Investigating the mechanisms of antibody binding to alpha-synuclein for the treatment of Parkinson's Disease

Abstract

Parkinsons Disease (PD) is an idiopathic neurodegenerative disorder with the second-highest prevalence rate behind Alzheimers Disease. The pathophysiological hallmarks of PD are both degeneration of dopaminergic neurons in the substantia nigra pars compacta and the inclusion of misfolded alpha-synuclein (-syn) aggregates known as Lewy bodies. Despite decades of research for potential PD treatments, none have been developed, and developing new therapeutic agents is a time-consuming and expensive process. Computational methods can be used to investigate the properties of drug candidates currently undergoing clinical trials to determine their theoretical efficiency at targeting -syn. Monoclonal antibodies (mAbs) are biological drugs with high specificity, and Prasinezumab (PRX002) is a mAb currently in Phase II, which targets the C-terminus (AA 118-126) of -syn. We utilized BioLuminate and PyMol for structure prediction and preparation of the fragment antigen-binding (Fab) region of PRX002 and 34 different conformations of -syn. Protein-protein docking simulations were performed using PIPER, and 3 of the docking poses were selected based on the best fit. Molecular dynamics simulations were conducted on the docked protein structures for 1000 ns, and hydrogen bonds, electrostatic, and hydrophobic interactions were analyzed using MDAnalysis to determine which residues were interacting and how often. Hydrogen bonds were shown to form frequently between the HCDR2 region of PRX002 and -syn. Free energy was calculated to determine binding affinity. The predicted binding affinity shows a strong antibody-antigen attraction between PRX002 and -syn. RMSD was calculated to determine the conformational change of these regions throughout the simulation. The mAbs developability was determined using computational screening methods. Our results demonstrate the efficiency and developability of this therapeutic agent.