Impact of sequence on the molecular assembly of short amyloid peptides

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Peptide Amphiphiles as Biodegradable Adjuvants for Efficient Retroviral Gene Delivery

Retroviral gene delivery is the key technique for in vitro and ex vivo gene therapy. However, inefficient virion-cell attachment resulting in low gene transduction efficacy remains a major challenge in clinical applications. Adjuvants for ex vivo therapy settings need to increase transduction efficiency while being easily removed or degraded post-transduction to prevent the risk of venous embolism after infusing the transduced cells back to the bloodstream of patients, yet no such peptide system have been reported thus far. In this study, peptide amphiphiles (PAs) with a hydrophobic fatty acid and a hydrophilic peptide moiety that reveal enhanced viral transduction efficiency are introduced. The PAs form β-sheet-rich fibrils that assemble into positively charged aggregates, promoting virus adhesion to the cell membrane. The block-type amphiphilic sequence arrangement in the PAs ensures efficient cell-virus interaction and biodegradability. Good biodegradability is observed for fibrils forming small aggregates and it is shown that via molecular dynamics simulations, the fibril-fibril interactions of PAs are governed by fibril surface hydrophobicity. These findings establish PAs as additives in retroviral gene transfer, rivalling commercially available transduction enhancers in efficiency and degradability with promising translational options in clinical gene therapy applications.

Multiscale Models for Fibril Formation: Rare Events Methods, Microkinetic Models, and Population Balances

Amyloid fibrils are thought to grow by a two-step dock-lock mechanism. However, previous simulations of fibril formation (i) overlook the bi-molecular nature of the docking step and obtain rates with first-order units, or (ii) superimpose the docked and locked states when computing the potential of mean force for association and thereby muddle the docking and locking steps. Here, we developed a simple microkinetic model with separate locking and docking steps and with the appropriate concentration dependences for each step. We constructed a simple model comprised of chiral dumbbells that retains qualitative aspects of fibril formation. We used rare events methods to predict separate docking and locking rate constants for the model. The rate constants were embedded in the microkinetic model, with the microkinetic model embedded in a population balance model for “bottom-up” multiscale fibril growth rate predictions. These were compared to “top-down” results using simulation data with the same model and multiscale framework to obtain maximum likelihood estimates of the separate lock and dock rate constants. We used the same procedures to extract separate docking and locking rate constants from experimental fibril growth data. Our multiscale strategy, embedding rate theories, and kinetic models in conservation laws should help to extract docking and locking rate constants from experimental data or long molecular simulations with correct units and without compromising the molecular description.

Interactions between Curcumin Derivatives and Amyloid-β Fibrils: Insights from Molecular Dynamics Simulations

The aggregation of amyloid-β (Aβ) peptides into senile plaques is a hallmark of Alzheimer's disease (AD) and is hypothesized to be the primary cause of AD related neurodegeneration. Previous studies have shown the ability of curcumin to both inhibit the aggregation of Aβ peptides into oligomers or fibrils and reduce amyloids in vivo. Despite the promise of curcumin and its derivatives to serve as diagnostic, preventative, and potentially therapeutic AD molecules, the mechanism by which curcumin and its derivatives bind to and inhibit Aβ fibrils' formation remains elusive. Here, we investigated curcumin and a set of curcumin derivatives in complex with a hexamer peptide model of the Aβ1-42 fibril using nearly exhaustive docking, followed by multi-ns molecular dynamics simulations, to provide atomistic-detail insights into the molecules' binding and inhibitory properties. In the vast majority of the simulations, curcumin and its derivatives remain firmly bound in complex with the fibril through primarily three different principle binding modes, in which the molecules interact with residue domain 17LVFFA21, in line with previous experiments. In a small subset of these simulations, the molecules partly dissociate the outermost peptide of the Aβ1-42 fibril by disrupting β-sheets within the residue domain 12VHHQKLVFF20. A comparison between binding modes leading or not leading to partial dissociation of the outermost peptide suggests that the latter is attributed to a few subtle key structural and energetic interaction-based differences. Interestingly, partial dissociation appears to be either an outcome of high affinity interactions or a cause leading to high affinity interactions between the molecules and the fibril, which could partly serve as a compensation for the energy loss in the fibril due to partial dissociation. In conjunction with this, we suggest a potential inhibition mechanism of Αβ1-42 aggregation by the molecules, where the partially dissociated 16KLVFF20 domain of the outermost peptide could either remain unstructured or wrap around to form intramolecular interactions with the same peptide's 29GAIIG33 domain, while the molecules could additionally act as a patch against the external edge of the second outermost peptide's 16KLVFF20 domain. Thereby, individually or concurrently, these could prohibit fibril elongation.

Electric Field Disruption of Amyloid Aggregation: Potential Noninvasive Therapy for Alzheimer's Disease

The aggregation of β-amyloid peptides is a key event in the formative stages of Alzheimer's disease. Promoting folding and inhibiting aggregation was reported as an effective strategy in reducing Aβ-elicited toxicity. This study experimentally investigates the influence of the external electric field (EF) and magnetic field (MF) of varying strengths on the in vitro fibrillogenesis of hydrophobic core sequence, Aβ_16-22, and its parent peptide, Aβ_1-42. Biophysical methods such as ThT fluorescence, static light scattering, circular dichroism, and infrared spectroscopy suggest that EF has a stabilizing effect on the secondary structure, initiating a conformational switch of Aβ_16-22 and Aβ_1-42 from β to non-β conformation. This observation was further corroborated by dynamic light scattering and transmission electron microscopic studies. To mimic in vivo conditions, we repeated ThT fluorescence assay with Aβ_1-42 in human cerebrospinal fluid to verify EF-mediated modulation. The self-seeding of Aβ_1-42 and cross-seeding with Aβ_1-40 to verify that the autocatalytic amplification of self-assembly as a result of secondary nucleation also yields comparable results in EF-exposed and unexposed samples. Aβ-elicited toxicity of EF-treated samples in two neuroblastoma cell lines (SH-SY5Y and IMR-32) and human embryonic kidney cell line (HEK293) were found to be 15-38% less toxic than the EF untreated ones under identical conditions. Experiments with fluorescent labeled Aβ_1-42 to correlate reduced cytotoxicity and cell internalization suggest a comparatively smaller uptake of the EF-treated peptides. Our results provide a scientific roadmap for future noninvasive, therapeutic solutions for the treatment of Alzheimer's disease.

Critical role of C-terminal residues of the Alzheimer's associated β-amyloid protein in mediating antiviral activity and modulating viral and bacterial interactions with neutrophils

Recent studies have shown that the Alzheimer's associated β-amyloid protein (βA) can inhibit growth of bacteria, fungi and viruses. We reported that the 42 amino acid βA protein inhibits replication of seasonal and pandemic strains of H3N2 and H1N1 influenza A virus (IAV) in vitro and modulates activation of neutrophils and monocytes exposed IAV. We here show that fragments composed of the N and C terminal domain of βA42, including βA22-42 and the 8 amino acid βA35-42, retain viral neutralizing and viral aggregating activity, whereas fragments lacking the C-terminal amino acids 41 and 42 (e.g. βA1-40, βA1-34, βA1-28, βA22-40 or βA33-40) have markedly diminished activities on these assays. βA22-42 also increased viral uptake, and virus induced respiratory burst responses, by human neutrophils, while peptides lacking residues 41 and 42 did not. Similar results were obtained with regard to bacterial aggregation, or promotion of bacterial uptake by neutrophils. Published structural studies have shown that βA1-42 has a greater propensity to form neurotoxic oligomers than βA1-40 due to a molecular interaction between Met35 and Ala42. Our findings suggest that there is a relationship between neurotoxic and antimicrobial activities of βA1-42. Truncated peptides containing the last 8 C-terminal amino acids of βA1-42 retain antimicrobial and opsonizing activities likely resulting from their ability to induce viral or bacterial aggregation.

Probing beta amyloid aggregation using fluorescence anisotropy: experiments and simulation

Simulated fluorescence anisotropy from Tyr residues distinguishes a beta amyloid monomer (black) from oligomers (coloured).

Modulating protein amyloid aggregation with nanomaterials

Direct exposure or intake of nanopaticles (NPs) to the human body can invoke a series of biological responses, some of which are deleterious, and as such the role of NPs in vivo requires thorough examination. Over the past decade, it has been established that biomolecules such as proteins can bind NPs to form a 'corona', where the structures and dynamics of NP-associated proteins can assign new functionality, systemic distribution and toxicity. However, the behavior and fate of NPs in biological systems are still far from being fully understood. Growing evidence has shown that some natural or artificial NPs could either up- or down-regulate protein amyloid aggregation, which is associated with neurodegenerative diseases like Alzheimer's and Parkinson's diseases, as well as metabolic diseases such as type 2 diabetes. These effects can be either indirect (e.g., through a crowding effect) or direct, depending on the NP composition, size, shape and surface chemistry. However, efforts to design anti-amyloid NPs for biomedical applications have been largely hindered by insufficient understanding of the complex processes, even though proof-of-concept experiments have been conducted. Therefore, exploring the general mechanisms of NP-meditated protein aggregation marks an emerging field in bio-nano research and a new stage of handling nanotechnology that not only aids in elucidating the origin of nanotoxicity, but also provides a foundation for engineering de novo anti-amyloid nanomedicines. In this review, we summarize research on NP-mediated protein amyloid aggregation, with the goal of contributing to sustained nanotechnology and safe nanomedicine against amyloid diseases.

Interplay between the hydrophobic effect and dipole interactions in peptide aggregation at interfaces

Amphipathic octapeptide aggregation at hydrophobic–hydrophilic interfaces is largely driven by backbone dipole interactions in peptide aggregation at interfaces.