Comparing the energy landscapes for native folding and aggregation of PrP

Structural evolution of fibril polymorphs during amyloid assembly

Cryoelectron microscopy (cryo-EM) has provided unprecedented insights into amyloid fibril structures, including those associated with disease. However, these structures represent the endpoints of long assembly processes, and their relationship to fibrils formed early in assembly is unknown. Consequently, whether different fibril architectures, with potentially different pathological properties, form during assembly remains unknown. Here, we used cryo-EM to determine structures of amyloid fibrils at different times during in vitro fibrillation of a disease-related variant of human islet amyloid polypeptide (IAPP-S20G). Strikingly, the fibrils formed in the lag, growth, and plateau phases have different structures, with new forms appearing and others disappearing as fibrillation proceeds. A time course with wild-type hIAPP also shows fibrils changing with time, suggesting that this is a general property of IAPP amyloid assembly. The observation of transiently populated fibril structures has implications for understanding amyloid assembly mechanisms with potential new insights into amyloid progression in disease.

Protein aggregation: Consequences, mechanism, characterization and inhibitory strategies

Proteins play a major role in the regulation of various cellular functions including the synthesis of structural components. But proteins are stable under physiological conditions only. A slight variation in environmental conditions can cost them huge in terms of conformational stability ultimately leading to aggregation. Under normal conditions, aggregated proteins are degraded or removed from the cell by a quality control system including ubiquitin-proteasomal machinery and autophagy. But they are burdened under diseased conditions or are impaired by the aggregated proteins leading to the generation of toxicity. The misfolding and aggregation of protein such as amyloid-β, α-synuclein, human lysozyme etc., are responsible for certain diseases including Alzheimer, Parkinson, and non- neuropathic systemic amyloidosis respectively. Extensive research has been done to find the therapeutics for such diseases but till now we have got only symptomatic treatment that will reduce the disease severity but will not target the initial formation of nucleus responsible for disease progression and propagation. Hence there is an urgent need to develop the drugs targeting the cause of the disease. For this, a wide knowledge related to misfolding and aggregation under the same heading is required as described in this review alongwith the strategies hypothesized and implemented till now. This will contribute a lot to the work of researchers in the field of neuroscience.

Thermoinducible E. coli for Recombinant Protein Production in Inclusion Bodies

The temperature-inducible λpL/pR-cI857 expression system has been widely used to produce recombinant proteins (RPs), especially when it is necessary to avoid the addition of exogenous materials to induce the expression of recombinant genes, preventing contamination of bioprocesses. The temperature increase favors the formation of inclusion bodies (IBs). The temperature upshift could change the metabolism, productivities, cell viability, IBs architecture, and the host cell proteins inside IBs, affecting downstream to obtain the final product. In this contribution, we focus on the relationship between the bioprocesses using temperature increase as inducer, the heat shock response associated with temperature up-shift, the RP accumulation, and the formation of IBs. Here, we describe how to produce IBs and how culture conditions can modulate the composition and architecture of IBs by modifying the induction temperature in RP production.

Following the Aggregation of Human Prion Protein on Heparin Functionalized Gold Surface in Real Time

The aggregation of the prion protein (PrP) plays a key role in the development of prion diseases and is believed to be an autocatalytic process with a very high kinetic barrier. Intensive studies have focused on overcoming the kinetic barriers under extremely nonphysiological in vitro conditions by altering the pH of PrP solution on solid surfaces, such as gold, mica, and a lipid bilayer. Importantly, sulfated glycosaminoglycans (GAGs), including heparin, were found to be associated with PrP misfolding and aggregation, suggesting GAGs have catalytic roles in PrP aggregation processes. However, the exact role and details of GAGs in the PrP aggregation are not clear and need a thorough perusal. Here, we investigate the PrP aggregation process on a heparin functionalized gold surface by in situ, real-time monitoring of the atomic scale details of the whole aggregation process by single molecule atomic force microscopy (AFM), combining simultaneous topographic and recognition (TREC) imaging and single molecule force spectroscopy (SMFS). We observed the whole aggregation process for full-length human recombinant PrP (23-231) aggregation on the heparin modified gold surface, from the formation of oligomers, to the assembly of protofibrils and short fibers, and the formation of elongated mature fibers. Heparin is found to promote the PrP aggregation by facilitating the formation of oligomers during the early nucleation stage.

Insights to Human γD-Crystallin Unfolding by NMR Spectroscopy and Molecular Dynamics Simulations

Human γD-crystallin (HGDC) is an abundant lens protein residing in the nucleus of the human lens. Aggregation of this and other structural proteins within the lens leads to the development of cataract. Much has been explored on the stability and aggregation of HGDC and where detailed investigation at the atomic resolution was needed, the X-ray structure was used as an initial starting conformer for molecular modeling. In this study, we implemented NMR-solution HGDC structures as starting conformers for molecular dynamics simulations to provide the missing pieces of the puzzle on the very early stages of HGDC unfolding leading up to the domain swap theories proposed by past studies. The high-resolution details of the conformational dynamics also revealed additional insights to possible early intervention for cataractogenesis.

An experimental approach probing the conformational transitions and energy landscape of antibodies: a glimmer of hope for reviving lost therapeutic candidates using ionic liquid

Understanding protein folding in different environmental conditions is fundamentally important for predicting protein structures and developing innovative antibody formulations. While the thermodynamics and kinetics of folding and unfolding have been extensively studied by computational methods, experimental methods for determining antibody conformational transition pathways are lacking. Motivated to fill this gap, we prepared a series of unique formulations containing a high concentration of a chimeric immunoglobin G4 (IgG4) antibody with different excipients in the presence and absence of the ionic liquid (IL) choline dihydrogen phosphate. We determined the effects of different excipients and IL on protein thermal and structural stability by performing variable temperature circular dichroism and bio-layer interferometry analyses. To further rationalise the observations of conformational changes with temperature, we carried out molecular dynamics simulations on a single antibody binding fragment from IgG4 in the different formulations, at low and high temperatures. We developed a methodology to study the conformational transitions and associated thermodynamics of biomolecules, and we showed IL-induced conformational transitions. We showed that the increased propensity for conformational change was driven by preferential binding of the dihydrogen phosphate anion to the antibody fragment. Finally, we found that a formulation containing IL with sugar, amino acids and surfactant is a promising candidate for stabilising proteins against conformational destabilisation and aggregation. We hope that ultimately, we can help in the quest to understand the molecular basis of the stability of antibodies and protein misfolding phenomena and offer new candidate formulations with the potential to revive lost therapeutic candidates.

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.

Optical Tweezers Approaches for Probing Multiscale Protein Mechanics and Assembly

Multi-step assembly of individual protein building blocks is key to the formation of essential higher-order structures inside and outside of cells. Optical tweezers is a technique well suited to investigate the mechanics and dynamics of these structures at a variety of size scales. In this mini-review, we highlight experiments that have used optical tweezers to investigate protein assembly and mechanics, with a focus on the extracellular matrix protein collagen. These examples demonstrate how optical tweezers can be used to study mechanics across length scales, ranging from the single-molecule level to fibrils to protein networks. We discuss challenges in experimental design and interpretation, opportunities for integration with other experimental modalities, and applications of optical tweezers to current questions in protein mechanics and assembly.

Cross-Species and Cross-Polymorph Seeding of Lysozyme Amyloid Reveals a Dominant Polymorph

The ability to self-propagate is one of the most intriguing characteristics of amyloid fibrils, and is a feature of great interest both to stopping unwanted pathological amyloid, and for engineering functional amyloid as a useful nanomaterial. The sequence and structural tolerances for amyloid seeding are not well understood, particularly concerning the propagation of distinct fibril morphologies (polymorphs) across species. This study examined the seeding and cross-seeding reactions between two unique fibril polymorphs, one long and flexible (formed at pH 2) and the other short and rigid (formed at pH 6.3), of human lysozyme and hen egg-white lysozyme. Both polymorphs could cross-seed aggregation across species, but this reaction was markedly reduced under physiological conditions. For both species, the pH 6.3 fibril polymorph was dominant, seeding fibril growth with a faster growth rate constant at pH 2 than the pH 2 polymorph. Based on fibrillation kinetics and fibril morphology, we found that the pH 2 polymorph was not able to faithfully replicate itself at pH 6.3. These results show that two distinct amyloid polymorphs are both capable of heterologous seeding across two species (human and hen) of lysozyme, but that the pH 6.3 polymorph is favored, regardless of the species, likely due to a lower energy barrier, or faster configurational diffusion, to accessing this particular misfolded form. These findings contribute to our better understanding of amyloid strain propagation across species barriers.

Model for Counterion Binding and Charge Reversal on Protein Surfaces

The structural stability and solubility of proteins in liquid therapeutic formulations is important, especially since new generations of therapeutics are designed for efficacy before consideration of stability. We introduce an electrostatic binding model to measure the net charge of proteins with bound ions in solution. The electrostatic potential on a protein surface is used to separately group together acidic and basic amino acids into patches, which are then iteratively bound with oppositely charged counterions. This model is aimed toward formulation chemists for initial screening of a range of conditions prior to lab-work. Computed results compare well with experimental zeta potential measurements from the literature covering a range of solution conditions. Importantly, the binding model reproduces the charge reversal phenomenon that is observed with polyvalent ion binding to proteins and its dependence on ion charge and concentration. Intriguingly, protein sequence can be used to give similarly good agreement with experiment as protein structure, interpreted as resulting from the close proximity of charged side chains on a protein surface. Further, application of the model to human proteins suggests that polyanion binding and overcharging, including charge reversal for cationic proteins, is a general feature. These results add to evidence that addition of polyanions to protein formulations could be a general mechanism for modulating solution stability.

Stochastic diffusion framework determines the free-energy landscape and rate from single-molecule trajectory

A theoretical stochastic diffusion framework is developed that characterizes the position-dependent diffusion coefficient [D(Q)] and drift velocity [ v (Q)] by analysing single-molecule time traces [Q(t)]. The free-energy landscape [F(Q)] that governs the dynamics is reconstructed with the calculated D and v . There are many computational tools that perform this task in which some are computationaly demanding, difficult to run, and, most of the time, not directly available to the community. This is a first attempt to implement the simplified stochastic diffusion framework that is fast, easy to run in a Python environment, and available to be extended as needed. It does not require adjustable parameters, inference methods, or sampling bias such as Monte Carlo Bayesian estimators or umbrella samplings. The stochastic framework was applied in the protein-like lattice model with Monte Carlo simulations, which accurately predicted the folding rates with the coordinate-dependent D and F plugged into Kramers' theory. The results were compared with two other independently developed methodologies (the Bayesian analysis and fep1D algorithm) presenting a good match, which confirms its validity. This theoretical framework might be useful in determining the free-energy and rates by providing time series only from biological or condensed-phase systems. The code is freely available at https://github.com/ronaldolab/stochastic_diffusion.