Small-molecule sequestration of amyloid-β as a drug discovery strategy for Alzheimer's disease

A Small Molecule Stabilizes the Disordered Native State of the Alzheimer's Aβ Peptide

The stabilization of native states of proteins is a powerful drug discovery strategy. It is still unclear, however, whether this approach can be applied to intrinsically disordered proteins. Here, we report a small molecule that stabilizes the native state of the Aβ42 peptide, an intrinsically disordered protein fragment associated with Alzheimer's disease. We show that this stabilization takes place by a disordered binding mechanism, in which both the small molecule and the Aβ42 peptide remain disordered. This disordered binding mechanism involves enthalpically favorable local π-stacking interactions coupled with entropically advantageous global effects. These results indicate that small molecules can stabilize disordered proteins in their native states through transient non-specific interactions that provide enthalpic gain while simultaneously increasing the conformational entropy of the proteins.

Therapeutic potential for amyloid surface inhibitor: only amyloid-β oligomers formed by secondary nucleation disrupt lipid membrane integrity

Inhibition of amyloid-β peptide (Aβ) aggregation is a promising therapeutic strategy for Alzheimer's disease (AD), as Aβ aggregation is generally believed to trigger AD pathology. Pre-fibril Aβ-oligomers induce membrane disruption and are crucial to neurotoxicity. We have previously designed a short peptide called cyclic helical amyloid surface inhibitor (cHASI) that can selectively bind to the Aβ fibril surface. Here, we use cHASI to efficiently inhibit the surface-catalysed secondary nucleation process of Aβ in a lipid membrane environment. By incubating Aβ monomers with lipid vesicles, we show that during the assembly of Aβ into amyloid fibrils, oligomers are formed that markedly disrupt the lipid bilayer. Remarkably, when Aβ monomers are incubated with cHASI, although Aβ forms amyloid fibrils via primary nucleation and elongation, this pathway to fibrils does not damage the lipid bilayer. This indicates that only oligomers produced during secondary surface nucleation disrupt membrane integrity. The protective effect of cHASI is confirmed by cytotoxicity assays. Our study highlights the therapeutic potential for inhibiting the secondary nucleation process in Aβ aggregation, rather than inhibiting all pathways to fibril formation.

Identifying Alzheimer's genes via brain transcriptome mapping

BACKGROUND

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders characterized by progressive decline in cognitive function. Targeted genetic analyses, genome-wide association studies, and imaging genetic analyses have been performed to detect AD risk and protective genes and have successfully identified dozens of AD susceptibility loci. Recently, brain imaging transcriptomics analyses have also been conducted to investigate the relationship between neuroimaging traits and gene expression measures to identify interesting gene-traits associations. These imaging transcriptomic studies typically do not involve the disease outcome in the analysis, and thus the identified brain or transcriptomic markers may not be related or specific to the disease outcome.

RESULTS

We propose an innovative two-stage approach to identify genes whose expression profiles are related to diagnosis phenotype via brain transcriptome mapping. Specifically, we first map the effects of a diagnosis phenotype onto imaging traits across the brain using a linear regression model. Then, the gene-diagnosis association is assessed by spatially correlating the brain transcriptome map with the diagnostic effect map on the brain-wide imaging traits. To demonstrate the promise of our approach, we apply it to the integrative analysis of the brain transcriptome data from the Allen Human Brain Atlas (AHBA) and the amyloid imaging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Our method identifies 12 genes whose brain-wide transcriptome patterns are highly correlated with six different diagnostic effect maps on the amyloid imaging traits. These 12 genes include four confirmatory findings (i.e., AD genes reported in DisGeNET) and eight novel genes that have not be associated with AD in DisGeNET.

CONCLUSION

We have proposed a novel disease-related brain transcriptomic mapping method to identify genes whose expression profiles spatially correlated with regional diagnostic effects on a studied brain trait. Our empirical study on the AHBA and ADNI data shows the promise of the approach, and the resulting AD gene discoveries provide valuable information for better understanding biological pathways from transcriptomic signatures to intermediate brain traits and to phenotypic disease outcomes.

Energetics of a protein disorder-order transition in small molecule recognition

Many proteins recognise other proteins via mechanisms that involve the folding of intrinsically disordered regions upon complex formation. Here we investigate how the selectivity of a drug-like small molecule arises from its modulation of a protein disorder-to-order transition. Binding of the compound AM-7209 has been reported to confer order upon an intrinsically disordered ‘lid’ region of the oncoprotein MDM2. Calorimetric measurements revealed that truncation of the lid region of MDM2 increases the apparent dissociation constant of AM-7209 250-fold. By contrast, lid truncation has little effect on the binding of the ligand Nutlin-3a. Insights into these differential binding energetics were obtained via a complete thermodynamic analysis that featured adaptive absolute alchemical free energy of binding calculations with enhanced-sampling molecular dynamics simulations. The simulations reveal that in apo MDM2 the ordered lid state is energetically disfavoured. AM-7209, but not Nutlin-3a, shows a significant energetic preference for ordered lid conformations, thus shifting the balance towards ordering of the lid in the AM-7209/MDM2 complex. The methodology reported herein should facilitate broader targeting of intrinsically disordered regions in medicinal chemistry.

Molecular simulations and biophysical measurements elucidate why the ligand AM-7209 orders a disordered region of the protein MDM2 on binding. This work expands strategies available to medicinal chemists for targeting disordered proteins.

High-throughput screening for amyloid-β binding natural small-molecules based on the combinational use of biolayer interferometry and UHPLC−DAD-Q/TOF-MS/MS

Discovery of drugs rapidly and effectively is an important aspect for Alzheimer's disease (AD). In this study, a novel high-throughput screening (HTS) method aims at screening the small-molecules with amyloid-β (Aβ) binding affinity from natural medicines, based on the combinational use of biolayer interferometry (BLI) and ultra-high-performance liquid chromatography coupled with diode-array detector and quadrupole/time-of-flight tandem mass spectrometry (UHPLC−DAD-Q/TOF-MS/MS) has been firstly developed. Briefly, the components in natural medicines disassociated from biotinylated Aβ were collected to analyze their potential Aβ binding affinity by UHPLC−DAD-Q/TOF-MS/MS. Here, baicalein was confirmed to exhibit the highest binding affinity with Aβ in Scutellaria baicalensis. Moreover, polyporenic acid C (PPAC), dehydrotumulosic acid (DTA), and tumulosic acid (TA) in Kai-Xin-San (KXS) were also identified as potent Aβ inhibitors. Further bioactivity validations indicated that these compounds could inhibit Aβ fibrillation, improve the viability in Aβ-induced PC-12 cells, and decrease the Aβ content and improve the behavioral ability in Caenorhabditis elegans. The molecular docking results confirmed that PPAC, DTA, and TA possessed good binding properties with Aβ. Collectively, the present study has provided a novel and effective HTS method for the identification of natural inhibitors on Aβ fibrillation, which may accelerate the process on anti-AD drugs discovery and development.

Endogenous Human Proteins Interfering with Amyloid Formation

Amyloid formation is a pathological process associated with a wide range of degenerative disorders, including Alzheimer’s disease, Parkinson’s disease, and diabetes mellitus type 2. During disease progression, abnormal accumulation and deposition of proteinaceous material are accompanied by tissue degradation, inflammation, and dysfunction. Agents that can interfere with the process of amyloid formation or target already formed amyloid assemblies are consequently of therapeutic interest. In this context, a few endogenous proteins have been associated with an anti-amyloidogenic activity. Here, we review the properties of transthyretin, apolipoprotein E, clusterin, and BRICHOS protein domain which all effectively interfere with amyloid in vitro, as well as displaying a clinical impact in humans or animal models. Their involvement in the amyloid formation process is discussed, which may aid and inspire new strategies for therapeutic interventions.

Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma

Intrinsically disordered proteins (IDPs) are proteins that lack rigid 3D structure. Hence, they are often misconceived to present a challenge to Anfinsen's dogma. However, IDPs exist as ensembles that sample a quasi-continuum of rapidly interconverting conformations and, as such, may represent proteins at the extreme limit of the Anfinsen postulate. IDPs play important biological roles and are key components of the cellular protein interaction network (PIN). Many IDPs can interconvert between disordered and ordered states as they bind to appropriate partners. Conformational dynamics of IDPs contribute to conformational noise in the cell. Thus, the dysregulation of IDPs contributes to increased noise and "promiscuous" interactions. This leads to PIN rewiring to output an appropriate response underscoring the critical role of IDPs in cellular decision making. Nonetheless, IDPs are not easily tractable experimentally. Furthermore, in the absence of a reference conformation, discerning the energy landscape representation of the weakly funneled IDPs in terms of reaction coordinates is challenging. To understand conformational dynamics in real time and decipher how IDPs recognize multiple binding partners with high specificity, several sophisticated knowledge-based and physics-based in silico sampling techniques have been developed. Here, using specific examples, we highlight recent advances in energy landscape visualization and molecular dynamics simulations to discern conformational dynamics and discuss how the conformational preferences of IDPs modulate their function, especially in phenotypic switching. Finally, we discuss recent progress in identifying small molecules targeting IDPs underscoring the potential therapeutic value of IDPs. Understanding structure and function of IDPs can not only provide new insight on cellular decision making but may also help to refine and extend Anfinsen's structure/function paradigm.

Tuning the rate of aggregation of hIAPP into amyloid using small-molecule modulators of assembly

Human islet amyloid polypeptide (hIAPP) self-assembles into amyloid fibrils which deposit in pancreatic islets of type 2 diabetes (T2D) patients. Here, we applied chemical kinetics to study the mechanism of amyloid assembly of wild-type hIAPP and its more amyloidogenic natural variant S20G. We show that the aggregation of both peptides involves primary nucleation, secondary nucleation and elongation. We also report the discovery of two structurally distinct small-molecule modulators of hIAPP assembly, one delaying the aggregation of wt hIAPP, but not S20G; while the other enhances the rate of aggregation of both variants at substoichiometric concentrations. Investigation into the inhibition mechanism(s) using chemical kinetics, native mass spectrometry, fluorescence titration, SPR and NMR revealed that the inhibitor retards primary nucleation, secondary nucleation and elongation, by binding peptide monomers. By contrast, the accelerator predominantly interacts with species formed in the lag phase. These compounds represent useful chemical tools to study hIAPP aggregation and may serve as promising starting-points for the development of therapeutics for T2D.

Molecular Basis of Small-Molecule Binding to α-Synuclein

Intrinsically disordered proteins (IDPs) are implicated in many human diseases. They have generally not been amenable to conventional structure-based drug design, however, because their intrinsic conformational variability has precluded an atomic-level understanding of their binding to small molecules. Here we present long-time-scale, atomic-level molecular dynamics (MD) simulations of monomeric α-synuclein (an IDP whose aggregation is associated with Parkinson’s disease) binding the small-molecule drug fasudil in which the observed protein–ligand interactions were found to be in good agreement with previously reported NMR chemical shift data. In our simulations, fasudil, when bound, favored certain charge–charge and π-stacking interactions near the C terminus of α-synuclein but tended not to form these interactions simultaneously, rather breaking one of these interactions and forming another nearby (a mechanism we term dynamic shuttling). Further simulations with small molecules chosen to modify these interactions yielded binding affinities and key structural features of binding consistent with subsequent NMR experiments, suggesting the potential for MD-based strategies to facilitate the rational design of small molecules that bind with disordered proteins.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Drugging Fuzzy Complexes in Transcription

Transcription factors (TFs) are one of the most promising but underutilized classes of drug targets. The high degree of intrinsic disorder in both the structure and the interactions (i.e., “fuzziness”) of TFs is one of the most important challenges to be addressed in this context. Here, we discuss the impacts of fuzziness on transcription factor drug discovery, describing how disorder poses fundamental problems to the typical drug design, and screening approaches used for other classes of proteins such as receptors or enzymes. We then speculate on ways modern biophysical and chemical biology approaches could synergize to overcome many of these challenges by directly addressing the challenges imposed by TF disorder and fuzziness.

Influence of Chaperones on Amyloid Formation of Аβ Peptide

Background:

An extensive study of the folding and stability of proteins and their complexes has revealed a number of problems and questions that need to be answered. One of them is the effect of chaperones on the process of fibrillation of various proteins and peptides.

Methods:

We studied the effect of molecular chaperones, such as GroEL and α-crystallin, on the fibrillogenesis of the Aβ(1-42) peptide using electron microscopy and surface plasmon resonance.

Results:

Recombinant GroEL and Aβ(1-42) were isolated and purified. It was shown that the assembly of GroEL occurs without the addition of magnesium and potassium ions, as is commonly believed. According to the electron microscopy results, GroEL insignificantly affects the fibrillogenesis of the Aβ(1-42) peptide, while α-crystallin prevents the elongation of the Aβ(1-42) peptide fibrils. We have demonstrated that GroEL interacts nonspecifically with Aβ(1-42), while α-crystallin does not interact with Aβ(1-42) at all using surface plasmon resonance.

Conclusion:

The data obtained will help us understand the process of amyloid formation and the effect of various components on it.

Past, present and future of therapeutic strategies against amyloid-β peptides in Alzheimer's disease: a systematic review

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease in ageing, affecting around 46 million people worldwide but few treatments are currently available. The etiology of AD is still puzzling, and new drugs development and clinical trials have high failure rates. Urgent outline of an integral (multi-target) and effective treatment of AD is needed. Accumulation of amyloid-β (Aβ) peptides is considered one of the fundamental neuropathological pillars of the disease, and its dyshomeostasis has shown a crucial role in AD onset. Therefore, many amyloid-targeted therapies have been investigated. Here, we will systematically review recent (from 2014) investigational, follow-up and review studies focused on anti-amyloid strategies to summarize and analyze their current clinical potential. Combination of anti-Aβ therapies with new developing early detection biomarkers and other therapeutic agents acting on early functional AD changes will be highlighted in this review. Near-term approval seems likely for several drugs acting against Aβ, with recent FDA approval of a monoclonal anti-Aβ oligomers antibody -aducanumab- raising hopes and controversies. We conclude that, development of oligomer-epitope specific Aβ treatment and implementation of multiple improved biomarkers and risk prediction methods allowing early detection, together with therapies acting on other factors such as hyperexcitability in early AD, could be the key to slowing this global pandemic.

All-d-Enantiomeric Peptide D3 Designed for Alzheimer's Disease Treatment Dynamically Interacts with Membrane-Bound Amyloid-β Precursors

Alzheimer's disease (AD) is a severe neurodegenerative pathology with no effective treatment known. Toxic amyloid-β peptide (Aβ) oligomers play a crucial role in AD pathogenesis. All-d-Enantiomeric peptide D3 and its derivatives were developed to disassemble and destroy cytotoxic Aβ aggregates. One of the D3-like compounds is approaching phase II clinical trials; however, high-resolution details of its disease-preventing or pharmacological actions are not completely clear. We demonstrate that peptide D3 stabilizing Aβ monomer dynamically interacts with the extracellular juxtamembrane region of a membrane-bound fragment of an amyloid precursor protein containing the Aβ sequence. MD simulations based on NMR measurement results suggest that D3 targets the amyloidogenic region, not compromising its α-helicity and preventing intermolecular hydrogen bonding, thus creating prerequisites for inhibition of early steps of Aβ conversion into β-conformation and its toxic oligomerization. An enhanced understanding of the D3 action molecular mechanism facilitates development of effective AD treatment and prevention strategies.

An Overview of Several Inhibitors for Alzheimer's Disease: Characterization and Failure

Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character. Computer simulation is a tool that allows tracing the molecular motion of molecules; hence it complements Aβ experiments, as it allows to explore the binding mechanism between metal ions and Aβ oligomers close to the cellular membrane at the atomic resolution. In this context, integrated studies of experiments and computer simulations can assist in mapping the complete pathways of aggregation and toxicity of Aβ peptides. Aβ oligomers are disordered proteins, and due to a rapid exploration of their intrinsic conformational space in real-time, they are challenging therapeutic targets. Therefore, no good drug candidate could have been identified for clinical use. Our previous investigations identified two small molecules, M30 (2-Octahydroisoquinolin-2(1H)-ylethanamine) and Gabapentin, capable of Aβ binding and inhibiting molecular aggregation, synaptotoxicity, intracellular calcium signaling, cellular toxicity and memory losses induced by Aβ. Thus, we recommend these molecules as novel candidates to assist anti-AD drug discovery in the near future. This review discusses the most recent research investigations about the Aβ dynamics in water, close contact with cell membranes, and several therapeutic strategies to remove plaque formation.

Prion-Like Proteins in Phase Separation and Their Link to Disease

Aberrant protein folding underpins many neurodegenerative diseases as well as certain myopathies and cancers. Protein misfolding can be driven by the presence of distinctive prion and prion-like regions within certain proteins. These prion and prion-like regions have also been found to drive liquid-liquid phase separation. Liquid-liquid phase separation is thought to be an important physiological process, but one that is prone to malfunction. Thus, aberrant liquid-to-solid phase transitions may drive protein aggregation and fibrillization, which could give rise to pathological inclusions. Here, we review prions and prion-like proteins, their roles in phase separation and disease, as well as potential therapeutic approaches to counter aberrant phase transitions.

Consequences of Amide Connectivity in the Supramolecular Polymerization of Porphyrins: Spectroscopic Observations Rationalized by Theoretical Modelling

The correlation between molecular structure and mechanism of supramolecular polymerizations is a topic of great interest, with a special focus on the pathway complexity of porphyrin assemblies. Their cooperative polymerization typically yields highly ordered, long 1D polymers and is driven by a combination of π-stacking due to solvophobic effects and hydrogen bonding interactions. Subtle changes in molecular structure, however, have significant influence on the cooperativity factor and yield different aggregate types (J- versus H-aggregates) of different lengths. In this study, the influence of amide connectivity on the self-assembly behavior of porphyrin-based supramolecular monomers was investigated. While in nonpolar solvents, C=O centered monomers readily assemble into helical supramolecular polymers via a cooperative mechanism, their NH centered counterparts form short, non-helical J-type aggregates via an isodesmic pathway. A combination of spectroscopy and density functional theory modelling sheds light on the molecular origins causing this stunning difference in assembly properties and demonstrates the importance of molecular connectivity in the design of supramolecular systems. Finally, their mutual interference in copolymerization experiments is presented.

Generic nature of the condensed states of proteins

Proteins undergoing liquid-liquid phase separation are being discovered at an increasing rate. Since at the high concentrations present in the cell most proteins would be expected to form a liquid condensed state, this state should be considered to be a fundamental state of proteins along with the native state and the amyloid state. Here we discuss the generic nature of the liquid-like and solid-like condensed states, and describe a wide variety of biological functions conferred by these condensed states.

How to Determine Accurate Conformational Ensembles by Metadynamics Metainference: A Chignolin Study Case

The reliability and usefulness of molecular dynamics simulations of equilibrium processes rests on their statistical precision and their capability to generate conformational ensembles in agreement with available experimental knowledge. Metadynamics Metainference (M&M), coupling molecular dynamics with the enhanced sampling ability of Metadynamics and with the ability to integrate experimental information of Metainference, can in principle achieve both goals. Here we show that three different Metadynamics setups provide converged estimate of the populations of the three-states populated by a model peptide. Errors are estimated correctly by block averaging, but higher precision is obtained by performing independent replicates. One effect of Metadynamics is that of dramatically decreasing the number of effective frames resulting from the simulations and this is relevant for M&M where the number of replicas should be large enough to capture the conformational heterogeneity behind the experimental data. Our simulations allow also us to propose that monitoring the relative error associated with conformational averaging can help to determine the minimum number of replicas to be simulated in the context of M&M simulations. Altogether our data provides useful indication on how to generate sound conformational ensemble in agreement with experimental data.

Advances in targeting 'undruggable' transcription factors with small molecules

Transcription factors (TFs) represent key biological players in diseases including cancer, autoimmunity, diabetes and cardiovascular disease. However, outside nuclear receptors, TFs have traditionally been considered 'undruggable' by small-molecule ligands due to significant structural disorder and lack of defined small-molecule binding pockets. Renewed interest in the field has been ignited by significant progress in chemical biology approaches to ligand discovery and optimization, especially the advent of targeted protein degradation approaches, along with increasing appreciation of the critical role a limited number of collaborators play in the regulation of key TF effector genes. Here, we review current understanding of TF-mediated gene regulation, discuss successful targeting strategies and highlight ongoing challenges and emerging approaches to address them.

Structural Studies Providing Insights into Production and Conformational Behavior of Amyloid-β Peptide Associated with Alzheimer's Disease Development

Alzheimer's disease is the most common type of neurodegenerative disease in the world. Genetic evidence strongly suggests that aberrant generation, aggregation, and/or clearance of neurotoxic amyloid-β peptides (Aβ) triggers the disease. Aβ accumulates at the points of contact of neurons in ordered cords and fibrils, forming the so-called senile plaques. Aβ isoforms of different lengths are found in healthy human brains regardless of age and appear to play a role in signaling pathways in the brain and to have neuroprotective properties at low concentrations. In recent years, different substances have been developed targeting Aβ production, aggregation, interaction with other molecules, and clearance, including peptide-based drugs. Aβ is a product of sequential cleavage of the membrane glycoprotein APP (amyloid precursor protein) by β- and γ-secretases. A number of familial mutations causing an early onset of the disease have been identified in the APP, especially in its transmembrane domain. The mutations are reported to influence the production, oligomerization, and conformational behavior of Aβ peptides. This review highlights the results of structural studies of the main proteins involved in Alzheimer's disease pathogenesis and the molecular mechanisms by which perspective therapeutic substances can affect Aβ production and nucleation.

Small-Molecule Targeted Aβ42 Aggregate Degradation: Negatively Charged Small Molecules Are More Promising than the Neutral Ones

Heavy evidence has confirmed that Aβ42 oligomers are the most neurotoxic aggregates and play a critical role in the occurrence and development of Alzheimer's disease by causing functional neuron death, cognitive damage, and dementia. Disordered Aβ42 oligomers are challenging therapeutic targets, and no drug is currently in clinical use that modifies the properties of their monomeric states. Here, a negatively charged molecule (ER), rather than the neutral TS1 one, is identified by a molecular dynamics simulation method to be more capable of binding and sequestering the intrinsically disordered amyloid-β peptide Aβ42 in its soluble pentameric state as well as its monomeric components. Results reveal that the ERs interact with Aβ and inhibit the primary nucleation pathways in its aggregation process in entropic expansion mechanism for both Aβ42 and Aβ40 oligomers but with opposite characteristics of hydrophobic surface area (HSA). The interaction between Aβ42 oligomer and either charged ER or neutral TS1/TS0 characterizes decreased HSA, and the decrease in ER-involved case is highly visible, consistent with the observations from in silico and in vitro studies. By contrast, the presence of these inhibitors causes the HSA of Aβ40 oligomer to change undetectably and there is even a bit of increase in the histidine isomerized Aβ40 oligomer. The HSA distinction between Aβ42 and Aβ40 oligomer is possibly derived from the different effects of M35-inhibitor interaction, which is analogous to the effect of M35 oxidation. In comparison with the neutral TS1/TS0 inhibitors, ER is more prone to bind the residues located in the central (β1) and C-terminal (β2) regions of Aβ42 peptide, two key nucleation regions for Aβ intramolecular folding, intermolecular aggregation, and assembly. Notably, ER can strongly bind the charged residues, such as K16, K28, D23, to greatly disturb the potential stabilizer (e.g., salt-bridge, etc.) in metastable Aβ42 oligomers and protofibrils. These results illustrate the strategy of overcoming Alzheimer's disease from inhibiting its early stage Aβ aggregation with two kinds of small molecules to alter their behavior for therapeutic purposes and strongly recommend paying more attention to the engineering and development of negatively charged inhibitors, the long-term underappreciated ones, targeting the early stage Aβ aggregates.

Intrinsically disordered proteins and biomolecular condensates as drug targets

Intrinsically disordered domains represent attractive therapeutic targets because they play key roles in cancer, as well as in neurodegenerative and infectious diseases. They are, however, considered undruggable because they do not form stable binding pockets for small molecules and, therefore, have not been prioritized in drug discovery. Under physiological solution conditions many biomedically relevant intrinsically disordered proteins undergo phase separation processes leading to the formation of mesoscopic highly dynamic assemblies, generally known as biomolecular condensates that define environments that can be quite different from the solutions surrounding them. In what follows, we review key recent findings in this area and show how biomolecular condensation can offer opportunities for modulating the activities of intrinsically disordered targets.

Cholesterol Molecules Alter the Energy Landscape of Small Aβ1-42 Oligomers

Small amyloid-β (Aβ) oligomers are believed to be key pathogenic species in Alzheimer's disease (AD). One suggested toxicity mechanism is the detergent model where oligomers remove lipid molecules from the bilayer. Senile plaques of AD patients also accumulate a 1:1 ratio of cholesterol/Aβ. What are the dominant structures of small Aβ42 oligomers with cholesterol molecules in aqueous solution? Here, we answer this question by performing atomistic replica exchange molecular dynamics simulations of Aβ42 dimers and trimers. Our simulations demonstrate that the interactions with cholesterol molecules change completely the energy landscape of small Aβ42 oligomers. This result shows that simulations in the bulk solution cannot recapitulate aggregation in the brain extracellular space.

A method of incorporating rate constants as kinetic constraints in molecular dynamics simulations

From the point of view of statistical mechanics, a full characterization of a molecular system requires an accurate determination of its possible states, their populations, and the respective interconversion rates. Toward this goal, well-established methods increase the accuracy of molecular dynamics simulations by incorporating experimental information about states using structural restraints and about populations using thermodynamics restraints. However, it is still unclear how to include experimental knowledge about interconversion rates. Here, we introduce a method of imposing known rate constants as constraints in molecular dynamics simulations, which is based on a combination of the maximum-entropy and maximum-caliber principles. Starting from an existing ensemble of trajectories, obtained from either molecular dynamics or enhanced trajectory sampling, this method provides a minimally perturbed path distribution consistent with the kinetic constraints, as well as modified free energy and committor landscapes. We illustrate the application of the method to a series of model systems, including all-atom molecular simulations of protein folding. Our results show that by combining experimental rate constants and molecular dynamics simulations, this approach enables the determination of transition states, reaction mechanisms, and free energies. We anticipate that this method will extend the applicability of molecular simulations to kinetic studies in structural biology and that it will assist the development of force fields to reproduce kinetic and thermodynamic observables. Furthermore, this approach is generally applicable to a wide range of systems in biology, physics, chemistry, and material science.

A kinetic ensemble of the Alzheimer's Aβ peptide

The conformational and thermodynamic properties of disordered proteins are commonly described in terms of structural ensembles and free energy landscapes. To provide information on the transition rates between the different states populated by these proteins, it would be desirable to generalize this description to kinetic ensembles. Approaches based on the theory of stochastic processes can be particularly suitable for this purpose. Here, we develop a Markov state model and apply it to determine a kinetic ensemble of Aβ42, a disordered peptide associated with Alzheimer's disease. Through the Google Compute Engine, we generated 315-µs all-atom molecular dynamics trajectories. Using a probabilistic-based definition of conformational states in a neural network approach, we found that Aβ42 is characterized by inter-state transitions on the microsecond timescale, exhibiting only fully unfolded or short-lived, partially folded states. Our results illustrate how kinetic ensembles provide effective information about the structure, thermodynamics and kinetics of disordered proteins.

Therapeutic Strategies to Reduce the Toxicity of Misfolded Protein Oligomers

The aberrant aggregation of proteins is implicated in the onset and pathogenesis of a wide range of neurodegenerative disorders, including Alzheimer’s and Parkinson’s diseases. Mounting evidence indicates that misfolded protein oligomers produced as intermediates in the aggregation process are potent neurotoxic agents in these diseases. Because of the transient and heterogeneous nature of these elusive aggregates, however, it has proven challenging to develop therapeutics that can effectively target them. Here, we review approaches aimed at reducing oligomer toxicity, including (1) modulating the oligomer populations (e.g., by altering the kinetics of aggregation by inhibiting, enhancing, or redirecting the process), (2) modulating the oligomer properties (e.g., through the size–hydrophobicity–toxicity relationship), (3) modulating the oligomer interactions (e.g., by protecting cell membranes by displacing oligomers), and (4) reducing oligomer toxicity by potentiating the protein homeostasis system. We analyze examples of these complementary approaches, which may lead to the development of compounds capable of preventing or treating neurodegenerative disorders associated with protein aggregation.