Thermodynamics-guided Design of Multivalent Ligands for the Myeloid C-type Lectin Receptor DC-SIGN

点击翻译按钮获取中文摘要

The myeloid C-type lectin receptor DC-SIGN promotes the infection of certain types of immune cells and dissemination of virus particles by mediating interactions with viral envelope glycoproteins. The receptor has been implicated in the pathology of multiple infections with viral pathogens such as SARS-CoV-2, Ebola, HIV, Zika, and Dengue. Carbohydrate-based compounds that are able to inhibit the interactions of viruses with DC-SIGN represent a promising approach towards the development of broadly acting antiviral therapeutics. By addressing molecular targets, which are ultimately conserved in the host genome, these molecules could contribute to the early containment of future viral infections with pandemic potential. This project aims to develop oligovalent ligands for DC-SIGN, which are able to bind multiple binding sites of the homotetrameric receptor simultaneously. A particular challenge in the in the design of such molecules is the selection of appropriate chemical linkers that connect the central scaffold of the oligovalent ligand with the glycomimetic binding epitope. The use of flexible linkers is typically associated with a significant reduction in binding affinity due to the loss of conformational degrees of freedom upon binding. Thus, the optimization of the proposed compounds will encompass the synthesis of tailor-made rigid linkers for the given system. A thermodynamic characterization of the respective interactions with DC-SIGN will then yield valuable information about the driving forces underlying oligovalent recognition. Further biological experiments in cellular models of viral infection will yield information about the potency of the developed compounds. The oligovalent glycomimetics presented here combine the advantages of monovalent carbohydrate analogs and complex polyvalent systems. Besides a high degree of selectivity and improved binding enthalpy, a targeted presentation of binding epitopes will harness multivalent affinity enhancement, while simultaneously minimizing entropic penalties.