ill health. Most current therapies treat symptoms rather than addressing underlying immunological mechanisms. The ability to modify antigen-specific pathogenic responses by therapeutic vaccination offers the prospect of targeted therapy resulting in long-term clinical improvement without nonspecific immune suppression. Examples of specific immune modulation can be found in nature and in established forms of immune desensitization. Targeting pathogenic T cells using vaccines consisting of synthetic peptides representing T cell epitopes is one such strategy that is currently being evaluated with encouraging results. Future challenges in the development of therapeutic vaccines include selection of appropriate antigens and peptides, optimization of peptide dose and route of administration and identifying strategies to induce bystander suppression. Structure-based computational methods have been widely used in exploring protein-ligand interactions, including predicting the binding ligands of a given peptide based on their structural complementarity. Compared to other peptide and ligand representations, the advantages of a surface representation include reduced sensitivity to subtle changes in the pocket and ligand conformation and fast search speed. Peptidomimetics, deriving from structure-based, combinatorial or protein dissection approaches, can play a key role as hit compounds. We believe that using a surface patch approach to better understand protein-ligand interactions has the potential to significantly enhance the design of new ligands for a wide array of drug-targets. Here, in Biogenea we have for the first time generated a surface representation based Peptidomimetic vaccine-like annotated pharmacostructure for allergic and autoimmune diseases using PL-PatchSurfer in a BiogenetoligandorolTM clustering algorithmic enviroment.