Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity.

In the early stages of drug development, large chemical libraries are typically screened to identify compounds of promising potency against the chosen targets. Often, however, the resulting hit compounds tend to have poor drug metabolism and pharmacokinetics (DMPK), with negative developability features that may be difficult to eliminate. Therefore, starting the drug discovery process with a "null library", compounds that have highly desirable DMPK properties but no potency against the chosen targets, could be advantageous. Here, we explore the opportunities offered by machine learning to realize this strategy in the case of the inhibition of α-synuclein aggregation, a process associated with Parkinson's disease. We apply MolDQN, a generative machine learning method, to build an inhibitory activity against α-synuclein aggregation into an initial inactive compound with good DMPK properties. Our results illustrate how generative modeling can be used to endow initially inert compounds with desirable developability properties.

Multiplexed Digital Characterization of Misfolded Protein Oligomers via Solid-State Nanopores.

Misfolded protein oligomers are of central importance in both the diagnosis and treatment of Alzheimer's and Parkinson's diseases. However, accurate high-throughput methods to detect and quantify oligomer populations are still needed. We present here a single-molecule approach for the detection and quantification of oligomeric species. The approach is based on the use of solid-state nanopores and multiplexed DNA barcoding to identify and characterize oligomers from multiple samples. We study α-synuclein oligomers in the presence of several small-molecule inhibitors of α-synuclein aggregation as an illustration of the potential applicability of this method to the development of diagnostic and therapeutic methods for Parkinson's disease.

Structure-Based Discovery of Small-Molecule Inhibitors of the Autocatalytic Proliferation of α-Synuclein Aggregates.

The presence of amyloid fibrils of α-synuclein is closely associated with Parkinson's disease and related synucleinopathies. It is still very challenging, however, to systematically discover small molecules that prevent the formation of these aberrant aggregates. Here, we describe a structure-based approach to identify small molecules that specifically inhibit the surface-catalyzed secondary nucleation step in the aggregation of α-synuclein by binding to the surface of the amyloid fibrils. The resulting small molecules are screened using a range of kinetic and thermodynamic assays for their ability to bind α-synuclein fibrils and prevent the further generation of α-synuclein oligomers. This study demonstrates that the combination of structure-based and kinetic-based drug discovery methods can lead to the identification of small molecules that selectively inhibit the autocatalytic proliferation of α-synuclein aggregates.

SAR by kinetics for drug discovery in protein misfolding diseases.

To develop effective therapeutic strategies for protein misfolding diseases, a promising route is to identify compounds that inhibit the formation of protein oligomers. To achieve this goal, we report a structure-activity relationship (SAR) approach based on chemical kinetics to estimate quantitatively how small molecules modify the reactive flux toward oligomers. We use this estimate to derive chemical rules in the case of the amyloid beta peptide (Aß), which we then exploit to optimize starting compounds to curtail Aß oligomer formation. We demonstrate this approach by converting an inactive rhodanine compound into an effective inhibitor of Aß oligomer formation by generating chemical derivatives in a systematic manner. These results provide an initial demonstration of the potential of drug discovery strategies based on targeting directly the production of protein oligomers.

Transthyretin Inhibits Primary and Secondary Nucleations of Amyloid-ß Peptide Aggregation and Reduces the Toxicity of Its Oligomers.

Alzheimer's disease is associated with the deposition of the amyloid-ß peptide (Aß) into extracellular senile plaques in the brain. In vitro and in vivo observations have indicated that transthyretin (TTR) acts as an Aß scavenger in the brain, but the mechanism has not been fully resolved. We have monitored the aggregation process of Aß40 by thioflavin T fluorescence, in the presence or absence of different concentrations of preformed seed aggregates of Aß40, of wild-type tetrameric TTR (WT-TTR), and of a variant engineered to be stable as a monomer (M-TTR). Both WT-TTR and M-TTR were found to inhibit specific steps of the process of Aß40 fibril formation, which are primary and secondary nucleations, without affecting the elongation of the resulting fibrils. Moreover, the analysis shows that both WT-TTR and M-TTR bind to Aß40 oligomers formed in the aggregation reaction and inhibit their conversion into the shortest fibrils able to elongate. Using biophysical methods, TTR was found to change some aspects of its overall structure following such interactions with Aß40 oligomers, as well as with oligomers of Aß42, while maintaining its overall topology. Hence, it is likely that the predominant mechanism by which TTR exerts its protective role lies in the binding of TTR to the Aß oligomers and in inhibiting primary and secondary nucleation processes, which limits both the toxicity of Aß oligomers and the ability of the fibrils to proliferate.

Monomeric and fibrillar α-synuclein exert opposite effects on the catalytic cycle that promotes the proliferation of Aß42 aggregates.

The coaggregation of the amyloid-ß peptide (Aß) and α-synuclein is commonly observed in a range of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. The complex interplay between Aß and α-synuclein has led to seemingly contradictory results on whether α-synuclein promotes or inhibits Aß aggregation. Here, we show how these conflicts can be rationalized and resolved by demonstrating that different structural forms of α-synuclein exert different effects on Aß aggregation. Our results demonstrate that whereas monomeric α-synuclein blocks the autocatalytic proliferation of Aß42 (the 42-residue form of Aß) fibrils, fibrillar α-synuclein catalyses the heterogeneous nucleation of Aß42 aggregates. It is thus the specific balance between the concentrations of monomeric and fibrillar α-synuclein that determines the outcome of the Aß42 aggregation reaction.

Systematic development of small molecules to inhibit specific microscopic steps of Aß42 aggregation in Alzheimer's disease.

The aggregation of the 42-residue form of the amyloid-ß peptide (Aß42) is a pivotal event in Alzheimer's disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aß42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aß42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aß42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery.

Rationally Designed Antibodies as Research Tools to Study the Structure-Toxicity Relationship of Amyloid-ß Oligomers.

Alzheimer's disease is associated with the aggregation of the amyloid-ß peptide (Aß), resulting in the deposition of amyloid plaques in brain tissue. Recent scrutiny of the mechanisms by which Aß aggregates induce neuronal dysfunction has highlighted the importance of the Aß oligomers of this protein fragment. Because of the transient and heterogeneous nature of these oligomers, however, it has been challenging to investigate the detailed mechanisms by which these species exert cytotoxicity. To address this problem, we demonstrate here the use of rationally designed single-domain antibodies (DesAbs) to characterize the structure-toxicity relationship of Aß oligomers. For this purpose, we use Zn2+-stabilized oligomers of the 40-residue form of Aß (Aß40) as models of brain Aß oligomers and two single-domain antibodies (DesAb18-24 and DesAb34-40), designed to bind to epitopes at residues 18-24 and 34-40 of Aß40, respectively. We found that the DesAbs induce a change in structure of the Zn2+-stabilized Aß40 oligomers, generating a simultaneous increase in their size and solvent-exposed hydrophobicity. We then observed that these increments in both the size and hydrophobicity of the oligomers neutralize each other in terms of their effects on cytotoxicity, as predicted by a recently proposed general structure-toxicity relationship, and observed experimentally. These results illustrate the use of the DesAbs as research tools to investigate the biophysical and cytotoxicity properties of Aß oligomers.

Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation.

Understanding how normally soluble peptides and proteins aggregate to form amyloid fibrils is central to many areas of modern biomolecular science, ranging from the development of functional biomaterials to the design of rational therapeutic strategies against increasingly prevalent medical conditions such as Alzheimer's and Parkinson's diseases. As such, there is a great need to develop models to mechanistically describe how amyloid fibrils are formed from precursor peptides and proteins. Here we review and discuss how ideas and concepts from chemical reaction kinetics can help to achieve this objective. In particular, we show how a combination of theory, experiments, and computer simulations, based on chemical kinetics, provides a general formalism for uncovering, at the molecular level, the mechanistic steps that underlie the phenomenon of amyloid fibril formation.

HSPB6: A lipid-dependent molecular chaperone inhibits α-synuclein aggregation.

The process of protein misfolding and aggregation is associated with various cytotoxic effects. Understanding how this phenomenon is regulated by the protein homeostasis system, however, is difficult, since it takes place through a complex non-linear network of coupled microscopic steps, including primary nucleation, fibril elongation, and secondary nucleation, which depend on environmental factors. To address this problem, we studied how the aggregation of α-synuclein, a protein associated with Parkinson's disease, is modulated by molecular chaperones and lipid membranes. We focused on small heat shock proteins (sHSPs/HSPBs), which interact with proteins and lipids and are upregulated during aging, a major risk factor for protein misfolding diseases. HSPBs act on different microscopic steps to prevent α-synuclein aggregation, with HSPB6 showing a lipid-dependent chaperone activity. Our findings provide an example of how HSPBs diversified their mechanisms of action to reach an efficient regulation of protein misfolding and aggregation within the complex cellular environment.

Maturation-dependent changes in the size, structure and seeding capacity of Aß42 amyloid fibrils.

Many proteins self-assemble to form amyloid fibrils, which are highly organized structures stabilized by a characteristic cross-ß network of hydrogen bonds. This process underlies a variety of human diseases and can be exploited to develop versatile functional biomaterials. Thus, protein self-assembly has been widely studied to shed light on the properties of fibrils and their intermediates. A still open question in the field concerns the microscopic processes that underlie the long-time behaviour and properties of amyloid fibrillar assemblies. Here, we use atomic force microscopy with angstrom-sensitivity to observe that amyloid fibrils undergo a maturation process, associated with an increase in both fibril length and thickness, leading to a decrease of their density, and to a change in their cross-ß sheet content. These changes affect the ability of the fibrils to catalyse the formation of new aggregates. The identification of these changes helps us understand the fibril maturation processes, facilitate the targeting of amyloid fibrils in drug discovery, and offer insight into the development of biocompatible and sustainable protein-based materials.

Thermal and pH stress dictate distinct mechanisms of monoclonal antibody aggregation.

Protein aggregation is a significant challenge in the development of monoclonal antibodies (mAbs), which can be exacerbated by stress conditions encountered along its production pipeline. In this study, we examine how thermal and pH stress conditions influence mAb aggregation mechanisms. We observe a complex interplay between these factors that significantly affects mAb stability, particularly under combined stress conditions. The mAb aggregates formed also varied distinctly in size and properties depending on the pH and thermal conditions, suggesting differences in their underlying mechanisms. Using a combination of experimental methods and kinetic modelling, we found that acidic pH conditions primarily promoted aggregation via the mAb unfolding step, while higher temperature conditions facilitated the formation of larger aggregates via monomer-independent cluster-cluster aggregation steps. These insights underscore the importance of extrinsic stress conditions in determining mAb aggregation propensity, and potentially provides a quantitative framework to holistically assess this across various accelerated stress conditions for the development of stable biologics.

A Relationship between the Structures and Neurotoxic Effects of Aß Oligomers Stabilized by Different Metal Ions.

Oligomeric assemblies of the amyloid ß peptide (Aß) have been investigated for over two decades as possible neurotoxic agents in Alzheimer's disease. However, due to their heterogeneous and transient nature, it is not yet fully established which of the structural features of these oligomers may generate cellular damage. Here, we study distinct oligomer species formed by Aß40 (the 40-residue form of Aß) in the presence of four different metal ions (Al3+, Cu2+, Fe2+, and Zn2+) and show that they differ in their structure and toxicity in human neuroblastoma cells. We then describe a correlation between the size of the oligomers and their neurotoxic activity, which provides a type of structure-toxicity relationship for these Aß40 oligomer species. These results provide insight into the possible role of metal ions in Alzheimer's disease by the stabilization of Aß oligomers.

Antibody glycan quality predicted from CHO cell culture media markers and machine learning.

N-glycosylation can have a profound effect on the quality of mAb therapeutics. In biomanufacturing, one of the ways to influence N-glycosylation patterns is by altering the media used to grow mAb cell expression systems. Here, we explore the potential of machine learning (ML) to forecast the abundances of N-glycan types based on variables related to the growth media. The ML models exploit a dataset consisting of detailed glycomic characterisation of Anti-HER fed-batch bioreactor cell cultures measured daily under 12 different culture conditions, such as changes in levels of dissolved oxygen, pH, temperature, and the use of two different commercially available media. By performing spent media quantitation and subsequent calculation of pseudo cell consumption rates (termed media markers) as inputs to the ML model, we were able to demonstrate a small subset of media markers (18 selected out of 167 mass spectrometry peaks) in a Chinese Hamster Ovary (CHO) cell cultures are important to model N-glycan relative abundances (Regression - correlations between 0.80-0.92; Classification - AUC between 75.0-97.2). The performances suggest the ML models can infer N-glycan critical quality attributes from extracellular media as a proxy. Given its accuracy, we envisage its potential applications in biomaufactucuring, especially in areas of process development, downstream and upstream bioprocessing.

Optimization of a small molecule inhibitor of secondary nucleation in α-synuclein aggregation.

Parkinson's disease is characterised by the deposition in the brain of amyloid aggregates of α-synuclein. The surfaces of these amyloid aggregates can catalyse the formation of new aggregates, giving rise to a positive feedback mechanism responsible for the rapid proliferation of α-synuclein deposits. We report a procedure to enhance the potency of a small molecule to inhibit the aggregate proliferation process using a combination of in silico and in vitro methods. The optimized small molecule shows potency already at a compound:protein stoichiometry of 1:20. These results illustrate a strategy to accelerate the optimisation of small molecules against α-synuclein aggregation by targeting secondary nucleation.

Enhancing pharmacokinetic and pharmacodynamic properties of recombinant therapeutic proteins by manipulation of sialic acid content.

The circulatory half-life of recombinant therapeutic proteins is an important pharmacokinetic attribute because it determines the dosing frequency of these drugs, translating directly to treatment cost. Thus, recombinant therapeutic glycoproteins such as monoclonal antibodies have been chemically modified by various means to enhance their circulatory half-life. One approach is to manipulate the N-glycan composition of these agents. Among the many glycan constituents, sialic acid (specifically, N-acetylneuraminic acid) plays a critical role in extending circulatory half-life by masking the terminal galactose that would otherwise be recognised by the hepatic asialoglycoprotein receptor (ASGPR), resulting in clearance of the biotherapeutic from the circulation. This review aims to provide an illustrative overview of various strategies to enhance the pharmacokinetic/pharmacodynamic properties of recombinant therapeutic proteins through manipulation of their sialic acid content.

Secondary Processes Dominate the Quiescent, Spontaneous Aggregation of α-Synuclein at Physiological pH with Sodium Salts.

The accurate recapitulation in an in vitro assay of the aggregation process of α-synuclein in Parkinson's disease has been a significant challenge. As α-synuclein does not aggregate spontaneously in most currently used in vitro assays, primary nucleation is triggered by the presence of surfaces such as lipid membranes or interfaces created by shaking, to achieve aggregation on accessible time scales. In addition, secondary nucleation is typically only observed by lowering the pH below 5.8. Here we investigated assay conditions that enables spontaneous primary nucleation and secondary nucleation at pH 7.4. Using 400 mM sodium phosphate, we observed quiescent spontaneous aggregation of α-synuclein and established that this aggregation is dominated by secondary processes. Furthermore, the presence of potassium ions enhanced the reproducibility of quiescent α-synuclein aggregation. This work provides a framework for the study of spontaneous α-synuclein aggregation at physiological pH.

Combinations of Vitamin A and Vitamin E Metabolites Confer Resilience against Amyloid-ß Aggregation.

Alzheimer's disease is characterized by the presence in the brain of amyloid plaques formed by the aberrant deposition of the amyloid-ß peptide (Aß). Since many vitamins are dysregulated in this disease, we explored whether these molecules contribute to the protein homeostasis system by modulating Aß aggregation. By screening 18 fat-soluble and water-soluble vitamin metabolites, we found that retinoic acid and α-tocopherol, two metabolites of vitamin A and vitamin E, respectively, affect Aß aggregation both in vitro and in a Caenorhabditis elegans model of Aß toxicity. We then show that the effects of these two vitamin metabolites in specific combinations cancel each other out, consistent with the "resilience in complexity" hypothesis, according to which the complex composition of the cellular environment could have an overall protective role against protein aggregation through the simultaneous presence of aggregation promoters and inhibitors. Taken together, these results indicate that vitamins can be added to the list of components of the protein homeostasis system that regulate protein aggregation.

Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α-Synuclein Secondary Nucleation.

The high attrition rate in drug discovery pipelines is an especially pressing issue for Parkinson's disease, for which no disease-modifying drugs have yet been approved. Numerous clinical trials targeting α-synuclein aggregation have failed, at least in part due to the challenges in identifying potent compounds in preclinical investigations. To address this problem, we present a machine learning approach that combines generative modeling and reinforcement learning to identify small molecules that perturb the kinetics of aggregation in a manner that reduces the production of oligomeric species. Training data were obtained by an assay reporting on the degree of inhibition of secondary nucleation, which is the most important mechanism of α-synuclein oligomer production. This approach resulted in the identification of small molecules with high potency against secondary nucleation.