Aggregation Propensity Research Articles

Molecular dynamics simulations as a guide for modulating small molecule aggregation

Small colloidally aggregating molecules (SCAMs) can be problematic for biological assays in drug discovery campaigns. However, the self-associating properties of SCAMs have potential applications in drug delivery and analytical biochemistry. Consequently, the ability to predict the aggregation propensity of a small organic molecule is of considerable interest. Chemoinformatics-based filters such as ChemAGG and Aggregator Advisor offer rapid assessment but are limited by the assay quality and structural diversity of their training set data. Complementary to these tools, we explore here the ability of molecular dynamics (MD) simulations as a physics-based method capable of predicting the aggregation propensity of diverse chemical structures. For a set of 32 molecules, using simulations of 100 ns in explicit solvent, we find a success rate of 97% (one molecule misclassified) as opposed to 75% by Aggregator Advisor and 72% by ChemAGG. These short timescale MD simulations are representative of longer microsecond trajectories and yield an informative spectrum of aggregation propensities across the set of solutes, capturing the dynamic behaviour of weakly aggregating compounds. Implicit solvent simulations using the generalized Born model were less successful in predicting aggregation propensity. MD simulations were also performed to explore structure-aggregation relationships for selected molecules, identifying chemical modifications that reversed the predicted behaviour of a given aggregator/non-aggregator compound. While lower throughput than rapid cheminformatics-based SCAM filters, MD-based prediction of aggregation has potential to be deployed on the scale of focused subsets of moderate size, and, depending on the target application, provide guidance on removing or optimizing a compound’s aggregation propensity.Graphical

AGRAMP: machine learning models for predicting antimicrobial peptides against phytopathogenic bacteria.

Antimicrobial peptides (AMPs) are promising alternatives to traditional antibiotics for combating plant pathogenic bacteria in agriculture and the environment. However, identifying potent AMPs through laborious experimental assays is resource-intensive and time-consuming. To address these limitations, this study presents a bioinformatics approach utilizing machine learning models for predicting and selecting AMPs active against plant pathogenic bacteria. N-gram representations of peptide sequences with 3-letter and 9-letter reduced amino acid alphabets were used to capture the sequence patterns and motifs that contribute to the antimicrobial activity of AMPs. A 5-fold cross-validation technique was used to train the machine learning models and to evaluate their predictive accuracy and robustness. The models were applied to predict putative AMPs encoded by intergenic regions and small open reading frames (ORFs) of the citrus genome. Approximately 7% of the 10,000-peptide dataset from the intergenic region and 7% of the 685,924-peptide dataset from the whole genome were predicted as probable AMPs. The prediction accuracy of the reported models range from 0.72 to 0.91. A subset of the predicted AMPs was selected for experimental test against Spiroplasma citri, the causative agent of citrus stubborn disease. The experimental results confirm the antimicrobial activity of the selected AMPs against the target bacterium, demonstrating the predictive capability of the machine learning models. Hydrophobic amino acid residues and positively charged amino acid residues are among the key features in predicting AMPs by the Random Forest Algorithm. Aggregation propensity appears to be correlated with the effectiveness of the AMPs. The described models would contribute to the development of effective AMP-based strategies for plant disease management in agricultural and environmental settings. To facilitate broader accessibility, our model is publicly available on the AGRAMP (Agricultural Ngrams Antimicrobial Peptides) server.

Wavily Curved Perylene Diimides: Synthesis, Characterization, and Photovoltaic Properties.

Solubility enhancement is a key issue for developing the perylene diimide-based functional materials. Introduction of curved structure proved an effective solubilizing method without employing steric repulsion. In this work, wavily curved perylene diimides were developed as a new family of highly soluble curved perylene diimides. Moreover, their conformational dynamics, aggregating properties, electronic properties, and photovoltaic performances were thoroughly examined in comparison to the previously reported isomer exhibiting an arched curvature. The waved isomer demonstrated heightened rigidity and a greater propensity for aggregation compared to the arched isomer, likely attributed to its more planar structure. Each benzoxepin unit played a role in cancelling out the curvature on the opposite side. While the difference in the molecular curvature did not cause significant alterations in the photophysical and electron-accepting properties, we identified that the modulation of the curved structure is effective in controlling the morphology of the photoelectric conversion layer.

Rapid and high-purity differentiation of human medium spiny neurons reveals LMNB1 hypofunction and subtype necessity in modeling Huntington’s disease

BackgroundDifferent neural subtypes are selectively lost in diverse neurodegenerative diseases. Huntington’s disease (HD) is an inherited neurodegenerative disease characterized by motor abnormalities that primarily affect the striatum. The Huntingtin (HTT) mutation involves an expanded CAG repeat, leading to insoluble polyQ, which renders GABA+ medium spiny neurons (MSN) more venerable to cell death. Human pluripotent stem cells (hPSCs) technology allows for the construction of disease-specific models, providing valuable cellular models for studying pathogenesis, drug screening, and high-throughput analysis.MethodsIn this study, we established a method that allows for rapid and efficient generation of MSNs (> 90%) within 21 days from hPSC-derived neural progenitor cells, by introducing a specific combination of transcription factors.ResultsWe efficiently induced several neural subtypes, in parallel, based on the same cell source, and revealed that, compared to other neural subtypes, MSNs exhibited higher polyQ aggregation propensity and overexpression toxicity, more severe dysfunction in BDNF/TrkB signaling, greater susceptibility to BDNF withdrawal, and more severe disturbances in nucleocytoplasmic transport (NCT). We further found that the nuclear lamina protein LMNB1 was greatly reduced in HD neurons and mislocalized to the cytoplasm and axons. Knockdown of HTT or treatment with KPT335, an orally selective inhibitor of nuclear export (SINE), effectively attenuated the pathological phenotypes and alleviated neuronal death caused by BDNF withdrawal.ConclusionsThis study thus establishes an effective method for obtaining MSNs and underscores the necessity of using high-purity MSNs to study HD pathogenesis, especially the MSN-selective vulnerability.

Elucidating intermolecular forces to improve compatibility of kraft lignin in poly(lactic acid).

Owing to its abundant supply from renewable resources, lignin has emerged as a promising functional filler for the development of sustainable composite materials. However, achieving good interfacial compatibility between lignin and synthetic polymers, particularly poly (lactic acid) (PLA), remains a fundamental challenge. To advance the development of high-performance bio-based composites incorporating lignin and PLA, our study has scrutinized to unravel the nuances of interfacial binding interactions with the lignin and PLA composite system. Molecular level and experimental examinations were employed to decipher fundamental mechanisms governing and demonstrating the interfacial adhesion. We synthesized casted films of lignin/PLA and acetylated lignin/PLA at varying weight percentages of lignin (5%, 10%, and 20%) and comprehensively investigated their physicochemical and mechanical properties. The inclusion of acetylated lignin in the composites resulted in improved mechanical strength and Young's modulus, while the glass transition temperature and melting point were reduced compared to neat PLA. Systematic variations in these properties revealed distinct compatibility behaviors between unmodified lignin and acetylated lignin when incorporated into PLA. Molecular dynamics (MD) simulation results elucidated that the observed changes in material properties were primarily attributed to the acetylation of lignin. Acetylated lignin exhibited lower Coulombic interaction energy and higher van der Waals forces, indicating a stronger affinity to PLA and a reduced propensity for intermolecular aggregation compared to unmodified lignin. Our findings highlight the critical role of controlling intermolecular interactions and lignin aggregation to develop PLA composites with predictable performance for new applications, such as functional packaging materials.

Impact of Confinement within a Hydrogel Mesh on Protein Thermodynamic Stability and Aggregation Kinetics.

Though protein stability and aggregation have been well characterized in dilute solutions, the influence of a confining environment that exists (e.g., in intercellular and tissue spaces and therapeutic formulations) on the protein structure is largely unknown. Herein, the effects of confinement on stability and aggregation were explored for proteins of different sizes, stability, and hydrophobicity when encapsulated in hydrophilic poly(ethylene glycol) hydrogels. Denaturation curves show linear correlations between confinement size (mesh size) and thermodynamic stability, i.e., unfolding free energy and surface area accessible for solvation (represented by m-value). Two clusters of protein types are identifiable from these correlations; the clusters are defined by differences in protein stability, surface area, and aggregation propensity. Proteins with higher stability, larger surface area, and lower aggregation propensity (e.g., lysozyme and myoglobin) are less affected by the confinement imposed by mesh size than proteins with lower stability, smaller surface area, and higher aggregation propensity (e.g., growth hormone and aldehyde dehydrogenase). According to aggregation kinetics measured by thioflavin T fluorescence, confinement in smaller mesh sizes resulted in slower aggregation rates than that in larger mesh sizes. Compared to that in buffer solution, the confinement of a hydrophobic protein (e.g., human insulin) in the hydrogels accelerates protein aggregation. Conversely, the confinement of a hydrophilic protein (e.g., human amylin) in the hydrogels decelerates or prevents aggregation, with the rates of aggregation inversely proportional to mesh size. These findings provide new insights into protein conformational stability in confined microenvironments relevant to various cellular, tissue, and therapeutics scenarios.

Heterologous expression and fibrillary characterization of the microtubule-binding domain of tau associated with tauopathies.

Neurofibrillary tangles (NFTs) are one of the most common pathological characteristics of Alzheimer's disease. The NFTs are mainly composed of hyperphosphorylated microtubule-associated tau. Thus, recombinant tau is urgently required for the study of its fibrillogenesis and its associated cytotoxicity. Heterologous expression, purification, and fibrillation of the microtubule-binding domain (MBD) of tau (tauMBD) were performed. The tauMBD was heterologously expressed in E. coli. Ni-chelating affinity chromatography was then performed to purify the target protein. Thereafter, tauMBD was systematically identified using the SDS-PAGE, western blot and MALDI-TOF MS methods. The aggregation propensity of the tauMBD was explored by both the thioflavin T fluorescence and atomic force microscopy experiments. The final yield of the recombinant tauMBD was ~ 20 mg L-1. It is shown that TauMBD, in the absence of an inducer, self-assembled into the typical fibrils at a faster rate than wild-type tau. Finally, the in vitro cytotoxicity of tauMBD aggregates was validated using PC12 cells. The heterologously expressed tau in this study can be further used in the investigation of the biophysical and cellular cytotoxic properties of tau.

Interaction between Permeation Enhancers and Lipid Bilayers.

Permeation enhancers (PEs) are a class of molecules that interact with the epithelial membrane and transiently increase its transcellular permeability. Although there have been few clinical trials of PE coformulated drugs, the mechanism of action of PEs remains elusive. In this paper, the interaction between two archetypes of PEs [salcaprozate sodium (SNAC) and sodium caprate (C10)] and membranes is investigated with extensive all-atom molecular dynamics simulations. The simulations show that (1) the association between the neutral PEs and membranes is favored in free energy, (2) the propensity of neutral PE aggregation is larger in aqueous solution than in lipid bilayers, (3) the equilibrium distribution of neutral PEs in membranes is fast, e.g., accessible with unbiased MD simulations, and (4) the micelle of neutral PEs formed in aqueous solution does not rupture the membranes (e.g., not forming pores or breaking up the membrane) under simulation conditions. All results combined, this study indicates that PEs insert into the membranes in an equilibrium or near equilibrium process. This study lays the foundation for future investigations of how PEs impact the free energy of permeation for small molecules.

Electrostatic-Driven Self-Assembly of Janus-like Monolayer-Protected Metal Nanoclusters.

The generation of controlled microstructures of functionalized nanoparticles has been a crucial challenge in nanoscience and nanotechnology. Efforts have been made to tune ligand charge states that can affect the aggregation propensity and modulate the self-assembled structures. In this work, we modeled zwitterionic Janus-like monolayer ligand-protected metal nanoclusters (J-MPCs) and studied their self-assembly using atomistic molecular dynamics and on-the-fly probability-based enhanced sampling simulations. The oppositely charged ligand functionalization on two hemispheres of a J-MPC elicits asymmetric solvation, primarily driven by distinctive hydrogen bonding patterns in the ligand-solvent interactions. Electrostatic interactions between the oppositely charged residues in J-MPCs guide the formation of one-dimensional and ring-like self-assembled superstructures with molecular dipoles oriented in specific patterns. The pertinent atomistic insights into the intermolecular interactions governing the self-assembled structures of zwitterionic J-MPCs obtained from this work can be used to design a general strategy to create tunable microstructures of charged MPCs.

Self-assembly and hydrogelation of a potential bioactive peptide derived from quinoa proteins

In this work the identification of peptides derived from quinoa proteins which could potentially self-assemble, and form hydrogels was carried out with TANGO, a statistical mechanical based algorithm that predicts β-aggregate propensity of peptides. Peptides with the highest aggregate propensity were subjected to gelling screening experiments from which the most promising bioactive peptide with sequence KIVLDSDDPLFGGF was selected. The self-assembling and hydrogelation properties of the C-terminal amidated peptide (KIVLDSDDPLFGGF-NH2) were studied. The effect of concentration, pH, and temperature on the secondary structure of the peptide were probed by circular dichroism (CD), while its nanostructure was studied by transmission electron microscopy (TEM) and small-angle neutron scattering (SANS). Results revealed the existence of random coil, α-helix, twisted β-sheet, and well-defined β-sheet secondary structures, with a range of nanostructures including elongated fibrils and bundles, whose proportion was dependant on the peptide concentration, pH, or temperature. The self-assembly of the peptide is demonstrated to follow established models of amyloid formation, which describe the unfolded peptide transiting from an α-helix-containing intermediate into β-sheet-rich protofibrils. The self-assembly is promoted at high concentrations, elevated temperatures, and pH values close to the peptide isoelectric point, and presumably mediated by hydrogen bond, hydrophobic and electrostatic interactions, and π-π interactions (from the F residue). At 15 mg/mL and pH 3.5, the peptide self-assembled and formed a self-supporting hydrogel exhibiting viscoelastic behaviour with G' (1 Hz) ~2300 Pa as determined by oscillatory rheology measurements. The study describes a straightforward method to monitor the self-assembly of plant protein derived peptides; further studies are needed to demonstrate the potential application of the formed hydrogels in food and biomedicine.

Sedimentation and Laser Light Scattering Methods for Quantifying Synthetic Tau Aggregation Propensity.

Tau aggregation assays detect and quantify the conversion of soluble tau monomers into species having filamentous or oligomeric structure. Assays for filamentous aggregates in cross-β-sheet conformation leverage optical, biochemical, or biophysical methods, each with their own advantages and throughput capacity. Here we provide protocols for two medium-throughput assays based on sedimentation and laser light scattering and compare their performance, their utility for characterizing tau aggregation dynamics, and their limitations relative to other approaches. Additionally, a protocol for transmission electron microscopy analysis is updated so as to be compatible with the truncated tau variants that have emerged as powerful tools for interrogating the structural basis of tau polymorphism. Together these methods contribute to a rich tool kit for interrogating tau aggregation kinetics and propensity over a wide range of experimental conditions.

RNA-Seq Analysis of Mammalian Prion Disease.

A protein, which can attain a prion state, differs from standard proteins in terms of structural conformation and aggregation propensity. High-throughput sequencing technology provides an opportunity to gain insight into the prion disease condition when coupled with single-cell RNA-Seq analysis to reveal transcriptional changes during prion-based pathogenicity. In this chapter, we present a protocol for RNA-Seq analysis of mammalian prion disease using a single-cell RNA sequencing dataset procured from the NCBI GEO database. This protocol is a tool that can assist researchers in characterizing mammalian prion disease in a reproducible and reusable manner. Further, the resulting output has the potential to provide transcript biomarkers for mammalian prion diseases, which can be employed for diagnostic and prognostic purposes.

Differentiating SH-SY5Y Cells into Polarized Human Neurons for Studying Endogenous and Exogenous Tau Trafficking: Four Protocols to Obtain Neurons with Noradrenergic, Dopaminergic, and Cholinergic Properties.

Pathological alterations of the neuronal Tau protein are characteristic for many neurodegenerative diseases, called tauopathies. To investigate the underlying mechanisms of tauopathies, human neuronal cell models are required to study Tau physiology and pathology in vitro. Primary rodent neurons are an often used model for studying Tau, but rodent Tau differs in sequence, splicing, and aggregation propensity, and rodent neuronal physiology cannot be compared to humans. Human-induced pluripotent stem cell (hiPSC)-derived neurons are expensive and time-consuming. Therefore, the human neuroblastoma SH-SY5Y cell line is a commonly used cell model in neuroscience as it combines convenient handling and low costs with the advantages of human-derived cells. Since naïve SH-SY5Y cells show little similarity to human neurons and almost no Tau expression, differentiation is necessary to obtain human-like neurons for studying Tau protein-related aspects of health and disease. As they express in principle all six Tau isoforms seen in the human brain, differentiated SH-SY5Y-derived neurons are suitable for investigating the human microtubule-associated protein Tau and, for example, its sorting and trafficking. Here, we describe and discuss a general cultivation procedure as well as four differentiation methods to obtain SH-SY5Y-derived neurons resembling noradrenergic, dopaminergic, and cholinergic properties, based on the treatment with retinoic acid (RA), brain-derived neurotrophic factor (BDNF), and 12-O-tetrade canoylphorbol-13-acetate (TPA). TPA and RA-/TPA-based protocols achieve differentiation efficiencies of 40-50% after 9 days of treatment. The highest differentiation efficiency (~75%) is accomplished by a combination of RA and BDNF; treatment only with RA is the most time-efficient method as ~50% differentiated cells can be obtained already after 7 days.

Serine phosphorylation mimics of Aβ form distinct, non-cross-seeding fibril morphs.

The self-assembly of amyloid-β peptide (Aβ) into fibrils and oligomers is linked to Alzheimer's disease (AD). Fibrillar aggregates in AD patient's brains contain several post-translational modifications, including phosphorylation at positions 8 and 26. These play a key role in modifying the aggregation propensity of Aβ, yet how they affect the mechanism of aggregation is only poorly understood. Here we elucidate the aggregation mechanism of Aβ42 peptides with phosphomimic mutations at these positions, with glutamine mimicking the size, and glutamate mimicking both the size and charge effect. We find that all variants are less aggregation-prone than wild-type Aβ42 with the glutamate mutants showing the largest reduction. Secondary nucleation is the dominant nucleation route for all variants, as confirmed using seeding experiments; however, its rate is reduced by about an order of magnitude or more for all variants relative to wild-type. S26Q and S26E fibrils fail to catalyse nucleation of wild-type monomers and vice versa, while the S8 variants co-aggregate more readily with wild-type. Ultrastructural analyses by cryo-electron microscopy and small angle X-ray scattering reveal an altered structure with longer node-to-node distance and smaller cross-section dimensions of S26Q fibrils. These results imply that structural compatibility between fibrils and monomer is a key determinant in secondary nucleation, and that small modifications can alter the preferred fibril structure, and thus its potential to induce aggregation of other variants. Overall, our results indicate that phosphorylation could play a key role in controlling aggregation propensity and may lead to the formation of distinct, non-cross-seeding fibril populations.

Amyloid Protein in AL-Amyloidosis. Natural History and Potential for Regression

Amyloid light chain amyloidosis is the most commonly seen form of systemic amyloidosis and is characterized by the accumulation of circulating monoclonal immunoglobulin light chain precursors arising from an abnormal clone of plasma cells. These light chain precursors demonstrate a propensity for misfolding, aggregation and deposition as highly stable fibrillar cross-linked beta sheets in various tissues and organs in a manner characteristic of other forms of systemic amyloidosis. There have been great advances in the treatment of the underlying plasma cell dyscrasia with improved long-term survival but the persistence of extracellular amyloid deposits in the tissues of vital organs, particularly the heart and kidney remains a significant cause of morbidity and mortality even in those patients in whom a hematological complete response has been achieved. This review focuses on the importance of early diagnosis and treatment on limiting the extent of amyloid protein accumulation and organ dysfunction and the current state of knowledge on the potential for resorption and clearance of these amyloid deposits in patients with amyloid light chain amyloidosis. The status of current novel anti-fibrillar agents is reviewed and future strategies for effectively intervening to improve organ function and survival these individuals is discussed.

Prediction of protein aggregation.

The scientific community is very interested in protein aggregation because of its involvement in several neurodegenerative diseases and its significance in industry. Remarkably, fibrillar aggregates are utilized naturally for constructing structural scaffolds or creating biological switches and may be intentionally designed to construct versatile nanomaterials. Consequently, there is a significant need to rationalize and predict protein aggregation. Researchers have developed various computational methodologies and algorithms to predict protein aggregation and understand its underlying mechanics. This chapter aims to summarize the significant advancements in computational methods, accessible resources, and prospective developments in the field of in silico research. We assess the existing computational tools for predicting protein aggregation propensities, detecting areas that are prone to sequential and structural aggregation, analyzing the effects of mutations on protein aggregation, or identifying prion-like domains.

Modulation of Aβ 16-22 aggregation by glucose.

The self-assembly of amyloid-beta (Aβ) peptides into fibrillar structures in the brain is a signature of Alzheimer's disease. Recent studies have reported correlations between Alzheimer's disease and type-2 diabetes. Structurally, hyperglycemia induces covalent protein crosslinkings by advanced glycation end products (AGE), which can affect the stability of Aβ oligomers. In this work, we leverage physics-based coarse-grained molecular simulations to probe alternate thermodynamic pathways that affect peptide aggregation propensities at varying concentrations of glucose molecules. Similar to previous experimental reports, our simulations show a glucose concentration-dependent increase in Aβ aggregation rates, without changes in the overall secondary structure content. We discovered that glucose molecules prefer partitioning onto the aggregate-water interface at a specific orientation, resulting in a loss of molecular rotational entropy. This effectively hastens the aggregation rates, as peptide self-assembly can reduce the available surface area for peptide-glucose interactions. This work introduces a new thermodynamic-driven pathway, beyond chemical cross-linking, that can modulate Aβ aggregation.

Multi-scale in silico analysis of the phase separation behavior of FUS mutants.

Fused in sarcoma (FUS) is an intrinsically disordered RNA-binding protein that helps to regulate transcription and RNA transport while reversibly assembling into membraneless organelles (MLOs). Some mutations of FUS can promote irreversible aggregation, contributing to neurodegenerative diseases. We previously reported a multi-scale computational framework combining a series of molecular dynamics simulations (MD) followed by lattice Monte Carlo (MC) simulations to describe the tendency and dynamics of the assembly and disassembly of intrinsically disordered proteins (IDPs) using wild-type (WT)-FUS as an illustrative example. In this study, we utilized our computational model to simulate three FUS mutants widely experimented with glycine point mutation G156E, arginine point mutation R244C, and deletion of the C-terminal nuclear localization signal (ΔNLS). MD simulation results conveyed that G156E has improved sticker contact probability compared to WT-FUS, while R244C has slightly lower contact probability, which is also complemented by change of net interactions according to the molecular mechanics Poisson Boltzmann surface area (MMPBSA) method. The MC simulation results revealed that G156E has a higher aggregation propensity than the WT-FUS, while ΔNLS has more liquid-like assemblies. R244C demonstrated higher dynamics at the beginning, while over the evolution of MC simulations, it tends to aggregate compared to WT-FUS. In addition, the G156E mutant has more stable protein aggregates, lacking the rapid dynamics shown in all other scenarios. From the peak height of radial distribution functions (RDFs) of the assemblies, the phase separation propensity in ascending order is ΔNLS < FUS-WT < R244C < G156E. Moreover, interpreting the dynamic assembly propensity (DAP) parameter over time, the fluidity of the assemblies in ascending order is G156E < FUS-WT < R244C < ΔNLS. The results obtained from this study support that the computational model is able to predict the effect of mutation down to single amino acid substitution on the phase separation behavior of FUS. This efficient in silico method can be generalized to investigate the phase separation propensity of other IDPs and their mutants.

Vertical growth of a 3D Ni-Co-LDH/N-doped graphene aerogel: a cost-effective and high-performance sulfur host for Li-S batteries.

Sulfur hosts and conversion catalysts based on NiCo-LDHs exhibit potential for improving the performance of Li-S batteries. Nevertheless, their low electron conductivity and aggregation propensity restrict their applicability. This investigation employs a temporary scaffold of ZIF-67 to produce a nanotube assembly of Ni-Co-LDH encapsulated within an N-doped graphene sponge. The electrochemically developed interface has an extended active surface area, and the clumping of LDH nanosheets is effectively inhibited by the design of the nanotube arrangement. Furthermore, the incorporation of nitrogen within the structure of graphene results in a boost of electrical conductivity and provides an increased quantity of active sites. Interfacial electron transport is facilitated by the interfacial rearrangement of charges resulting from p-n heterojunctions and fosters redox activity. In this study, the researchers have presented the double role played by the nickel-cobalt layered double hydroxide (NiCo-LDH) nanotubes in improving the polysulphide (LiPS) conversion and decreasing the movement of the sulphur (S) ions by forming surface-bound intermediates. The battery that was fabricated using the above composite cathode mixture showed a higher energy storage ability, i.e., 1190.0 mA h g-1 at J = 0.2. Furthermore, the battery showed a significantly higher capacity to rapidly supply energy and displayed a rate capacity of 670.1 mA h g-1 at J = 5C. Also, the above battery displayed a longer cycle life, with 1000 charge-discharge cycles and the deterioration rate of 0.029% for each cycle.

Probing the Protein-Excipient Interaction in the Orally Delivered Protein by Solid-State Hydrogen-Deuterium Exchange Mass Spectrometry and Molecular Dynamics.

The oral administration of protein therapeutics in solid dosage form is gaining popularity due to its benefits, such as improved medication adherence, convenience, and ease of use for patients compared to traditional parental delivery. However, formulating oral biologics presents challenges related to pH barriers, enzymatic breakdown, and poor bioavailability. Therefore, understanding the interaction between excipients and protein therapeutics in the solid state is crucial for formulation development. In this Letter, we present a case study focused on investigating the role of excipients in protein aggregation during the production of a solid dosage form of a single variable domain on a heavy chain (VHH) protein. We employed solid-state hydrogen-deuterium exchange coupled with mass spectrometry (ssHDX-MS) at both intact protein and peptide levels to assess differences in protein-excipient interactions between two formulations. ssHDX-MS analysis revealed that one formulation effectively prevents protein aggregation during compaction by blocking β-sheets across the VHH protein, thereby preventing β-sheet-β-sheet interactions. Spatial aggregation propensity (SAP) mapping and cosolvent simulation from molecular dynamics (MD) simulation further validated the protein-excipient interaction sites identified through ssHDX-MS. Additionally, the MD simulation demonstrated that the interaction between the VHH protein and excipients involves hydrophilic interactions and/or hydrogen bonding. This novel approach holds significant potential for understanding protein-excipient interactions in the solid state and can guide the formulation and process development of orally delivered protein dosage forms, ultimately enhancing their efficacy and stability.