Structural Modulation of Human Amylin Protofilaments by Naturally Occurring Mutations

Authentic hSAA related with AA amyloidosis: New method of purification, folding and amyloid polymorphism

The secondary amyloidosis of humans is caused by the formation of hSAA fibrils in different organs and tissues. Until now hSAA was thought to have low amyloidogenicity in vitro and the majority of SAA aggregation experiments were done using murine protein or hSAA non-pathogenic isoforms. In this work a novel purification method for recombinant hSAA was introduced, enabling to obtain monomeric protein capable of amyloid aggregation under physiological conditions. The stability and amyloid aggregation of hSAA have been examined using a wide range of biophysical methods. It was shown that the unfolding of monomeric protein occurs through the formation of molten globule-like intermediate state. Polymorphism of hSAA amyloids was discovered to depend on the solution pH. At pH 8.5, rapid protein aggregation occurs, which leads to the formation of twisted short fibrils. Even a slight decrease of the pH to 7.8 results in delayed aggregation with the formation of long straight amyloids composed of laterally associated protofilaments. Limited proteolysis experiments have shown that full-length hSAA is involved in the formation of intermolecular interactions in both amyloid polymorphs. The results obtained, and the experimental approach used in this study can serve as a basis for further research on the mechanism of authentic hSAA amyloid formation.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Living with the enemy: from protein-misfolding pathologies we know, to those we want to know

Conformational diseases are caused by the aggregation of misfolded proteins. The risk for such pathologies develops years before clinical symptoms appear, and is higher in people with alpha-1 antitrypsin (AAT) polymorphisms. Thousands of people with alpha-1 antitrypsin deficiency (AATD) are underdiagnosed. Enemy-aggregating proteins may reside in these underdiagnosed AATD patients for many years before a pathology for AATD fully develops. In this perspective review, we hypothesize that the AAT protein could exert a new and previously unconsidered biological effect as an endogenous metal ion chelator that plays a significant role in essential metal ion homeostasis. In this respect, AAT polymorphism may cause an imbalance of metal ions, which could be correlated with the aggregation of amylin, tau, amyloid beta, and alpha synuclein proteins in type 2 diabetes mellitus (T2DM), Alzheimer's and Parkinson's diseases, respectively.

α-CGRP disrupts amylin fibrillization and regulates insulin secretion: implications on diabetes and migraine

Despite being relatively benign and not an indicative signature of toxicity, fibril formation and fibrillar structures continue to be key factors in assessing the structure-function relationship in protein aggregation diseases. The inability to capture molecular cross-talk among key players at the tissue level before fibril formation greatly accounts for the missing link toward the development of an efficacious therapeutic intervention for Type II diabetes mellitus (T2DM). We show that human α-calcitonin gene-related peptide (α-CGRP) remodeled amylin fibrillization. Furthermore, while CGRP and/or amylin monomers reduce the secretion of both mouse Ins1 and Ins2 proteins, CGRP oligomers have a reverse effect on Ins1. Genetically reduced Ins2, the orthologous version of human insulin, has been shown to enhance insulin sensitivity and extend the life-span in old female mice. Beyond the mechanistic insights, our data suggest that CGRP regulates insulin secretion and lowers the risk of T2DM. Our result rationalizes how migraine might be protective against T2DM. We envision the new paradigm of CGRP : amylin interactions as a pivotal aspect for T2DM diagnostics and therapeutics. Maintaining a low level of amylin while increasing the level of CGRP could become a viable approach toward T2DM prevention and treatment.

Proteostasis of Islet Amyloid Polypeptide: A Molecular Perspective of Risk Factors and Protective Strategies for Type II Diabetes

The possible link between hIAPP accumulation and β-cell death in diabetic patients has inspired numerous studies focusing on amyloid structures and aggregation pathways of this hormone. Recent studies have reported on the importance of early oligomeric intermediates, the many roles of their interactions with lipid membrane, pH, insulin, and zinc on the mechanism of aggregation of hIAPP. The challenges posed by the transient nature of amyloid oligomers, their structural heterogeneity, and the complex nature of their interaction with lipid membranes have resulted in the development of a wide range of biophysical and chemical approaches to characterize the aggregation process. While the cellular processes and factors activating hIAPP-mediated cytotoxicity are still not clear, it has recently been suggested that its impaired turnover and cellular processing by proteasome and autophagy may contribute significantly toward toxic hIAPP accumulation and, eventually, β-cell death. Therefore, studies focusing on the restoration of hIAPP proteostasis may represent a promising arena for the design of effective therapies. In this review we discuss the current knowledge of the structures and pathology associated with hIAPP self-assembly and point out the opportunities for therapy that a detailed biochemical, biophysical, and cellular understanding of its aggregation may unveil.

Amyloid-Like Peptide Aggregates

Self-assembly of proteins and peptides into the amyloid fold is a widespread phenomenon in the natural world. The structural hallmark of self-assembly into amyloid fibrillar assemblies is the cross-beta motif, which conveys distinct morphological and mechanical properties. The amyloid fibril formation has contrasting results depending on the organism, in the sense that it can bestow an organism with the advantages of mechanical strength and improved functionality or, on the contrary, could give rise to pathological states. In this chapter we review the existing information on amyloid-like peptide aggregates, which could either be derived from protein sequences, but also could be rationally or de novo designed in order to self-assemble into amyloid fibrils under physiological conditions. Moreover, the development of self-assembled fibrillar biomaterials that are tailored for the desired properties towards applications in biomedical or environmental areas is extensively analyzed. We also review computational studies predicting the amyloid propensity of the natural amino acid sequences and the structure of amyloids, as well as designing novel functional amyloid materials.

Long-time methods for molecular dynamics simulations: Markov State Models and Milestoning

Molecular dynamics (MD) studies of biomolecules require the ability to simulate complex biochemical systems with an increasingly larger number of particles and for longer time scales, a problem that cannot be overcome by computational hardware advances alone. A main problem springs from the intrinsically high-dimensional and complex nature of the underlying free energy landscape of most systems, and from the necessity to sample accurately such landscapes for identifying kinetic and thermodynamic states in the configurations space, and for accurate calculations of both free energy differences and of the corresponding transition rates between states. Here, we review and present applications of two increasingly popular methods that allow long-time MD simulations of biomolecular systems that can open a broad spectrum of new studies. A first approach, Markov State Models (MSMs), relies on identifying a set of configuration states in which the system resides sufficiently long to relax and loose the memory of previous transitions, and on using simulations for mapping the underlying complex energy landscape and for extracting accurate thermodynamic and kinetic information. The Markovian independence of the underlying transition probabilities creates the opportunity to increase the sampling efficiency by using sets of appropriately initialized short simulations rather than typically long MD trajectories, which also enhances sampling. This allows MSM-based studies to unveil bio-molecular mechanisms and to estimate free energy barriers with high accuracy, in a manner that is both systematic and relatively automatic, which accounts for their increasing popularity. The second approach presented, Milestoning, targets accurate studies of the ensemble of pathways connecting specific end-states (e.g., reactants and products) in a similarly systematic, accurate and highly automatic manner. Applications presented range from studies of conformational dynamics and binding of amyloid-forming peptides, cell-penetrating peptides and the DFG-flip dynamics in Abl kinase. As highlighted by the increasing number of studies using both methods, we anticipate that they will open new avenues for the investigation of systematic sampling of reactions pathways and mechanisms occurring on longer time scales than currently accessible by purely computational hardware developments.

Amyloid Fibril Design: Limiting Structural Polymorphism in Alzheimer's Aβ Protofilaments

Nanoscale fibrils formed by amyloid peptides have a polymorphic character, adopting several types of molecular structures in similar growth conditions. As shown by experimental (e.g., solid-state NMR) and computational studies, amyloid fibril polymorphism hinders both the structural characterization of Alzheimer's Aβ amyloid protofilaments and fibrils at a molecular level, as well as the possible applications (e.g., development of drugs or biomarkers) that rely on similar, controlled molecular arrangements of the Aβ peptides in amyloid fibril structures. We have explored the use of several contact potentials for the efficient identification of minimal sequence mutations that could enhance the stability of specific fibril structures while simultaneously destabilizing competing topologies, controlling thus the amount of structural polymorphism in a rational way. We found that different types of contact potentials, while having only partial accuracy on their own, lead to similar results regarding ranking the compatibility of wild-type (WT) and mutated amyloid sequences with different fibril morphologies. This approach allows exhaustive screening and assessment of possible mutations and the identification of minimal consensus mutations that could stabilize fibrils with the desired topology at the expense of other topology types, a prediction that is further validated using atomistic molecular dynamics with explicit water molecules. We apply this two-step multiscale (i.e., residue and atomistic-level) approach to predict and validate mutations that could bias either parallel or antiparallel packing in the core Alzheimer's Aβ_9-40 amyloid fibril models based on solid-state NMR experiments. Besides shedding new light on the molecular origins of structural polymorphism in WT Aβ fibrils, our study could also lead to efficient tools for assisting future experimental approaches for amyloid fibril determination, and for the development of biomarkers or drugs aimed at interfering with the stability of amyloid fibrils, as well as for the future design of amyloid fibrils with a controlled (e.g., reduced) level of structural polymorphism.

Mechanistic perspective and functional activity of insulin in amylin aggregation

This work provides the first-ever complete atomic model of insulin–amylin aggregates, identifying the specific interactions that stabilize the insulin–amylin complex.

Insulin is a key regulatory polypeptide that is secreted from pancreatic β-cells and has several important effects on the synthesis of lipids, regulation of enzymatic activities, blood glucose levels and the prevention of hyperglycemia. Insulin was demonstrated to self-assemble into ordered amyloid fibrils upon repeated injections, although the possible biological significance of the supramolecular structures is enigmatic. Amylin is also an amyloidogenic polypeptide that is secreted from pancreatic β-cells and plays an important role in glycemic regulation preventing post-prandial spikes in blood glucose levels. These two amyloidogenic proteins are secreted together from the pancreas and have the ability to interact and produce insulin–amylin aggregates. So far, the molecular architecture of insulin–amylin complexes at the atomic resolution has been unknown. The current work identifies for the first time the specific π–π interactions between Y16 in insulin and F19 in amylin that contribute to the stability of the insulin–amylin complex, by using experimental and molecular modeling techniques. We performed additional experiments that verify the functional activity of insulin in amylin aggregation. Our findings illustrate for the first time the specific interactions between insulin and amylin aggregates at the atomic resolution and provide a new mechanistic perspective on the effect of insulin on amylin aggregation and may pave the way towards pharmacological intervention in this process.