Optimizing Epitope Conformational Ensembles Using α-Synuclein Cyclic Peptide “Glycindel” Scaffolds: A Customized Immunogen Method for Generating Oligomer-Selective Antibodies for Parkinson’s Disease

Abstract

Effectively presenting epitopes on immunogens, in order to raise conformationally selective antibodies through active immunization, is a central problem in treating protein misfolding diseases, particularly neurodegenerative diseases such as Alzheimer’s disease or Parkinson’s disease. We seek to selectively target conformations enriched in toxic, oligomeric propagating species while sparing the healthy forms of the protein that are often more abundant. To this end, we computationally modeled scaffolded epitopes in cyclic peptides by inserting/deleting a variable number of flanking glycines (“glycindels”) to best mimic a misfolding-specific conformation of an epitope of α-synuclein enriched in the oligomer ensemble, as characterized by a region most readily disordered and solvent-exposed in a stressed, partially denatured protofibril. We screen and rank the cyclic peptide scaffolds of α-synuclein in silico based on their ensemble overlap properties with the fibril, oligomer-model and isolated monomer ensembles. We present experimental data of seeded aggregation that support nucleation rates consistent with computationally predicted cyclic peptide conformational similarity. We also introduce a method for screening against structured off-pathway targets in the human proteome by selecting scaffolds with minimal conformational similarity between their epitope and the same solvent-exposed primary sequence in structured human proteins. Different cyclic peptide scaffolds with variable numbers of glycines are predicted computationally to have markedly different conformational ensembles. Ensemble comparison and overlap were quantified by the Jensen–Shannon divergence and a new measure introduced here, the embedding depth, which determines the extent to which a given ensemble is subsumed by another ensemble and which may be a more useful measure in developing immunogens that confer conformational selectivity to an antibody.

Rational Generation of Monoclonal Antibodies Selective for Pathogenic Forms of Alpha-Synuclein

“…The Collective Coordinate (CC) computational algorithm [ 24 ] was applied to stressed α-Syn protofibrils (PDB ID: 2N0A) to identify conformational epitopes predicted to be solvent-exposed on pathogenic forms of α-Syn but not on monomers or on fully formed fibrils. The CC algorithm identified EKTKEQ (aa 57–62) as a region thermodynamically likely to be solvent-exposed in oligomers and small soluble fibrils, with less inter-chain electrostatic and van der Waals interactions with neighboring monomers in the fibril, and increased local dynamics [ 23 ]. Cyclic peptide scaffolds containing a variable number of glycines at N- and C-termini (“glycindels”) were constructed to mimic the conformation of the predicted EKTK and TKEQ epitopes present in the oligomer ( Figure 1 ).…”

“…Computational modeling using Collective Coordinates [ 24 ] predicted exposure of conformational epitopes in the EKTKEQ (aa 57–62) region of misfolded pathogenic species of α-Syn (oligomers, small soluble fibrils) but not on α-Syn monomers or fully formed insoluble fibrils [ 23 ]. The conformational ensembles of the candidate epitopes EKTK and TKEQ predicted by the algorithm were approximated with cyclic peptide scaffolds containing flanking glycine residues on each side (“glycindels”) [ 25 ], and a cysteine between the glycine linkers, for conjugation to a carrier protein for immunization.…”

“…In order to generate optimally selective antibodies against pathogenic forms of α-Syn, we used computational modeling to identify conformational epitopes predicted to be exposed in α-Syn oligomers and small soluble fibrils/protofibrils, but to be inaccessible in large fully formed insoluble fibrils or α-Syn monomers [ 23 ]. Cyclic peptide scaffolds reproducing the conformational epitopes were used to immunize mice and generate mAbs.…”

Accelerated ensemble generation for cyclic peptides using a Reservoir-REMD implementation in GROMACS

“…The method of utilizing JSD to measure the ensemble similarity was also employed in our previous work. 43 Structural ensembles were extracted from the 300K replica with 500 ps sampling interval for CGPRRARSG and CGHHQKLVG, and 150 ps sampling interval for oxytocin. Ensembles of conventional MD were extracted every 1 ns.…”

“…Cyclic peptides have been widely used as potential therapeutics [38][39][40] and scaffolded antigens, [41][42][43] since they are in the "beyond-rule-of-five" chemical space 44 and have many protein characteristics. 45 Computational methods have been developed to design well-structured cyclic peptides that preferentially populate a single conformation, [45][46][47][48][49][50] which have led to several applications.…”