Recognition Mechanisms between a Nanobody and Disordered Epitopes of the Human Prion Protein: An Integrative Molecular Dynamics Study

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Abstract

Immunotherapy using antibodies to target the aggregation of flexible proteins holds promise for therapeutic interventions in neurodegenerative diseases caused by protein misfolding. Prions or PrPSc, the causal agents of transmissible spongiform encephalopathies (TSE), represent a model target for immunotherapies as TSE are prototypical protein misfolding diseases. The X-ray crystal structure of the wild-type (WT) human prion protein (HuPrP) bound to a camelid antibody fragment, denoted as Nanobody 484 (Nb484), has been previously solved. Nb484 was found to inhibit prion aggregation in vitro through a unique mechanism of structural stabilization of two disordered epitopes, that is, the palindromic motif (residues 113-120) and the β2−α2 loop region (residues 164-185). The study of the structural basis for antibody recognition of flexible proteins requires appropriate sampling techniques for the identification of conformational states occurring in disordered epitopes. To elucidate the Nb484-HuPrP recognition mechanisms, here we applied molecular dynamics (MD) simulations complemented with available NMR and X-ray crystallography data collected on the WT HuPrP to describe the conformational spaces occurring on HuPrP prior to Nb484 binding. We observe the experimentally determined binding competent conformations within the ensembles of pre-existing conformational states in solution before binding. We also described the Nb484 recognition mechanisms in two HuPrP carrying a polymorphism (E219K) and a TSE-causing mutation (V210I). Our hybrid approaches allow the identification of dynamic conformational landscapes existing on HuPrP and highly characterized by molecular disorder to identify physiologically relevant and druggable transitions.

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Mollica, L., & Giachin, G. (2023). Recognition Mechanisms between a Nanobody and Disordered Epitopes of the Human Prion Protein: An Integrative Molecular Dynamics Study. Journal of Chemical Information and Modeling, 63(2), 531–545. https://doi.org/10.1021/acs.jcim.2c01062

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