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

Virus-like particles of retroviral origin in protein aggregation and neurodegenerative diseases

A wide range of human diseases are associated with protein misfolding and amyloid aggregates. Recent studies suggest that in certain neurological disorders, including Amyotrophic Lateral Sclerosis (ALS), Frontotemporal Dementia (FTD) and various tauopathies, protein aggregation may be promoted by virus-like particles (VLPs) formed by endogenous retroviruses (ERVs). The molecular mechanisms by which these VLPs contribute to protein aggregation, however, remain enigmatic. Here, we discuss possible molecular mechanisms of ERV-derived VLPs in the formation and spread of protein aggregates. An intriguing possibility is that liquid-like condensates may facilitate the formation of both protein aggregates and ERV-derived VLPs. We also describe how RNA chaperoning, and the encapsulation and trafficking of misfolded proteins, may contribute to protein homeostasis through the elimination of protein aggregates from cells. Based on these insights, we discuss future potential therapeutic opportunities.

The thermodynamic hypothesis of protein aggregation

Protein misfolding and aggregation drive some of the most prevalent and lethal disorders of our time, including Alzheimer's and Parkinson's diseases, now affecting tens of millions of people worldwide. The complexity of these diseases, which are often multifactorial and related to age and lifestyle, has made it challenging to identify the causes of the accumulation of aberrant protein deposits. An insight into the origins of these deposits comes from reports of a widespread presence of protein aggregates even under normal cellular conditions. This observation is best accounted for by the thermodynamic hypothesis of protein aggregation. According to this hypothesis, many proteins are expressed at levels close to their supersaturation limits, so that their native states are metastable against aggregation. Here we integrate the evidence behind this hypothesis and outline actionable therapeutic strategies that could halt protein aggregation at its source.

Kinetic Steering of Amyloid Formation and Polymorphism by Canagliflozin, a Type-2 Diabetes Drug

Amyloid formation is involved in widespread health conditions such as Alzheimer's disease, Parkinson's disease, and type-2 diabetes. Amyloid fibrils have a similar cross-β architecture, but fibrils formed by a single protein sequence can have diverse structures, varying with time, self-assembly conditions, and sequence modifications. Fibril structure has been proposed to be diagnostic of disease, but why different structures result under different conditions, especially in vitro, remains elusive. We previously identified a small molecule, YX-I-1, which inhibits in vitro amyloid formation by islet amyloid polypeptide (IAPP), a peptide hormone whose amyloid formation is involved in type-2 diabetes. Here, using YX-I-1 as a lead, we identified regulator-approved drugs with similar structures by chemical similarity analysis and substructure searches and monitored the effect of 24 of these potential ligands on IAPP amyloid assembly in vitro. We show that one such compound, canagliflozin (Invokana), a type-2 diabetes drug already in clinical use, can strongly delay the kinetics of IAPP amyloid formation, an activity independent of its intended mode of action [sodium-glucose linked transporter 2 (SGLT2) inhibitor] that may have important therapeutic implications. Combining analysis of amyloid self-assembly kinetics, biophysical characterization of monomer and fibril binding, and cryo-EM of the assembly products, we show that YX-I-1 and canagliflozin target IAPP early in aggregation, remodeling the energy landscape of primary nucleation and profoundly altering the resulting fibril structures. Early binding events thus imprint long-lasting effects on the amyloid structures that form.

Gene delivery of SUMO1-derived peptide rescues neuronal degeneration and motor deficits in a mouse model of Parkinson's disease

Developing α-synuclein aggregation inhibitors is challenging because its aggregation process involves several microscopic steps and heterogeneous intermediates. Previously, we identified a SUMO1-derived peptide, SUMO1(15-55), that exhibits tight binding to monomeric α-synuclein via SUMO-SUMO-interacting motif (SIM) interactions, and effectively blocks the initiation of aggregation and formation of toxic aggregates in vitro. In cellular and Drosophila models, SUMO1(15-55) was efficacious in protecting neuronal cells from α-synuclein-induced neurotoxicity and neuronal degeneration. Given the demonstrated ability of SUMO1(15-55) to sequester α-synuclein monomers thereby blocking oligomer formation, we sought to evaluate whether it could be equally effective against the aggregation-prone familial mutant α-synuclein-A53T. Herein, we show that SUMO1(15-55) selectively binds to monomeric α-synuclein-A53T, inhibits primary nucleation, and prevents the formation of structured protofibrils in vitro, thereby protecting neuronal cells from protofibril-induced cell death. We further demonstrate that larval feeding of a designed His10-SUMO1(15-55) that exhibits enhanced sub-stoichiometric suppression of α-synuclein-A53T aggregation in vitro can ameliorate Parkinson's disease (PD)-related symptoms in α-synuclein-A53T transgenic Drosophila models, while its rAAV-mediated gene delivery can relieve the PD-related histological and behavioral deficiencies in an rAAV-α-synuclein-A53T mouse PD model. Our findings suggest that gene delivery of His10-SUMO1(15-55) may serve as a clinical therapy for a spectrum of α-synuclein-aggregation associated synucleinopathies.

Evidence of α-Synuclein/Glucocerebrosidase Dual Targeting by Iminosugar Derivatives

Intrinsically disordered proteins (IDPs) are highly flexible molecules often linked to the onset of incurable diseases. Despite their great therapeutic potential, IDPs are often considered as undruggable because they lack defined binding pockets, which constitute the basis of drug discovery approaches. However, small molecules that interact with the intrinsically disordered state of α-synuclein, the protein linked to Parkinson's disease (PD), were recently identified and shown to act as chemical chaperones. Glucocerebrosidase (GCase) is an enzyme crucially involved in PD, since mutations that code for GCase are among the most frequent genetic risk factors for PD. Following the "dual-target" approach, stating that one carefully designed molecule can, in principle, interfere with more than one target, we identified a pharmacological chaperone for GCase that interacts with the intrinsically disordered monomeric form of α-synuclein. This result opens novel avenues to be explored in the search for molecules that act on dual targets, in particular, with challenging targets such as IDPs.

Current amyloid inhibitors: Therapeutic applications and nanomaterial-based innovations

Amyloid proteins have long been in the spotlight for being involved in many degenerative diseases including Alzheimer´s, Parkinson´s or type 2 diabetes, which currently cannot be prevented and for which there is no effective treatment or cure. Here we provide a comprehensive review of inhibitors that act directly on the amyloidogenic pathway (at the monomer, oligomer or fibril level) of key pathological amyloids, focusing on the most representative amyloid-related diseases. We discuss the latest advances in preclinical and clinical trials, focusing on cutting-edge developments, particularly on nanomaterials-based inhibitors, which offer unprecedented opportunities to address the complexity of protein misfolding disorders and are revolutionizing the landscape of anti-amyloid therapeutics. Notably, nanomaterials are impacting critical areas such as bioavailability, penetrability and functionality of compounds currently used in biomedicine, paving the way for more specific therapeutic solutions tailored to various amyloid-related diseases. Finally, we highlight the window of opportunity opened by comparative analysis with so-called functional amyloids for the development of innovative therapeutic approaches for these devastating diseases.

The Use of Natural Volatile Compounds on the Fibrillation Domain of Amyloid Beta (GSNKGAIIGLM)─Towards Promising Agents to Combat Alzheimer's Disease

Alzheimer's disease (AD), which is caused by the accumulation of amyloid-beta, is a major medical concern today. Controlling these aggregates is critical to drug development, but delivering them effectively into the bloodstream poses significant challenges. In this context, aromatherapy has been proposed as an innovative and promising approach for AD disease. The volatile compounds cinnamaldehyde, phenylethyl alcohol, α-asarone, and β-caryophyllene have neuroprotective effects that can be effective in the treatment of neurodegenerative diseases like AD. The amyloid-beta (Aβ) fragment (25-35), which retains the properties of the full-length Aβ is used as a suitable model to evaluate the potential toxicity associated with AD. This study investigated the effects of the four mentioned volatile compounds at four different concentrations on the fibrillation process of the Aβ (25-35) peptide. Structural changes in the peptide have been analyzed using various techniques such as fluorescence probing, far-UV circular dichroism spectroscopy (CD), and atomic force microscopy (AFM). Fluorescence probing results showed that these compounds can effectively prevent the formation of amyloid fibrils by forming chemical bonds with the intermediate species. CD spectroscopy results indicated a decrease in β-sheet content of fibrils and confirmed the effect of pH on structural changes. AFM analysis revealed that volatile compounds effectively prevented the formation of amyloid fibrils at different concentrations and changed the average size of intermediates and oligomeric species. These findings show a promising future for AD patients and emphasize the importance of natural compounds in the treatment and prevention of neurodegenerative diseases.

Uncaria rhynchophylla alkaloid extract exerts neuroprotective activity against Parkinson's disease via activating mitophagy with the involvement of UCHL1

ETHNOPHARMACOLOGICAL RELEVANCE

Uncaria rhynchophylla (Miq.) Miq. ex Havil. (UR), a traditional Chinese medicinal plant, plays an active role in neuroprotection. Clinical medication and modern pharmacological studies have proved the efficacy of UR against Parkinson's disease (PD), with alkaloids being recognized as the main bioactive components. But the therapeutic effect and mechanism of U. rhynchophylla alkaloid extract (URA) against PD need further exploration.

AIM OF STUDY

The study aimed to investigate the therapeutic effect and potential mechanism of URA on PD.

MATERIALS AND METHODS

LC-MS methodology was used to evaluate the chemical constituents of URA. The anti-PD activity of URA in vivo was measured on the mouse and rat models of PD. Neuroprotective effect of URA on PC12 cells was measured by MTT assay. Dopamine (DA) and its metabolites were detected by LC-MS for probing the protection ability on dopaminergic neurons. The differentially expressed proteins between model group and URA administrated group were analyzed by proteomics, suggesting oxidative phosphorylation as possible pathway of URA. Considering the critical role of mitochondria in oxidative phosphorylation, JC-1 staining, MitoSOX staining, transmission electron microscopy (TEM) observation and adenosine triphosphate (ATP) levels detection were used to analyze the effects of URA on mitochondrial morphology and function. Biolayer interferometry (BLI) was used to search for the possible UCHL1-bonding compounds in URA.

RESULTS

URA significantly mitigated the behavioural defects by improving coordination, shortening the time to climb down the whole pole (T-LA) and increasing the forelimbs' muscle strength of MPTP-induced PD mice and 6-OHDA-induced PD rats. In addition, URA improved tyrosine hydroxylase expression in dopaminergic neurons by immunohistochemistry (IHC) staining, and thus increased the neurotransmitter levels of DA and relevant metabolites. Furthermore, URA promoted mitophagy as reflected by a significant decrease in reactive oxygen species (ROS) generation, an increase in ATP levels and clearance of damaged mitochondria. Subsequently, Ubiquitin C-terminal hydrolase 1 (UCHL1), which is associated with the mitochondrial dysfunction in PD, is suggested to be a promising target based on the proteomics result, and proved by the blocked protective effects of URA by UCHL1 inhibitor. Furthermore, hirsuteine (HTE) was identified as a potential active compound of URA binding to UCHL1 by BLI, and the binding capacity and site were verified by surface plasmon resonance (SPR) and molecular docking.

CONCLUSION

This work demonstrates that URA exerts effective neuroprotective activity against PD via activation of mitophagy with the involvement of UCHL1, and HTE may be a potential active compound of URA.

Flexibility in PAM recognition expands DNA targeting in xCas9

xCas9 is an evolved variant of the CRISPR-Cas9 genome editing system, engineered to improve specificity and reduce undesired off-target effects. How xCas9 expands the DNA targeting capability of Cas9 by recognising a series of alternative protospacer adjacent motif (PAM) sequences while ignoring others is unknown. Here, we elucidate the molecular mechanism underlying xCas9's expanded PAM recognition and provide critical insights for expanding DNA targeting. We demonstrate that while wild-type Cas9 enforces stringent guanine selection through the rigidity of its interacting arginine dyad, xCas9 introduces flexibility in R1335, enabling selective recognition of specific PAM sequences. This increased flexibility confers a pronounced entropic preference, which also improves recognition of the canonical TGG PAM. Furthermore, xCas9 enhances DNA binding to alternative PAM sequences during the early evolution cycles, while favouring binding to the canonical PAM in the final evolution cycle. This dual functionality highlights how xCas9 broadens PAM recognition and underscores the importance of fine-tuning the flexibility of the PAM-interacting cleft as a key strategy for expanding the DNA targeting potential of CRISPR-Cas systems. These findings deepen our understanding of DNA recognition in xCas9 and may apply to other CRISPR-Cas systems with similar PAM recognition requirements.

Ensemble docking for intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are implicated in many human diseases and are increasingly being pursued as drug targets. Conventional structure-based drug design methods that rely on well-defined binding sites are however, largely unsuitable for IDPs. Here, we present computationally efficient ensemble docking approaches to predict the relative affinities of small molecules to IDPs and characterize their dynamic, heterogenous binding mechanisms at atomic resolution. We demonstrate that these ensemble docking protocols accurately predict the relative binding affinities of small molecule α-synuclein ligands measured by NMR spectroscopy and generate conformational ensembles of ligand binding modes in remarkable agreement with experimentally validated long-timescale molecular dynamics simulations. Our results display the potential of ensemble docking approaches for predicting small molecule binding to IDPs and suggest that these methods may be valuable tools for IDP drug discovery campaigns.

Transient interactions between the fuzzy coat and the cross-β core of brain-derived Aβ42 filaments

Several human disorders, including Alzheimer's disease (AD), are characterized by the aberrant formation of amyloid fibrils. In many cases, the amyloid core is flanked by disordered regions, known as fuzzy coat. The structural properties of fuzzy coats, and their interactions with their environments, however, have not been fully described to date. Here, we generate conformational ensembles of two brain-derived amyloid filaments of Aβ42, corresponding respectively to the familial and sporadic forms of AD. Our approach, called metadynamic electron microscopy metainference (MEMMI), provides a characterization of the transient interactions between the fuzzy coat and the cross-β core of the filaments. These calculations indicate that the familial AD filaments are less soluble than the sporadic AD filaments, and that the fuzzy coat contributes to solubilizing both types of filament. These results illustrate how the metainference approach can help analyze cryo-EM maps for the characterization of the properties of amyloid fibrils.

Estimation of Ligand Binding Free Energy Using Multi-eGO

The computational study of ligand binding to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of in silico drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by thermodynamic integration, and to probe binding mechanisms, including the description of protein conformational dynamics. The advantages of MD come at a high computational cost, which limits its use. Such cost could be reduced by using coarse-grained models, but their use is generally associated with an undesirable loss of resolution and accuracy. To address the trade-off between speed and accuracy of MD simulations, we describe the use of the recently introduced multi-eGO atomic model for the estimation of binding free energies. We illustrate this approach in the case of the binding of benzene to lysozyme by both thermodynamic integration and metadynamics, showing multiple binding/unbinding pathways of benzene. We then provide equally accurate results for the binding free energy of dasatinib and PP1 to Src kinase by thermodynamic integration. Finally, we show how we can describe the binding of the small molecule 10074-G5 to Aβ42 by single molecule simulations and by explicit titration of the ligand as a function of concentration. These results demonstrate that multi-eGO has the potential to significantly reduce the cost of accurate binding free energy calculations and can be used to develop and benchmark in silico ligand binding techniques.

Flexibility in PAM Recognition Expands DNA Targeting in xCas9

xCas9 is an evolved variant of the CRISPR-Cas9 genome editing system, engineered to improve specificity and reduce undesired off-target effects. How xCas9 expands the DNA targeting capability of Cas9 by recognizing a series of alternative Protospacer Adjacent Motif (PAM) sequences while ignoring others is unknown. Here, we elucidate the molecular mechanism underlying xCas9's expanded PAM recognition and provide critical insights for expanding DNA targeting. We demonstrate that while wild-type Cas9 enforces stringent guanine selection through the rigidity of its interacting arginine dyad, xCas9 introduces flexibility in R1335, enabling selective recognition of specific PAM sequences. This increased flexibility confers a pronounced entropic preference, which also improves recognition of the canonical TGG PAM. Furthermore, xCas9 enhances DNA binding to alternative PAM sequences during the early evolution cycles, while favouring binding to the canonical PAM in the final evolution cycle. This dual functionality highlights how xCas9 broadens PAM recognition and underscores the importance of fine-tuning the flexibility of the PAM-interacting cleft as a key strategy for expanding the DNA targeting potential of CRISPR-Cas systems. These findings deepen our understanding of DNA recognition in xCas9 and may apply to other CRISPR-Cas systems with similar PAM recognition requirements.

Cutting-edge Strategies for Overcoming Therapeutic Barriers in Alzheimer's Disease

Alzheimer's disease (AD) remains one of the hardest neurodegenerative diseases to treat due to its enduring cognitive deterioration and memory loss. Despite extensive research, few viable treatment approaches have been found; these are mostly due to several barriers, such as the disease's complex biology, limited pharmaceutical efficacy, and the BBB. This presentation discusses current strategies for addressing these therapeutic barriers to enhance AD treatment. Innovative drug delivery methods including liposomes, exosomes, and nanoparticles may be able to pass the blood-brain barrier and allow medicine to enter specific brain regions. These innovative strategies of medicine distribution reduce systemic side effects by improving absorption. Moreover, the development of disease-modifying treatments that target tau protein tangles, amyloid-beta plaques, and neuroinflammation offers the chance to influence the course of the illness rather than only treat its symptoms. Furthermore, gene therapy and CRISPR-Cas9 technologies have surfaced as potentially groundbreaking methods for addressing the underlying genetic defects associated with AD. Furthermore, novel approaches to patient care may involve the utilization of existing medications having neuroprotective properties, such as those for diabetes and cardiovascular conditions. Furthermore, biomarker research and personalized medicine have made individualized therapy approaches possible, ensuring that patients receive the best care possible based on their unique genetic and molecular profiles.

Probing the Conformational Ensemble of the Amyloid Beta 16-22 Fragment with Parallel-Bias Metadynamics

Aβ(16-22) is a segment of the Alzheimer's-related β-amyloid peptide that plays a crucial role in its aggregation. This study applies well-tempered parallel-bias metadynamics to investigate the impact of several denaturants and osmolytes on the conformational ensembles of both termini-capped and uncapped Aβ(16-22) monomers. Comparison of the different sets of collective variables in the metadynamics bias shows that using the set of backbone torsional angles results in better and faster convergence of simulations than employing more general structural characteristics of the short peptide. The equilibrium conformational ensembles of the peptides are characterized in pure water and in the presence of TMAO, urea, guanidinium chloride, and trifluoroethanol. In particular, trifluoroethanol and TMAO are found to increase the population of compact peptide conformations, whereas urea and guanidinium chloride favor extended structures. The analysis of the free energy surfaces in the presence of various substances with a comparison of the behavior of the capped and uncapped peptide forms reveals the role of different types of intrapeptide interactions such as salt bridges, hydrophobic contacts, and hydrogen bonds in stabilization of the compact or extended structures. As compounds reducing the abundance of the compact states of Aβ(16-22) and other disordered peptides are likely to suppress their amyloid fibril formation, simulations in the systems with this short peptide may be useful for the virtual screening of such compounds.

An integrated machine learning approach delineates an entropic expansion mechanism for the binding of a small molecule to α-synuclein

The mis-folding and aggregation of intrinsically disordered proteins (IDPs) such as α-synuclein (αS) underlie the pathogenesis of various neurodegenerative disorders. However, targeting αS with small molecules faces challenges due to the lack of defined ligand-binding pockets in its disordered structure. Here, we implement a deep artificial neural network-based machine learning approach, which is able to statistically distinguish the fuzzy ensemble of conformational substates of αS in neat water from those in aqueous fasudil (small molecule of interest) solution. In particular, the presence of fasudil in the solvent either modulates pre-existing states of αS or gives rise to new conformational states of αS, akin to an ensemble-expansion mechanism. The ensembles display strong conformation-dependence in residue-wise interaction with the small molecule. A thermodynamic analysis indicates that small-molecule modulates the structural repertoire of αS by tuning protein backbone entropy, however entropy of the water remains unperturbed. Together, this study sheds light on the intricate interplay between small molecules and IDPs, offering insights into entropic modulation and ensemble expansion as key biophysical mechanisms driving potential therapeutics.

Stereochemistry in the disorder-order continuum of protein interactions

Intrinsically disordered proteins can bind via the formation of highly disordered protein complexes without the formation of three-dimensional structure1. Most naturally occurring proteins are levorotatory (L)-that is, made up only of L-amino acids-imprinting molecular structure and communication with stereochemistry2. By contrast, their mirror-image dextrorotatory (D)-amino acids are rare in nature. Whether disordered protein complexes are truly independent of chiral constraints is not clear. Here, to investigate the chiral constraints of disordered protein-protein interactions, we chose as representative examples a set of five interacting protein pairs covering the disorder-order continuum. By observing the natural ligands and their stereochemical mirror images in free and bound states, we found that chirality was inconsequential in a fully disordered complex. However, if the interaction relied on the ligand undergoing extensive coupled folding and binding, correct stereochemistry was essential. Between these extremes, binding could be observed for the D-ligand with a strength that correlated with disorder in the final complex. These findings have important implications for our understanding of the molecular processes that lead to complex formation, the use of D-peptides in drug discovery and the chemistry of protein evolution of the first living entities on Earth.

Dimerization of the Aβ42 under the Influence of the Gold Nanoparticle: A REMD Study

Advances in Alzheimer's disease (AD) are related to the oligomerization of Amyloid β (Aβ) peptides. Therefore, alteration of the process can prevent AD. We investigated the Aβ42 dimerization under the effects of gold nanoparticles using temperature replica-exchange molecular dynamics (REMD) simulations. The structural change of dimers in the presence and absence of the gold nanoparticle, Au55, was monitored over stable intervals. Physical insights into the oligomerization of Aβ were thus clarified. The computed metrics indicate that Au55 affects the progress of oligomerization. Specifically, the presence of the gold nanoparticle significantly modifies the structure of dimeric Aβ42. The β-content experienced a substantial decrease with the induction of Au55. The turn and coil-contents are also decreased under the effects of the gold nanoparticle. However, the α-content of the dimer exhibited a rigid increase. The influence of gold nanoparticles on the dimeric Aβ42 differs significantly from that of silver nanoparticles, which reduce β-content but increase coil-, turn-, and α-contents. The nature of inhibition will be discussed, in which the vdW interaction plays a driving force for the interaction between the Aβ42 dimer and the gold nanoparticle.

Determining accurate conformational ensembles of intrinsically disordered proteins at atomic resolution

Determining accurate atomic resolution conformational ensembles of intrinsically disordered proteins (IDPs) is extremely challenging. Molecular dynamics (MD) simulations provide atomistic conformational ensembles of IDPs, but their accuracy is highly dependent on the quality of physical models, or force fields, used. Here, we demonstrate how to determine accurate atomic resolution conformational ensembles of IDPs by integrating all-atom MD simulations with experimental data from nuclear magnetic resonance (NMR) spectroscopy and small-angle x-ray scattering (SAXS) with a simple, robust and fully automated maximum entropy reweighting procedure. We demonstrate that when this approach is applied with sufficient experimental data, IDP ensembles derived from different MD force fields converge to highly similar conformational distributions. The maximum entropy reweighting procedure presented here facilitates the integration of MD simulations with extensive experimental datasets and enables the calculation of accurate, force-field independent atomic resolution conformational ensembles of IDPs.

Covalent adducts formed by the androgen receptor transactivation domain and small molecule drugs remain disordered

Intrinsically disordered proteins are implicated in many human diseases. Small molecules that target the disordered androgen receptor transactivation domain have entered human trials for the treatment of castration-resistant prostate cancer. These molecules have been shown to react with cysteine residues of the androgen receptor transactivation domain and form covalent adducts under physiological conditions. It is currently unclear how covalent attachment of these molecules alters the conformational ensemble of the androgen receptor. Here, we utilize all-atom molecular dynamics computer simulations to simulate covalent adducts of the small molecule ligands EPI-002 and EPI-7170 bound to the disordered androgen receptor transactivation domain. Our simulations reveal that the conformational ensembles of androgen receptor transactivation domain covalent adducts are heterogeneous and disordered. We find that covalent attachment of EPI-002 and EPI-7170 increases the population of collapsed helical transactivation domain conformations relative to the populations observed in non-covalent binding simulations and we identify networks of protein-ligand interactions that stabilize collapsed conformations in covalent adduct ensembles. We compare the populations of protein-ligand interactions observed in covalent adduct ensembles to those observed in non-covalent ligand-bound ensembles and find substantial differences. Our results provide atomically detailed descriptions of covalent adducts formed by small molecules and an intrinsically disordered protein and suggest strategies for developing more potent covalent inhibitors of intrinsically disordered proteins.

Comparison of Methodologies for Absolute Binding Free Energy Calculations of Ligands to Intrinsically Disordered Proteins

Modulating the function of Intrinsically Disordered Proteins (IDPs) with small molecules is of considerable importance given the crucial roles of IDPs in the pathophysiology of numerous diseases. Reported binding affinities for ligands to diverse IDPs vary broadly, and little is known about the detailed molecular mechanisms that underpin ligand efficacy. Molecular simulations of IDP ligand binding mechanisms can help us understand the mode of action of small molecule inhibitors of IDP function, but it is still unclear how binding energies can be modeled rigorously for such a flexible class of proteins. Here, we compare alchemical absolute binding free energy calculations (ABFE) and Markov-State Modeling (MSM) protocols to model the binding of the small molecule 10058-F4 to a disordered peptide extracted from a segment of the oncoprotein c-Myc. The ABFE results produce binding energy estimates that are sensitive to the choice of reference structure. In contrast, the MSM results produce more reproducible binding energy estimates consistent with weak mM binding affinities and transient intermolecular contacts reported in the literature.

An integrative characterization of proline cis and trans conformers in a disordered peptide

Intrinsically disordered proteins (IDPs) often contain proline residues that undergo cis/trans isomerization. While molecular dynamics (MD) simulations have the potential to fully characterize the proline cis and trans subensembles, they are limited by the slow timescales of isomerization and force field inaccuracies. NMR spectroscopy can report on ensemble-averaged observables for both the cis-proline and trans-proline states, but a full atomistic characterization of these conformers is challenging. Given the importance of proline cis/trans isomerization for influencing the conformational sampling of disordered proteins, we employed a combination of all-atom MD simulations with enhanced sampling (metadynamics), NMR, and small-angle x-ray scattering (SAXS) to characterize the two subensembles of the ORF6 C-terminal region (ORF6CTR) from SARS-CoV-2 corresponding to the proline-57 (P57) cis and trans states. We performed MD simulations in three distinct force fields: AMBER03ws, AMBER99SB-disp, and CHARMM36m, which are all optimized for disordered proteins. Each simulation was run for an accumulated time of 180-220 μs until convergence was reached, as assessed by blocking analysis. A good agreement between the cis-P57 populations predicted from metadynamic simulations in AMBER03ws was observed with populations obtained from experimental NMR data. Moreover, we observed good agreement between the radius of gyration predicted from the metadynamic simulations in AMBER03ws and that measured using SAXS. Our findings suggest that both the cis-P57 and trans-P57 conformations of ORF6CTR are extremely dynamic and that interdisciplinary approaches combining both multiscale computations and experiments offer avenues to explore highly dynamic states that cannot be reliably characterized by either approach in isolation.

NMR studies of amyloid interactions

Amyloid fibrils are insoluble, fibrous nanostructures that accumulate extracellularly in biological tissue during the progression of several human disorders, including Alzheimer's disease (AD) and type 2 diabetes. Fibrils are assembled from protein monomers via the transient formation of soluble, cytotoxic oligomers, and have a common molecular architecture consisting of a spinal core of hydrogen-bonded protein β-strands. For the past 25 years, NMR spectroscopy has been at the forefront of research into the structure and assembly mechanisms of amyloid aggregates. Until the recent boom in fibril structure analysis by cryo-electron microscopy, solid-state NMR was unrivalled in its ability to provide atomic-level models of amyloid fibril architecture. Solution-state NMR has also provided complementary information on the early stages in the amyloid assembly mechanism. Now, both NMR modalities are proving to be valuable in unravelling the complex interactions between amyloid species and a diverse range of physiological metal ions, molecules and surfaces that influence the assembly pathway, kinetics, morphology and clearance in vivo. Here, an overview is presented of the main applications of solid-state and solution-state NMR for studying the interactions between amyloid proteins and biomembranes, glycosaminoglycan polysaccharides, metal ions, polyphenols, synthetic therapeutics and diagnostics. Key NMR methodology is reviewed along with examples of how to overcome the challenges of detecting interactions with aggregating proteins. The review heralds this new role for NMR in providing a comprehensive and pathologically-relevant view of the interactions between protein and non-protein components of amyloid. Coverage of both solid- and solution-state NMR methods and applications herein will be informative and valuable to the broad communities that are interested in amyloid proteins.

How to drug a cloud? Targeting intrinsically disordered proteins

Biologically active proteins/regions without stable structure (i.e., intrinsically disordered proteins and regions (IDPs and IDRs)) are commonly found in all proteomes. They have a unique functional repertoire that complements the functionalities of ordered proteins and domains. IDPs/IDRs are multifunctional promiscuous binders capable of folding at interaction with specific binding partners on a template- or context-dependent manner, many of which undergo liquid-liquid phase separation, leading to the formation of membrane-less organelles and biomolecular condensates. Many of them are frequently related to the pathogenesis of various human diseases. All this defines IDPs/IDRs as attractive targets for the development of novel drugs. However, their lack of unique structures, multifunctionality, binding promiscuity, and involvement in unusual modes of action preclude direct use of traditional structure-based drug design approaches for targeting IDPs/IDRs, and make disorder-based drug discovery for these "protein clouds" challenging. Despite all these complexities there is continuing progress in the design of small molecules affecting IDPs/IDRs. This article describes the major structural features of IDPs/IDRs and the peculiarities of the disorder-based functionality. It also discusses the roles of IDPs/IDRs in various pathologies, and shows why the approaches elaborated for finding drugs targeting ordered proteins cannot be directly used for the intrinsic disorder-based drug design, and introduces some novel methodologies suitable for these purposes. Finally, it emphasizes that regardless of their multifunctionality, binding promiscuity, lack of unique structures, and highly dynamic nature, "protein clouds" are principally druggable. Significance Statement Intrinsically disordered proteins and regions are highly abundant in nature, have multiple important biological functions, are commonly involved in the pathogenesis of a multitude of human diseases, and are therefore considered as very attractive drug targets. Although dealing with these unstructured multifunctional protein/regions is a challenging task, multiple innovative approaches have been designed to target them by small molecules.

A Cationic Zn-Phthalocyanine Turns Alzheimer's Amyloid β Aggregates into Non-Toxic Oligomers and Inhibits Neurotoxicity in Culture

Amyloid β peptide (Aβ) aggregation and deposition are considered the main causes of Alzheimer's disease. In a previous study, we demonstrated that anionic Zn-phthalocyanine (ZnPc) can interact with the Aβ peptide and inhibit the fibril-formation process. However, due to the inability of anionic ZnPc to cross the intact blood-brain barrier, we decided to explore the interaction of cationic methylated Zn-phthalocyanine (cZnPc) with the peptide. Using a ThT fluorescence assay, we observed that cZnPc dose-dependently and time-dependently inhibited Aβ1-42 fibril levels under in vitro fibril-formation conditions. Electron microscopy revealed that it caused Aβ1-42 peptides to form small aggregates. Western blotting and dot immunoblot oligomer experiments demonstrated that cZnPc increased rather than decreased the levels of oligomers from the very early stages of incubation. A binding assay confirmed that cZnPc could bind with the peptide. Docking simulations indicated that the oligomer species of Aβ1-42 had a higher ability to interact with cZnPc. ANS fluorescence assay results indicated that cZnPc did not affect the hydrophobicity of the peptide. However, cZnPc significantly increased intrinsic tyrosine fluorescence of the peptide after 8 h of incubation in fibril-formation conditions. Importantly, cell culture experiments demonstrated that cZnPc did not exhibit any toxicity up to a concentration of 10 µM. Instead, it protected a neuronal cell line from Aβ1-42-induced toxicity. Thus, our results suggest that cZnPc can affect the aggregation process of Aβ1-42, rendering it non-toxic, which could be crucial for the therapy of Alzheimer's disease.

Predicting Conformational Ensembles of Intrinsically Disordered Proteins: From Molecular Dynamics to Machine Learning

Intrinsically disordered proteins and regions (IDP/IDRs) are ubiquitous across all domains of life. Characterized by a lack of a stable tertiary structure, IDP/IDRs populate a diverse set of transiently formed structural states that can promiscuously adapt upon binding with specific interaction partners and/or certain alterations in environmental conditions. This malleability is foundational for their role as tunable interaction hubs in core cellular processes such as signaling, transcription, and translation. Tracing the conformational ensemble of an IDP/IDR and its perturbation in response to regulatory cues is thus paramount for illuminating its function. However, the conformational heterogeneity of IDP/IDRs poses several challenges. Here, we review experimental and computational methods devised to disentangle the conformational landscape of IDP/IDRs, highlighting recent computational advances that permit proteome-wide scans of IDP/IDRs conformations. We briefly evaluate selected computational methods using the disordered N-terminal of the human copper transporter 1 as a test case and outline further challenges in IDP/IDRs ensemble prediction.

Molecular engineering of a theranostic molecule that detects Aβ plaques, inhibits Iowa and Dutch mutation Aβ self-aggregation and promotes lysosomal biogenesis for Alzheimer's disease

Extracellular clustering of amyloid-β (Aβ) and an impaired autophagy lysosomal pathway (ALP) are the hallmark features in the early stages of incurable Alzheimer's disease (AD). There is a pressing need to find or develop new small molecules for diagnostics and therapeutics for the early stages of AD. Herein, we report a small molecule, namely F-SLCOOH, which can bind and detect Aβ1-42, Iowa mutation Aβ, Dutch mutation Aβ fibrils and oligomers exhibiting enhanced emission with high affinity. Importantly, F-SLCOOH can readily pass through the blood-brain barrier and shows highly selective binding toward the extracellular Aβ aggregates in real-time in live animal imaging of a 5XFAD mice model. In addition, a high concentration of F-SLCOOH in both brain and plasma of wildtype mice after intraperitoneal administration was found. The ex vivo confocal imaging of hippocampal brain slices indicated excellent colocalization of F-SLCOOH with Aβ positive NU1, 4G8, 6E10 A11 antibodies and THS staining dye, affirming its excellent Aβ specificity and targetability. The molecular docking studies have provided insight into the unique and specific binding of F-SLCOOH with various Aβ species. Importantly, F-SLCOOH exhibits remarkable anti-fibrillation properties against toxic Aβ aggregate formation of Aβ1-42, Iowa mutation Aβ, and Dutch mutation Aβ. F-SLCOOH treatment also exerts high neuroprotective functions and promotes autophagy lysosomal biogenesis in neuronal AD cell models. In summary, the present results suggest that F-SLCOOH is a highly promising theranostic agent for diagnosis and therapeutics of AD.

Context-dependent, fuzzy protein interactions: Towards sequence-based insights

Predicting protein interactions in the cellular environment still remains a challenge in the AlphaFold era. Protein interactions, similarly to their structures, sample a continuum from ordered to disordered states, with specific partners in many bound configurations. A multiplicity of binding modes (MBM) enables transition between these states under different cellular conditions. This review focuses on how the cellular environment affects protein interactions, highlighting the molecular mechanisms, biophysical origin, and sequence-based principles of context-dependent, fuzzy interactions. It summarises experimental and computational approaches to address the challenge of interaction heterogeneity and its contribution to a wide range of biological functions. These insights will help in understanding complex cellular processes, involving conversions between protein assembly states, such as from liquid-like droplet state to the amyloid state.

Epitope-specific antibody fragments block aggregation of AGelD187N, an aberrant peptide in gelsolin amyloidosis

Aggregation of aberrant fragment of plasma gelsolin, AGelD187N, is a crucial event underlying the pathophysiology of Finnish gelsolin amyloidosis, an inherited form of systemic amyloidosis. The amyloidogenic gelsolin fragment AGelD187N does not play any physiological role in the body, unlike most aggregating proteins related to other protein misfolding diseases. However, no therapeutic agents that specifically and effectively target and neutralize AGelD187N exist. We used phage display technology to identify novel single-chain variable fragments that bind to different epitopes in the monomeric AGelD187N that were further maturated by variable domain shuffling and converted to antigen-binding fragment (Fab) antibodies. The generated antibody fragments had nanomolar binding affinity for full-length AGelD187N, as evaluated by biolayer interferometry. Importantly, all four Fabs selected for functional studies efficiently inhibited the amyloid formation of full-length AGelD187N as examined by thioflavin fluorescence assay and transmission electron microscopy. Two Fabs, neither of which bound to the previously proposed fibril-forming region of AGelD187N, completely blocked the amyloid formation of AGelD187N. Moreover, no small soluble aggregates, which are considered pathogenic species in protein misfolding diseases, were formed after successful inhibition of amyloid formation by the most promising aggregation inhibitor, as investigated by size-exclusion chromatography combined with multiangle light scattering. We conclude that all regions of the full-length AGelD187N are important in modulating its assembly into fibrils and that the discovered epitope-specific anti-AGelD187N antibody fragments provide a promising starting point for a disease-modifying therapy for gelsolin amyloidosis, which is currently lacking.

Amyloid formation and depolymerization of tumor suppressor p16INK4a are regulated by a thiol-dependent redox mechanism

The conversion of a soluble protein into polymeric amyloid structures is a process that is poorly understood. Here, we describe a fully redox-regulated amyloid system in which cysteine oxidation of the tumor suppressor protein p16INK4a leads to rapid amyloid formation. We identify a partially-structured disulfide-bonded dimeric intermediate species that subsequently assembles into fibrils. The stable amyloid structures disassemble when the disulfide bond is reduced. p16INK4a is frequently mutated in cancers and is considered highly vulnerable to single-point mutations. We find that multiple cancer-related mutations show increased amyloid formation propensity whereas mutations stabilizing the fold prevent transition into amyloid. The complex transition into amyloids and their structural stability is therefore strictly governed by redox reactions and a single regulatory disulfide bond.

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules

Computational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here, we developed a comparative Markov state analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer's disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting nonspecifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42 and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target biomolecules other than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.

Silver nanoparticles alter the dimerization of Aβ42 studied by REMD simulations

The aggregation of amyloid beta (Aβ) peptides is associated with the development of Alzheimer's disease (AD). However, there has been a growing belief that the oligomerization of Aβ species in different environments has a neurotoxic effect on the patient's brain, causing damage. It is necessary to comprehend the compositions of Aβ oligomers in order to develop medications that may effectively inhibit these neurotoxic forms that affect the nervous system of AD patients. Thus, dissociation or inhibition of Aβ aggregation may be able to prevent AD. To date, the search for traditional agents and biomolecules has largely been unsuccessful. In this context, nanoparticles have emerged as potential candidates to directly inhibit the formation of Aβ oligomers. The oligomerization of the dimeric Aβ peptides with or without the influence of a silver nanoparticle was thus investigated using temperature replica-exchange molecular dynamics (REMD) simulations. The physical insights into the dimeric Aβ oligomerization were clarified by analyzing intermolecular contact maps, the free energy landscape of the dimeric oligomer, secondary structure terms, etc. The difference in obtained metrics between Aβ with or without a silver nanoparticle provides a picture of the influence of silver nanoparticles on the oligomerization process. The underlying mechanisms that are involved in altering Aβ oligomerization will be discussed. The obtained results may play an important role in searching for Aβ inhibitor pathways.

In search of chemical rationales

Small molecules and drugs do not homogenously distribute across cells, enriching instead in distinct sub-cellular compartments and membrane-less biomolecular condensates. A new study lays out the path to identifying chemical features or “rationales” that confer condensate selective partitioning of small molecules.

Misfolded protein oligomers: mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases

The conversion of native peptides and proteins into amyloid aggregates is a hallmark of over 50 human disorders, including Alzheimer's and Parkinson's diseases. Increasing evidence implicates misfolded protein oligomers produced during the amyloid formation process as the primary cytotoxic agents in many of these devastating conditions. In this review, we analyze the processes by which oligomers are formed, their structures, physicochemical properties, population dynamics, and the mechanisms of their cytotoxicity. We then focus on drug discovery strategies that target the formation of oligomers and their ability to disrupt cell physiology and trigger degenerative processes.

Self-replication of Aβ42 aggregates occurs on small and isolated fibril sites

Self-replication of amyloid fibrils via secondary nucleation is an intriguing physicochemical phenomenon in which existing fibrils catalyze the formation of their own copies. The molecular events behind this fibril surface-mediated process remain largely inaccessible to current structural and imaging techniques. Using statistical mechanics, computer modeling, and chemical kinetics, we show that the catalytic structure of the fibril surface can be inferred from the aggregation behavior in the presence and absence of a fibril-binding inhibitor. We apply our approach to the case of Alzheimer's A[Formula: see text] amyloid fibrils formed in the presence of proSP-C Brichos inhibitors. We find that self-replication of A[Formula: see text] fibrils occurs on small catalytic sites on the fibril surface, which are far apart from each other, and each of which can be covered by a single Brichos inhibitor.

NU6300 covalently reacts with cysteine-191 of gasdermin D to block its cleavage and palmitoylation

Gasdermin D (GSDMD) serves as a vital mediator of inflammasome-driven pyroptosis. In our study, we have identified NU6300 as a specific GSDMD inhibitor that covalently interacts with cysteine-191 of GSDMD, effectively blocking its cleavage while not affecting earlier steps such as ASC oligomerization and caspase-1 processing in AIM2- and NLRC4-mediated inflammation. On the contrary, NU6300 robustly inhibits these earlier steps in NLRP3 inflammasome, confirming a unique feedback inhibition effect in the NLRP3-GSDMD pathway upon GSDMD targeting. Our study reveals a previously undefined mechanism of GSDMD inhibitors: NU6300 impairs the palmitoylation of both full-length and N-terminal GSDMD, impeding the membrane localization and oligomerization of N-terminal GSDMD. In vivo studies further demonstrate the efficacy of NU6300 in ameliorating dextran sodium sulfate-induced colitis and improving survival in lipopolysaccharide-induced sepsis. Overall, these findings highlight the potential of NU6300 as a promising lead compound for the treatment of inflammatory diseases.

Molecular simulations integrated with experiments for probing the interaction dynamics and binding mechanisms of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) exploit their plasticity to deploy a rich panoply of soft interactions and binding phenomena. Advances in tailoring molecular simulations for IDPs combined with experimental cross-validation offer an atomistic view of the mechanisms that control IDP binding, function, and dysfunction. The emerging theme is that unbound IDPs autonomously form transient local structures and self-interactions that determine their binding behavior. Recent results have shed light on whether and how IDPs fold, stay disordered or drive condensation upon binding; how they achieve binding specificity and select among competing partners. The disorder-binding paradigm is now being proactively used by researchers to target IDPs for rational drug design and engineer molecular responsive elements for biosensing applications.

Picosecond Dynamics of a Small Molecule in Its Bound State with an Intrinsically Disordered Protein

Intrinsically disordered proteins (IDPs) are highly dynamic biomolecules that rapidly interconvert among many structural conformations. These dynamic biomolecules are involved in cancers, neurodegeneration, cardiovascular illnesses, and viral infections. Despite their enormous therapeutic potential, IDPs have generally been considered undruggable because of their lack of classical long-lived binding pockets for small molecules. Currently, only a few instances are known where small molecules have been observed to interact with IDPs, and this situation is further exacerbated by the limited sensitivity of experimental techniques to detect such binding events. Here, using experimental nuclear magnetic resonance (NMR) spectroscopy 19F transverse spin-relaxation measurements, we discovered that a small molecule, 5-fluoroindole, interacts with the disordered domains of non-structural protein 5A from hepatitis C virus with a Kd of 260 ± 110 μM. Our analysis also allowed us to determine the rotational correlation times (τc) for the free and bound states of 5-fluoroindole. In the free state, we observed a rotational correlation time of 27.0 ± 1.3 ps, whereas in the bound state, τc only increased to 46 ± 10 ps. Our findings imply that it is possible for small molecules to engage with IDPs in exceptionally dynamic ways, in sharp contrast to the rigid binding modes typically exhibited when small molecules bind to well-defined binding pockets within structured proteins.

Transition Metal Ion FRET-Based Probe to Study Cu(II)-Mediated Amyloid- Ligand Binding

Recent therapeutic strategies suggest that small peptides can act as aggregation inhibitors of monomeric amyloid-β (Αβ) by inducing structural rearrangements upon complexation. However, characterizing the binding events in such dynamic and transient noncovalent complexes, especially in the presence of natively occurring metal ions, remains a challenge. Here, we deploy a combined transition metal ion Förster resonance energy transfer (tmFRET) and native ion mobility-mass spectrometry (IM-MS) approach to characterize the structure of mass- and charge-selected Aβ complexes with Cu(II) ions (a quencher) and a potential aggregation inhibitor, a small neuropeptide named leucine enkephalin (LE). We show conformational changes of monomeric Αβ species upon Cu(II)-binding, indicating an uncoiled N-terminus and a close interaction between the C-terminus and the central hydrophobic region. Furthermore, we introduce LE labeled at the N-terminus with a metal-chelating agent, nitrilotriacetic acid (NTA). This allows us to employ tmFRET to probe the binding even in low-abundance and transient Aβ-inhibitor-metal ion complexes. Complementary intramolecular distance and global shape information from tmFRET and native IM-MS, respectively, confirmed Cu(II) displacement toward the N-terminus of Αβ, which discloses the binding region and the inhibitor's orientation.

Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules

The electron microscopy metainference integrative structural biology method enables the combination of cryo-electron microscopy electron density maps with molecular modeling techniques such as molecular dynamics to unveil the atomistic biomolecular structural ensemble and the error in the map data in an efficient manner. Here we illustrate the electron microscopy metainference protocol and analysis used to elucidate the atomistic structural ensemble of the microtubule-associated protein tau bound to microtubules by using state-of-the-art molecular mechanic force field and the electron density map.

Conformational inhibitors of protein aggregation

Amyloidoses are fatal conditions associated with the aggregation of proteins into amyloid fibrils that deposit systemically and/or locally. Possibly because the causal mechanism of protein aggregation and deposition is not fully understood, this group of diseases remains uncurable. Advances in structural biology, such as the use of nuclear magnetic resonance and cryo-electron microscopy, have enabled the study of the structures and the conformational nature of the proteins whose aggregation is associated with the underlying pathogenesis of amyloidosis. As a result, the last years of research have translated into the development of directed therapeutic strategies that target the specific conformations of precursors, fibrils, and intermediary species. Current efforts include the use of small molecules, peptides, and antibodies. This review summarizes the recent progress in developing strategies that target specific protein conformations for the treatment of amyloidoses.

Conformational entropy in molecular recognition of intrinsically disordered proteins

Broad conformational ensembles make intrinsically disordered proteins or regions entropically intriguing. Although methodologically challenging and understudied, emerging studies into their changes in conformational entropy (ΔS°conf) upon complex formation have provided both quantitative and qualitative insight. Recent work based on thermodynamics from isothermal titration calorimetry and NMR spectroscopy uncovers an expanded repertoire of regulatory mechanisms, where ΔS°conf plays roles in partner selection, state behavior, functional buffering, allosteric regulation, and drug design. We highlight these mechanisms to display the large entropic reservoir of IDPs for the regulation of molecular communication. We call upon the field to make efforts to contribute to this insight as more studies are needed for forwarding mechanistic decoding of intrinsically disordered proteins and their complexes.

Understanding the Molecular Mechanisms of Polyphenol Inhibition of Amyloid β Aggregation

Alzheimer's disease (AD) is highly associated with self-aggregation of amyloid β (Aβ) proteins into fibrils. Inhibition of Aβ aggregation by polyphenols is one of the major therapeutic strategies for AD. Among them, four polyphenols (brazilin, resveratrol, hematoxylin, and rosmarinic acid) have been reported to be effective at inhibiting Aβ aggregation, but the inhibition mechanisms are still unclear. In this work, these four polyphenols were selected to explore their interactions with the Aβ17-42 pentamer by molecular dynamics simulation. All four polyphenols can bind to the pentamer tightly but prefer different binding sites. Conversion of the β-sheet to the random coil, fewer interchain hydrogen bonds, and weaker salt bridges were observed after binding. Interestingly, different Aβ17-42 pentamer destabilizing mechanisms for resveratrol and hematoxylin were found. Resveratrol inserts into the hydrophobic core of the pentamer by forming hydrogen bonds with Asp23 and Lys28, while hematoxylin prefers to bind beside chain A of the pentamer, which leads to β-sheet offset and dissociation of the β1 sheet of chain E. This work reveals the interactions between the Aβ17-42 pentamer and four polyphenols and discusses the relationship between inhibitor structures and their inhibition mechanisms, which also provides useful guidance for screening effective Aβ aggregation inhibitors and drug design against AD.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Development of 11 C-labeled CRANAD-102 for positron emission tomography imaging of soluble Aβ-species

CRANAD-102, a selective near-infrared fluorescent tracer targeting soluble amyloid-β (Aβ) species, has recently attracted attention due to its potential to be used as a diagnostic tool for early stages of Alzheimer's disease (AD). Development of a positron emission tomography (PET) tracer based on CRANAD-102 could as such allow to noninvasively study soluble and protofibrillar species of Aβ in humans. These soluble and protofibrillar species are thought to be responsible to cause AD. Within this work, we successfully 11 C-labeled CRANAD-102 via a Suzuki-Miyaura reaction in a RCС of 48 ± 9%, with a RCP of >96% and a molar activity (Am ) of 25 ± 7 GBq/μmol. Future studies have to be conducted to evaluate if [11 C]CRANAD-102 can be used to detect soluble protofibrils in vivo and if [11 C]CRANAD-102 can be used to detect AD earlier as possible with current diagnostics.

Defining the condensate landscape of fusion oncoproteins

Fusion oncoproteins (FOs) arise from chromosomal translocations in ~17% of cancers and are often oncogenic drivers. Although some FOs can promote oncogenesis by undergoing liquid-liquid phase separation (LLPS) to form aberrant biomolecular condensates, the generality of this phenomenon is unknown. We explored this question by testing 166 FOs in HeLa cells and found that 58% formed condensates. The condensate-forming FOs displayed physicochemical features distinct from those of condensate-negative FOs and segregated into distinct feature-based groups that aligned with their sub-cellular localization and biological function. Using Machine Learning, we developed a predictor of FO condensation behavior, and discovered that 67% of ~3000 additional FOs likely form condensates, with 35% of those predicted to function by altering gene expression. 47% of the predicted condensate-negative FOs were associated with cell signaling functions, suggesting a functional dichotomy between condensate-positive and -negative FOs. Our Datasets and reagents are rich resources to interrogate FO condensation in the future.

Phase separation and pathologic transitions of RNP condensates in neurons: implications for amyotrophic lateral sclerosis, frontotemporal dementia and other neurodegenerative disorders

Liquid-liquid phase separation results in the formation of dynamic biomolecular condensates, also known as membrane-less organelles, that allow for the assembly of functional compartments and higher order structures within cells. Multivalent, reversible interactions between RNA-binding proteins (RBPs), including FUS, TDP-43, and hnRNPA1, and/or RNA (e.g., RBP-RBP, RBP-RNA, RNA-RNA), result in the formation of ribonucleoprotein (RNP) condensates, which are critical for RNA processing, mRNA transport, stability, stress granule assembly, and translation. Stress granules, neuronal transport granules, and processing bodies are examples of cytoplasmic RNP condensates, while the nucleolus and Cajal bodies are representative nuclear RNP condensates. In neurons, RNP condensates promote long-range mRNA transport and local translation in the dendrites and axon, and are essential for spatiotemporal regulation of gene expression, axonal integrity and synaptic function. Mutations of RBPs and/or pathologic mislocalization and aggregation of RBPs are hallmarks of several neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease. ALS/FTD-linked mutations of RBPs alter the strength and reversibility of multivalent interactions with other RBPs and RNAs, resulting in aberrant phase transitions. These aberrant RNP condensates have detrimental functional consequences on mRNA stability, localization, and translation, and ultimately lead to compromised axonal integrity and synaptic function in disease. Pathogenic protein aggregation is dependent on various factors, and aberrant dynamically arrested RNP condensates may serve as an initial nucleation step for pathologic aggregate formation. Recent studies have focused on identifying mechanisms by which neurons resolve phase transitioned condensates to prevent the formation of pathogenic inclusions/aggregates. The present review focuses on the phase separation of neurodegenerative disease-linked RBPs, physiological functions of RNP condensates, and the pathologic role of aberrant phase transitions in neurodegenerative disease, particularly ALS/FTD. We also examine cellular mechanisms that contribute to the resolution of aberrant condensates in neurons, and potential therapeutic approaches to resolve aberrantly phase transitioned condensates at a molecular level.

Origin of stronger binding of ionic pair (IP) inhibitor to Aβ42 than the equimolar neutral counterparts: synergy mechanism of IP in disrupting Aβ42 protofibril and inhibiting Aβ42 aggregation under two pH conditions

Fibrous aggregates of beta-amyloid (Aβ) is a hallmark of Alzheimer's disease (AD). Several major strategies of drugs or inhibitors, including neutral molecules, positive or negative ions, and dual-inhibitor, are used to inhibit the misfolding or aggregation of Aβ42, among which a kind of dual-inhibitor composed of a pair of positive and negative ions is emerging as the most powerful candidate. This knowledge lacks the origin of the strong inhibitory effect and synergy mechanisms blocking the development and application of such inhibitors. To this end, we employed 1 : 1 ionic pairs (IP) of oppositely charged benzothiazole molecules (+)BAM1-EG6 (Pos) and (-)BAM1-EG6 (Neg) as well as equimolar neutral BAM1-EG6 (Neu) counterpart at two pH conditions (5.5 and 7.0) to bind Aβ42 targets, Aβ42 monomer (AβM), soluble pentamer (AβP), and pentameric protofibril (AβF) models, respectively, corresponding to the products of three toxic Aβ42 development pathways, lag, exponential and fibrillation phases. Simulated results illustrated the details of the inhibitory mechanisms of IP and Neu for the AβY (Y = M, P, or F) in the three different phases, characterizing the roles of Pos and Neg of IP as well as their charged, hydrophobic groups and linker playing in the synergistic interaction, and elucidated a previously unknown molecular mechanism governing the IP-Aβ42 interaction. Most importantly, we first revealed the origin of the stronger binding of IP inhibitors to Aβ42 than that of the equimolar neutral counterparts, observing a perplexing phenomenon that the physiological condition (pH = 7.0) than the acidic one (pH = 5.5) is more favorable to the enhancement of IP binding, and finally disclosed that solvation is responsible to the enhancement because at pH 7.0, AβP and AβF act as anionic membranes, where solvation plays a critical role in the chemoelectromechanics. The result not only provides a new dimension in dual-inhibitor/drug design and development but also a new perspective for uncovering charged protein disaggregation under IP-like inhibitors.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.