Advances in the understanding of Alzheimer’s disease (AD) suggest that pathogenesis is not directly related to plaque burden, but rather to soluble toxic amyloid-beta oligomers (AßO). Therapeutic antibodies targeting Aß monomers and/or plaque have shown limited efficacy and dose-limiting adverse events in clinical trials. These findings suggest that antibodies capable of selectively neutralizing toxic AßO may achieve improved efficacy and safety. To this end, we generated monoclonal antibodies against a conformational Aß epitope predicted by computational modeling to be presented on toxic AßO but not monomers or fibrils. The resulting lead antibody, PMN310, showed the desired AßO-selective binding profile. In vitro , PMN310 inhibited AßO propagation and toxicity. In vivo , PMN310 prevented AßO-induced loss of memory formation and reduced synaptic loss and inflammation. A humanized version (huPMN310) compared favorably to other Aß-directed antibodies showing a lack of adverse event-associated binding to Aß deposits in AD brains, and greater selective binding to AßO-enriched AD brain fractions that contain synaptotoxic Aß species. Systemic administration of huPMN310 in mice resulted in brain exposure and kinetics comparable to those of other therapeutic human monoclonal antibodies. Greater selectivity for AßO and the potential to safely administer high doses of huPMN310 are expected to result in enhanced safety and therapeutic potency.
Oligomers of amyloid-β (AβO) are deemed key in synaptotoxicity and amyloid seeding of Alzheimer's disease (AD). However, the heterogeneous and dynamic nature of AβO and inadequate markers for AβO subtypes have stymied effective AβO identification and therapeutic targeting in vivo. We identified an AβO-subclass epitope defined by differential solvent orientation of the lysine 28 side chain in a constrained loop of serine-asparagine-lysine (cSNK), rarely displayed in molecular dynamics simulations of monomer and fibril ensembles. A mouse monoclonal antibody targeting AβO recognizes ∼50-60 kDa SDS-resistant soluble Aβ assemblages in AD brain and prolongs the lag phase of Aβ aggregation in vitro. Acute peripheral infusion of a murine IgG1 anti-AβO in two AD mouse models reduced soluble brain Aβ aggregates by 20-30%. Chronic cSNK peptide immunization of APP/PS1 mice engendered an anti-AβO IgG1 response without epitope spreading to Aβ monomers or fibrils and was accompanied by preservation of global PSD95 expression and improved cued fear memory. Our data indicate that the oligomer subtype AβO participates in synaptotoxicity and propagation of Aβ aggregation in vitro and in vivo.
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.
Multiple different screening tests for candidate leads in drug development may often yield conflicting or ambiguous results, sometimes making the selection of leads a nontrivial maximum-likelihood ranking problem. Here, we employ methods from the field of multiple criteria decision making (MCDM) to the problem of screening candidate antibody therapeutics. We employ the SMAA-TOPSIS method to rank a large cohort of antibodies using up to eight weighted screening criteria, in order to find lead candidate therapeutics for Alzheimer’s disease, and determine their robustness to both uncertainty in screening measurements, as well as uncertainty in the user-defined weights of importance attributed to each screening criterion. To choose lead candidates and measure the confidence in their ranking, we propose two new quantities, the Retention Probability and the Topness, as robust measures for ranking. This method may enable more systematic screening of candidate therapeutics when it becomes difficult intuitively to process multi-variate screening data that distinguishes candidates, so that additional candidates may be exposed as potential leads, increasing the likelihood of success in downstream clinical trials. The method properly identifies true positives and true negatives from synthetic data, its predictions correlate well with known clinically approved antibodies vs. those still in trials, and it allows for ranking analyses using antibody developability profiles in the literature. We provide a webserver where users can apply the method to their own data: http://bjork.phas.ubc.ca .
Misfolded toxic forms of alpha-synuclein (α-Syn) have been implicated in the pathogenesis of synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). The α-Syn oligomers and soluble fibrils have been shown to mediate neurotoxicity and cell-to-cell propagation of pathology. To generate antibodies capable of selectively targeting pathogenic forms of α-Syn, computational modeling was used to predict conformational epitopes likely to become exposed on oligomers and small soluble fibrils, but not on monomers or fully formed insoluble fibrils. Cyclic peptide scaffolds reproducing these conformational epitopes exhibited neurotoxicity and seeding activity, indicating their biological relevance. Immunization with the conformational epitopes gave rise to monoclonal antibodies (mAbs) with the desired binding profile showing selectivity for toxic α-Syn oligomers and soluble fibrils, with little or no reactivity with monomers, physiologic tetramers, or Lewy bodies. Recognition of naturally occurring soluble α-Syn aggregates in brain extracts from DLB and MSA patients was confirmed by surface plasmon resonance (SPR). In addition, the mAbs inhibited the seeding activity of sonicated pre-formed fibrils (PFFs) in a thioflavin-T fluorescence-based aggregation assay. In neuronal cultures, the mAbs protected primary rat neurons from toxic α-Syn oligomers, reduced the uptake of PFFs, and inhibited the induction of pathogenic phosphorylated aggregates of endogenous α-Syn. Protective antibodies selective for pathogenic species of α-Syn, as opposed to pan α-Syn reactivity, are expected to provide enhanced safety and therapeutic potency by preserving normal α-Syn function and minimizing the diversion of active antibody from the target by the more abundant non-toxic forms of α-Syn in the circulation and central nervous system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.