Elucidating the 3D structures of Al(iii)-Aβ complexes: a template free strategy based on the pre-organization hypothesis

Computational 3D Models of Fe2+/3+-Aβ1-42 Complexes Associated with Alzheimer's Disease

The interaction between iron and amyloid-beta (Aβ) peptides has received significant attention in Alzheimer's disease (AD) research due to its potential implications in developing this pathology. However, the coordination preferences of iron and Aβ1-42 have not been thoroughly investigated or remain unknown. This study employs a computational protocol that combines homology modeling techniques with quantum mechanics (DTF-xTB) calculations to build and evaluate several 3D models of Fe2+/3+-Aβ1-42. Our results reveal well-defined complexes for both the metal and peptide moieties, and we discuss the molecular interactions stabilizing these complexes by elucidating the coordinating environments and binding preferences. These proposed models offer valuable insights into the role of iron in Alzheimer's disease (AD) pathology.

Computational Study of Amyloidβ42 Familial Mutations and Metal Interaction: Impact on Monomers and Aggregates Dynamical Behaviors

One of the main hallmarks of Alzheimer's Disease is the formation of β-amyloid plaques, whose formation may be enhanced by metal binding or the appearance of familial mutations. In the present study, the simultaneous effect of familial mutations (E22Q, E22G, E22K, and D23N) and binding to metal ions (Cu(II) or Al(III)) is studied at the Aβ42 monomeric and fibrillar levels. With the application of GaMD and MD simulations, it is observed that the effects of metal binding and mutations differ in the monomeric and fibrillar forms. In the monomeric structures, without metal binding, all mutations reduce the amount of α-helix and increase, in some cases, the β-sheet content. In the presence of Cu(II) and Al(III) metal ions, the peptide becomes less flexible, and the β-sheet content decreases in favor of forming α-helix motifs that stabilize the system through interhelical contacts. Regarding the fibrillar structures, mutations decrease the opening of the fiber in the vertical axis, thereby stabilizing the S-shaped structure of the fiber. This effect is, in general, enhanced upon metal binding. These results may explain the different Aβ42 aggregation patterns observed in familial mutations.

Influence of metal binding on the conformational landscape of neurofilament peptides

In order to understand the preferred modes of chelation in metal-binding peptides, quantum mechanical calculations can be used to compute energies, resulting in a hierarchy of binding affinities. These calculations often produce increasing stabilization energies the higher the coordination of the complex. However, as the coordination of a metal increases, the conformational freedom of the polypeptide chain is inevitably reduced, resulting in an entropic penalty. Estimating the magnitude of this penalty from the many different degrees of freedom of biomolecular systems is very challenging, and as a result this contribution to the free energy is often ignored. Here we explore this problem focusing on a family of phosphorylated neuropeptides that bind to aluminum. We find that there is a general negative correlation between both stabilization energy and entropy. Our results suggest that a subtle interplay between enthalpic and entropic forces will determine the population of the most favourable species. Additionally, we discuss the requirements for a possible "Metal Ion Hypothesis" based on our findings.

Influence of Metal Cations on the Viscoelastic Properties of Escherichia coli Biofilms

Biofilms frequently cause complications in various areas of human life, e.g., in medicine and in the food industry. More recently, biofilms are discussed as new types of living materials with tunable mechanical properties. In particular, Escherichia coli produces a matrix composed of amyloid-forming curli and phosphoethanolamine-modified cellulose fibers in response to suboptimal environmental conditions. It is currently unknown how the interaction between these fibers contributes to the overall mechanical properties of the formed biofilms and if extrinsic control parameters can be utilized to manipulate these properties. Using shear rheology, we show that biofilms formed by the E. coli K-12 strain AR3110 stiffen by a factor of 2 when exposed to the trivalent metal cations Al(III) and Fe(III), while no such response is observed for the bivalent cations Zn(II) and Ca(II). Strains producing only one matrix component did not show any stiffening response to either cation or even a small softening. No stiffening response was further observed when strains producing only one type of fiber were co-cultured or simply mixed after biofilm growth. These results suggest that the E. coli biofilm matrix is a uniquely structured composite material when both matrix fibers are produced from the same bacterium. While the exact interaction mechanism between curli, phosphoethanolamine-modified cellulose, and trivalent metal cations is currently not known, our results highlight the potential of using extrinsic parameters to understand and control the interplay between biofilm structure and mechanical properties. This will ultimately aid in the development of better strategies for controlling biofilm growth.

Role of Metal Cations of Copper, Iron, and Aluminum and Multifunctional Ligands in Alzheimer's Disease: Experimental and Computational Insights

Alzheimer's disease (AD) is the most common form of dementia, affecting millions of people around the world. Even though the causes of AD are not completely understood due to its multifactorial nature, some neuropathological hallmarks of its development have been related to the high concentration of some metal cations. These roles include the participation of these metal cations in the production of reactive oxygen species, which have been involved in neuronal damage. In order to avoid the increment in the oxidative stress, multifunctional ligands used to coordinate these metal cations have been proposed as a possible treatment to AD. In this review, we present the recent advances in experimental and computational works aiming to understand the role of two redox active and essential transition-metal cations (Cu and Fe) and one nonbiological metal (Al) and the recent proposals on the development of multifunctional ligands to stop or revert the damaging effects promoted by these metal cations.

Computational assessment of the impact of Cu(II) and Al(III) on β-amyloid42 fibrils: Binding sites, structural stability, and possible physiological implications

One of Alzheimer's disease major hallmarks is the aggregation of β-amyloid peptide, a process in which metal ions play an important role. In the present work, an integrative computational study has been performed to identify the metal-binding regions and determine the conformational impact of Cu(II) and Al(III) ion binding to the β-amyloid (Aβ₄₂) fibrillary structure. Through classical and Gaussian accelerated molecular dynamics, it has been observed that the metal-free fiber shows a hinge fan-like motion of the S-shaped structure, maintaining the general conformation. Upon metal coordination, distinctive patterns are observed depending on the metal. Cu(II) binds to the flexible N-terminal region and induces structural changes that could ultimately disrupt the fibrillary structure. In contrast, Al(III) binding takes place with the residues Glu22 and Asp23, and its binding reinforces the core stability of the system. These results give clues on the molecular impact of the interaction of metal ions with the aggregates and sustain their non-innocent roles in the evolution of the illness.

Impact of Cu(II) and Al(III) on the conformational landscape of amyloidβ1-42

Metal ions have been found to play an important role in the formation of extracellular β-amyloid plaques, a major hallmark of Alzheimer's disease. In the present study, the conformational landscape of Aβ42 with Al(iii) and Cu(ii) has been explored using Gaussian accelerated molecular dynamics. Both metals reduce the flexibility of the peptide and entail a higher structural organization, although to different degrees. As a general trend, Cu(ii) binding leads to an increased α-helix content and to the formation of two α-helices that tend to organize in a U-shape. By contrast, most Al(iii) complexes induce a decrease in helical content, leading to more extended structures that favor the appearance of transitory β-strands.

BioMetAll: Identifying Metal-Binding Sites in Proteins from Backbone Preorganization

With a large amount of research dedicated to decoding how metallic species bind to proteins, in silico methods are interesting allies for experimental procedures. To date, computational predictors mostly work by identifying the best possible sequence or structural match of the target protein with metal-binding templates. These approaches are fundamentally focused on the first coordination sphere of the metal. Here, we present the BioMetAll predictor that is based on a different postulate: the formation of a potential metal-binding site is related to the geometric organization of the protein backbone. We first report the set of convenient geometric descriptors of the backbone needed for the algorithm and their parameterization from a statistical analysis. Then, the successful benchmark of BioMetAll on a set of more than 90 metal-binding X-ray structures is presented. Because BioMetAll allows structural predictions regardless of the exact geometry of the side chains, it appears extremely valuable for systems whose structures (either experimental or theoretical) are not optimal for metal-binding sites. We report here its application on three different challenging cases: (i) the modulation of metal-binding sites during conformational transition in human serum albumin, (ii) the identification of possible routes of metal migration in hemocyanins, and (iii) the prediction of mutations to generate convenient metal-binding sites for de novo biocatalysts. This study shows that BioMetAll offers a versatile platform for numerous fields of research at the interface between inorganic chemistry and biology and allows to highlight the role of the preorganization of the protein backbone as a marker for metal binding. BioMetAll is an open-source application available at https://github.com/insilichem/biometall.

Theoretical characterization of Al(III) binding to KSPVPKSPVEEKG: Insights into the propensity of aluminum to interact with key sequences for neurofilament formation

Classical molecular dynamic simulations and density functional theory are used to unveil the interaction of aluminum with various phosphorylated derivatives of the fragment KSPVPKSPVEEKG (NF13), a major multiphosphorylation domain of human neurofilament medium (NFM). Our calculations reveal the rich coordination chemistry of the resultant structures with a clear tendency of aluminum to form multidentate structures, acting as a bridging agent between different sidechains and altering the local secondary structure around the binding site. Our evaluation of binding energies allows us to determine that phosphorylation has an increase in the affinity of these peptides towards aluminum, although the interaction is not as strong as well-known chelators of aluminum in biological systems. Finally, the presence of hydroxides in the first solvation layer has a clear damping effect on the binding affinities. Our results help in elucidating the potential structures than can be formed between this exogenous neurotoxic metal and key sequences for the formation of neurofilament tangles, which are behind of some of the most important degenerative diseases.

Imaging of aluminium and amyloid β in neurodegenerative disease

Objectives

Recent research has confirmed the presence of aluminium in human brain tissue. Quantitative analyses suggest increased brain aluminium content in a number of neurodegenerative diseases including familial Alzheimer's disease, congophilic amyloid angiopathy, epilepsy and autism. Complementary aluminium-specific fluorescence microscopy identifies the location of aluminium in human brain tissue and demonstrates significant differences in distribution between diseases. Herein we combine these approaches in investigating associations between aluminium in human brain tissue and specific disease-associated neuropathologies.

Methods

We have used aluminium-specific fluorescence microscopy, Congo red staining using light and polarised light and thioflavin S fluorescence microscopy on serial sections of brain tissues to identify co-localisation of aluminium and amyloid β and tau neuropathology.

Results

A combination of light, polarised and fluorescence microscopy demonstrates an intimate relationship between aluminium and amyloid β in familial Alzheimer's disease but not in other conditions and diseases, such as congophilic amyloid angiopathy and autism. We demonstrate preliminary evidence of amyloid β pathology, including associations with vasculature and parenchymal tissues, in autism in tissues heavily loaded with aluminium.

Conclusion

We suggest that complementary aluminium-specific fluorescence microscopy may reveal important information about the putative toxicity of aluminium in neurodegenerative and neurodevelopmental disorders.

Quantum chemical molecular dynamics and metadynamics simulation of aluminium binding to amyloid-β and related peptides

We report semi-empirical tight-binding simulations of the interaction between Al(III) and biologically relevant peptides. The GFN2-XTB method is shown to accurately reproduce previously reported and density functional theory (DFT)-calculated geometries of model systems. Molecular dynamics simulations based on this method are able to sample peptide flexibility over timescales of up to nanoseconds, but these timescales are insufficient to explore potential changes in metal-peptide binding modes. To achieve this, metadynamics simulations using root mean square deviation as a collective variable were employed. With suitably chosen biasing potentials, these are able to efficiently explore diverse coordination modes, for instance, through Glu and/or Asp residues in a model peptide. Using these methods, we find that Al(III) binding to the N-terminal sequence of amyloid-β is highly fluxional, with all acidic sidechains and several backbone oxygens participating in coordination. We also show that such simulations could provide a means to predict a priori possible binding modes as a precursor to longer, atomistic simulations.

Neurotoxic effects of aluminum are associated with its interference with estrogen receptors signaling

Aluminum compounds have been observed in various brain regions, and their accumulation has been associated with many neurodegenerative disorders. Neurotoxic effects of aluminum are attributed to reactive oxygen species generation, induction of apoptosis and inflammatory reactions activation. Metalloestrogen activity of aluminum has also been linked to breast cancer progression and metastasis. In this study, taking into account the anti-apoptotic and anti-oxidant activities of estrogens in neuronal cells, which are mediated by estrogen receptors, the possible estrogenic activity of aluminum in SH-SY5Y neuroblastoma cells was studied. Our results showed that aluminum in the form of aluminum chlorohydrate (ACH) exhibited no effect on estrogen receptors transcriptional activation, and differential effect on estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) protein levels. ACH caused reduction in ERβ protein levels, and increase in its mitochondrial localization. ACH-induced reduction in ERβ protein level may be linked, at least in part, to the ACH-induced increase in ERα protein level. This statement is based on our observations showing aluminum-induced reduction in the E2-induced increase in ERα S118 phosphorylation, in MCF-7 and SH-SH5Y cells. Phosphorylation at S118 residue is known to be associated with inhibition of the ubiquitin-induced proteolytic degradation of ERα, leading to its accumulation. Since it is known that ERα negatively regulate ERβ expression, increase in ERα, may contribute to reduction in ERβ levels and subsequent weakening of its anti-apoptotic and anti-oxidant activity, justified by the observed reduction in procaspase 9, mitochondrial cytochrome c, Bcl-2, Bcl-xL and mitochondrial thioredoxin protein level, as well as by the increase in proapoptotic BAX level, in ACH treated SH-SY5Y cells. In addition, increase in mitochondrial ERβ localization may also trigger mitochondrial metabolism, suppress biosynthetic process of gluconeogenesis, as indicated by the observed reduction in the phosphoenolpyruvate carboxykinase protein level, and eventually lead to increase in reactive oxygen species (ROS) generation, known to be implicated in aluminum induced neurodegeneration. This statement was verified by the observed ACH-induced increase in ERβ mitochondrial localization, induction of the mitochondrial membrane depolarization and increase in ROS production, in neuronal-like differentiated SH-SY5Y cells.

The interaction of aluminum with catecholamine-based neurotransmitters: can the formation of these species be considered a potential risk factor for neurodegenerative diseases?

The potential neurotoxic role of Al(iii) and its proposed link with the insurgence of Alzheimer's Disease (AD) have attracted increasing interest towards the determination of the nature of bioligands that are propitious to interact with aluminum. Among them, catecholamine-based neurotransmitters have been proposed to be sensitive to the presence of this non-essential metal ion in the brain. In the present work, we characterize several aluminum-catecholamine complexes in various stoichiometries, determining their structure and thermodynamics of formation. For this purpose, we apply a recently validated computational protocol with results that show a remarkably good agreement with the available experimental data. In particular, we employ Density Functional Theory (DFT) in conjunction with continuum solvation models to calculate complexation energies of aluminum for a set of four important catecholamines: l-DOPA, dopamine, noradrenaline and adrenaline. In addition, by means of the Quantum Theory of Atoms in Molecules (QTAIM) and Energy Decomposition Analysis (EDA) we assessed the nature of the Al-ligand interactions, finding mainly ionic bonds with an important degree of covalent character. Our results point at the possibility of the formation of aluminum-catecholamine complexes with favorable formation energies, even when proton/aluminum competition is taken into account. Indeed, we found that these catecholamines are better aluminum binders than catechol at physiological pH, because of the electron withdrawing effect of the positively-charged amine that decreases their deprotonation penalty with respect to catechol. However, overall, our results show that, in an open biological environment, the formation of Al-catecholamine complexes is not thermodynamically competitive when compared with the formation of other aluminum species in solution such as Al-hydroxide, or when considering other endogenous/exogenous Al(iii) ligands such as citrate, deferiprone and EDTA. In summary, we rule out the possibility, suggested by some authors, that the formation of Al-catecholamine complexes in solution might be behind some of the toxic roles attributed to aluminum in the brain. An up-to-date view of the catecholamine biosynthesis pathway with sites of aluminum interference (according to the current literature) is presented. Alternative mechanisms that might explain the deleterious effects of this metal on the catecholamine route are thoroughly discussed, and new hypotheses that should be investigated in future are proposed.

Molecular dynamics simulation of aluminium binding to amyloid-β and its effect on peptide structure

Multiple microsecond-length molecular dynamics simulations of complexes of Al(III) with amyloid-β (Aβ) peptides of varying length are reported, employing a non-bonded model of Al-coordination to the peptide, which is modelled using the AMBER ff14SB forcefield. Individual simulations reach equilibrium within 100 to 400 ns, as determined by root mean square deviations, leading to between 2.1 and 2.7 μs of equilibrated data. These reveal a compact set of configurations, with radius of gyration similar to that of the metal free peptide but larger than complexes with Cu, Fe and Zn. Strong coordination through acidic residues Glu3, Asp7 and Glu11 is maintained throughout all trajectories, leading to average coordination numbers of approximately 4 to 5. Helical conformations predominate, particularly in the longer Al-Aβ40 and Al-Aβ42 peptides, while β-strand forms are rare. Binding of the small, highly charged Al(III) ion to acidic residues in the N-terminus strongly disrupts their ability to engage in salt bridges, whereas residues outside the metal binding region engage in salt bridges to similar extent to the metal-free peptide, including the Asp23-Lys28 bridge known to be important for formation of fibrils. High helical content and disruption of salt bridges leads to characteristic tertiary structure, as shown by heat maps of contact between residues as well as representative clusters of trajectories.

Simple Coordination Geometry Descriptors Allow to Accurately Predict Metal-Binding Sites in Proteins

With more than a third of the genome encoding for metal-containing biomolecules, the in silico prediction of how metal ions bind to proteins is crucial in chemistry, biology, and medicine. To date, algorithms for metal-binding site prediction are mainly based on sequence analysis. Those methods have reached enough quality to predict the correct region of the protein and the coordinating residues involved in metal-binding, but they do not provide three-dimensional (3D) models. On the contrary, the prediction of accurate 3D models for protein-metal adducts by structural bioinformatics and molecular modeling techniques is still a challenge. Here, we present an update of our multipurpose molecular modeling suite, GaudiMM, to locate metal-binding sites in proteins. The approach is benchmarked on 105 X-ray structures with resolution lower than 2.0 Å. Results predict the correct binding site of the metal in the biological scaffold for all the entries in the data set. Generated 3D models of the protein-metal coordination complexes reach root-mean-square deviation values under 1.0 Å between calculated and experimental structures. The whole process is purely based on finding poses that satisfy metal-derived geometrical rules without needing sequence or fine electronic inputs. Additional post-optimizations, including receptor flexibility, have been tested and suggest that more extensive searches, required when the host structures present a low level of pre-organization, are also possible. With this new update, GaudiMM is now able to look for metal-binding sites in biological scaffolds and clearly shows how explicitly considering the geometric particularities of the first coordination sphere of the metal in a docking process provides excellent results.

A Fragment Quantum Mechanical Method for Metalloproteins

An accurate energy calculation of metalloprotein is of crucial importance and also a theoretical challenge. In this work, a metal molecular fractionation with conjugate caps (metal-MFCC) approach is developed for efficient linear-scaling quantum calculation of potential energy and atomic forces of metalloprotein. In this approach, the potential energy of a given protein is calculated by a linear combination of potential energies of the neighboring residues, two-body interaction energy between non-neighboring residues that are spatially in close contact and the potential energy of the metal binding group. The calculation of each fragment is embedded in a field of point charges representing the remaining protein environment. Numerical studies were carried out to check the performance of this method, and the calculated potential energies and atomic forces all show excellent agreement with the full system calculations at the M06-2X/6-31G(d) level. By combining the energy calculation with molecular dynamic simulation, we performed an ab initio structural optimization for a zinc finger protein with high efficiency. The present metal-MFCC approach is linear-scaling with a low prefactor and trivially parallelizable. The individual fragment typically contains about 50 atoms, and it is thus possible to be calculated at higher levels of the quantum chemistry method. This fragment method can be routinely applied to perform structural optimization and ab initio molecular dynamic simulation for metalloproteins of any size.

Design, Synthesis, and Evaluation of Orally Bioavailable Quinoline-Indole Derivatives as Innovative Multitarget-Directed Ligands: Promotion of Cell Proliferation in the Adult Murine Hippocampus for the Treatment of Alzheimer's Disease

A novel series of quinoline-indole derivatives were synthesized and evaluated as multitarget-directed ligands for the treatment of Alzheimer's disease (AD). Biological evaluation revealed that the derivatives had multifunctional profiles including antioxidant effects, blood-brain barrier (BBB) penetration, biometal chelation, Aβ aggregation modulation, neurotrophic and neuroprotective properties. Moreover, several representative target derivatives demonstrated hippocampal cell proliferation in living adult mice by intracerebroventricular (icv) injection or oral administration. Further drug-like property analysis demonstrated that the optimized compound, 8d (WI-1758), had liver microsomal metabolic stability, was well tolerated (>2000 mg/kg), and had a rational pharmacokinetic profile, as well as an oral bioavailability of 14.1% and a positive log BB (-0.19) to cross the BBB in vivo. Pharmacodynamics studies demonstrated that chronic oral administration of 8d·HCl substantially ameliorated the cognitive and spatial memory deficits in APP/PS1 AD mice and noticeably reduced overall cerebral β-amyloid deposits.

Tuning the affinity of catechols and salicylic acids towards Al(iii): characterization of Al–chelator interactions

Aluminum is a non-essential element in the human body with unclear harmful effects; therefore, the design and tuning of new and efficient Al(iii) chelating agents is a subject of paramount importance nowadays.