Predicting the Structure of Enzymes with Metal Cofactors: The Example of [FeFe] Hydrogenases.

The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron-sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron-sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron-sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron-sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix.

Amyloid-ß Tetramers and Divalent Cations at the Membrane/Water Interface: Simple Models Support a Functional Role.

Charge polarization at the membrane interface is a fundamental process in biology. Despite the lower concentration compared to the abundant monovalent ions, the relative abundance of divalent cations (Ca2+, Mg2+, Zn2+, Fe2+, Cu2+) in particular spaces, such as the neuron synapse, raised many questions on the possible effects of free multivalent ions and of the required protection of membranes by the eventual defects caused by the free forms of the cations. In this work, we first applied a recent realistic model of divalent cations to a well-investigated model of a polar lipid bilayer, di-myristoyl phosphatidyl choline (DMPC). The full atomistic model allows a fairly good description of changes in the hydration of charged and polar groups upon the association of cations to lipid atoms. The lipid-bound configurations were analyzed in detail. In parallel, amyloid-ß 1-42 (Aß42) peptides assembled into tetramers were modeled at the surface of the same bilayer. Two of the protein tetramers' models were loaded with four Cu2+ ions, the latter bound as in DMPC-free Aß42 oligomers. The two Cu-bound models differ in the binding topology: one with each Cu ion binding each of the monomers in the tetramer; one with pairs of Cu ions linking two monomers into dimers, forming tetramers as dimers of dimers. The models here described provide hints on the possible role of Cu ions in synaptic plasticity and of Aß42 oligomers in storing the same ions away from lipids. The release of structurally disordered peptides in the synapse can be a mechanism to recover ion homeostasis and lipid membranes from changes in the divalent cation concentration.

Probing protein stability: towards a computational atomistic, reliable, affordable, and improvable model.

We present an improved application of a recently proposed computational method designed to evaluate the change of free energy as a function of the average value of a suitably chosen collective variable in proteins. The method is based on a full atomistic description of the protein and its environment. The goal is to understand how the protein melting temperature changes upon single-point mutations, because the sign of the temperature variation will allow us to discriminate stabilizing vs. destabilizing mutations in protein sequences. In this refined application the method is based on altruistic well-tempered metadynamics, a variant of multiple-walkers metadynamics. The resulting metastatistics is then modulated by the maximal constrained entropy principle. The latter turns out to be especially helpful in free-energy calculations as it is able to alleviate the severe limitations of metadynamics in properly sampling folded and unfolded configurations. In this work we apply the computational strategy outlined above in the case of the bovine pancreatic trypsin inhibitor, a well-studied small protein, which is a reference for computer simulations since decades. We compute the variation of the melting temperature characterizing the folding-unfolding process between the wild-type protein and two of its single-point mutations that are seen to have opposite effect on the free energy changes. The same approach is used for free energy difference calculations between a truncated form of frataxin and a set of five of its variants. Simulation data are compared to in vitro experiments. In all cases the sign of the change of melting temperature is reproduced, under the further approximation of using an empirical effective mean-field to average out protein-solvent interactions.

Probing Reactivity with External Forces: The Case of Nitroacetamides in Water.

Many computational methods have been applied to interpret and predict changes in reactivity by slight modifications of a given molecular scaffold. We describe a novel and simple method based on approximate density-functional theory of valence electrons that can be applied within a large high-performance computational infrastructure to probe such changes using a statistical sample of molecular configurations, including the solvent. All the used computational tools are fully open-source. Following our previous application, we are able to explain the high acidity of C-H bond at α position in nitro compounds when the amide linkage an ammonium group is inserted into the α substituent.

Amyloid ß Dodecamer Disrupts the Neuronal Membrane More Strongly than the Mature Fibril: Understanding the Role of Oligomers in Neurotoxicity.

The amyloid cascade hypothesis states that senile plaques, composed of amyloid ß (Aß) fibrils, play a key role in Alzheimer's disease (AD). However, recent experiments have shown that Aß oligomers are more toxic to neurons than highly ordered fibrils. The molecular mechanism underlying this observation remains largely unknown. One of the possible scenarios for neurotoxicity is that Aß peptides create pores in the lipid membrane that allow Ca2+ ions to enter cells, resulting in a signal of cell apoptosis. Hence, one might think that oligomers are more toxic due to their higher ability to create ion channels than fibrils. In this work, we study the effect of Aß42 dodecamer and fibrils on a neuronal membrane, which is similar to that observed in AD patients, using all-atom molecular dynamics simulations. Due to short simulation times, we cannot observe the formation of pores, but useful insight on the early events of this process has been obtained. Namely, we showed that dodecamer distorts the lipid membrane to a greater extent than fibrils, which may indicate that ion channels can be more easily formed in the presence of oligomers. Based on this result, we anticipate that oligomers are more toxic than mature fibrils, as observed experimentally. Moreover, the Aß-membrane interaction was found to be governed by the repulsive electrostatic interaction between Aß and the ganglioside GM1 lipid. We calculated the bending and compressibility modulus of the membrane in the absence of Aß and obtained good agreement with the experiment. We predict that the dodecamer will increase the compressibility modulus but has little effect on the bending modulus. Due to the weak interaction with the membrane, fibrils insignificantly change the membrane elastic properties.

Modelling Protein Plasticity: The Example of Frataxin and Its Variants.

Frataxin (FXN) is a protein involved in storage and delivery of iron in the mitochondria. Single-point mutations in the FXN gene lead to reduced production of functional frataxin, with the consequent dyshomeostasis of iron. FXN variants are at the basis of neurological impairment (the Friedreich's ataxia) and several types of cancer. By using altruistic metadynamics in conjunction with the maximal constrained entropy principle, we estimate the change of free energy in the protein unfolding of frataxin and of some of its pathological mutants. The sampled configurations highlight differences between the wild-type and mutated sequences in the stability of the folded state. In partial agreement with thermodynamic experiments, where most of the analyzed variants are characterized by lower thermal stability compared to wild type, the D104G variant is found with a stability comparable to the wild-type sequence and a lower water-accessible surface area. These observations, obtained with the new approach we propose in our work, point to a functional switch, affected by single-point mutations, of frataxin from iron storage to iron release. The method is suitable to investigate wide structural changes in proteins in general, after a proper tuning of the chosen collective variable used to perform the transition.

Aggregates Sealed by Ions.

The chapter draws a line connecting some recent results where the role of ions is found essential in sealing more or less pre-organized assemblies of macromolecules. We draw some dots along the line that starts from the effect of the ionic atmosphere and ends with the chemical bonds formed by multivalent ions acting as bridges between macromolecules. Many of these dots involve structurally disordered peptides and disordered regions of proteins. A broad perspective of the role of multivalent ions in assisting the assembly process, shifting population in polymorphic states, and sealing protein aggregates, is suggested.

Zn-Induced Interactions Between SARS-CoV-2 orf7a and BST2/Tetherin.

We present in this work a first X-ray Absorption Spectroscopy study of the interactions of Zn with human BST2/tetherin and SARS-CoV-2 orf7a proteins as well as with some of their complexes. The analysis of the XANES region of the measured spectra shows that Zn binds to BST2, as well as to orf7a, thus resulting in the formation of BST2-orf7a complexes. This structural information confirms the the conjecture, recently put forward by some of the present Authors, according to which the accessory orf7a (and possibly also orf8) viral protein are capable of interfering with the BST2 antiviral activity. Our explanation for this behavior is that, when BST2 gets in contact with Zn bound to the orf7a Cys15 ligand, it has the ability of displacing the metal owing to the creation of a new disulfide bridge across the two proteins. The formation of this BST2-orf7a complex destabilizes BST2 dimerization, thus impairing the antiviral activity of the latter.

Measuring Shared Electrons in Extended Molecular Systems: Covalent Bonds from Plane-Wave Representation of Wave Function.

In the study of materials and macromolecules by first-principle methods, the bond order is a useful tool to represent molecules, bulk materials and interfaces in terms of simple chemical concepts. Despite the availability of several methods to compute the bond order, most applications have been limited to small systems because a high spatial resolution of the wave function and an all-electron representation of the electron density are typically required. Both limitations are critical for large-scale atomistic calculations, even within approximate density-functional theory (DFT) approaches. In this work, we describe our methodology to quickly compute delocalization indices for all atomic pairs, while keeping the same representation of the wave function used in most compute-intensive DFT calculations on high-performance computing equipment. We describe our implementation into a post-processing tool, designed to work with Quantum ESPRESSO, a popular open-source DFT package. In this way, we recover a description in terms of covalent bonds from a representation of wave function containing no explicit information about atomic types and positions.

Probing the Structure of Toxic Amyloid-ß Oligomers with Electron Spin Resonance and Molecular Modeling.

Structural models of the toxic species involved in the development of Alzheimer's disease are of utmost importance to understand the molecular mechanism and to describe early biomarkers of the disease. Among toxic species, soluble oligomers of amyloid-ß (Aß) peptides are particularly important, because they are responsible for spreading cell damages over brain regions, thus rapidly impairing brain functions. In this work we obtain structural information on a carefully prepared Aß(1-42) sample, representing a toxic state for cell cultures, by combining electron spin resonance spectroscopy and computational models. We exploited the binding of Cu2+ to Aß(1-42) and used copper as a probe for estimating Cu-Cu distances in the oligomers by applying double electron-electron resonance (DEER) pulse sequence. The DEER trace of this sample displays a unique feature that fits well with structural models of oligomers formed by Cu-cross-linked peptide dimers. Because Cu is bound to the Aß(1-42) N-terminus, for the first time structural constraints that are missing in reported studies are provided at physiological conditions for the Aß N-termini. These constraints suggest the Aß(1-42) dimer as the building block of soluble oligomers, thus changing the scenario for any kinetic model of Aß(1-42) aggregation.

Polyphenols as Potential Metal Chelation Compounds Against Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disease affecting more than 50 million people worldwide. The pathology of this multifactorial disease is primarily characterized by the formation of amyloid-ß (Aß) aggregates; however, other etiological factors including metal dyshomeostasis, specifically copper (Cu), zinc (Zn), and iron (Fe), play critical role in disease progression. Because these transition metal ions are important for cellular function, their imbalance can cause oxidative stress that leads to cellular death and eventual cognitive decay. Importantly, these transition metal ions can interact with the amyloid-ß protein precursor (AßPP) and Aß42 peptide, affecting Aß aggregation and increasing its neurotoxicity. Considering how metal dyshomeostasis may substantially contribute to AD, this review discusses polyphenols and the underlying chemical principles that may enable them to act as natural chelators. Furthermore, polyphenols have various therapeutic effects, including antioxidant activity, metal chelation, mitochondrial function, and anti-amyloidogenic activity. These combined therapeutic effects of polyphenols make them strong candidates for a moderate chelation-based therapy for AD.

SARS-CoV-2 Virion Stabilization by Zn Binding.

Zinc plays a crucial role in the process of virion maturation inside the host cell. The accessory Cys-rich proteins expressed in SARS-CoV-2 by genes ORF7a and ORF8 are likely involved in zinc binding and in interactions with cellular antigens activated by extensive disulfide bonds. In this report we provide a proof of concept for the feasibility of a structural study of orf7a and orf8 proteins. A conceivable hypothesis is that lack of cellular zinc, or substitution thereof, might lead to a significant slowing down of viral maturation.

Emergence of Barrel Motif in Amyloid-ß Trimer: A Computational Study.

Amyloid-ß (Aß) peptides form assemblies that are pathological hallmarks of Alzheimer's disease. Aß oligomers are soluble, mobile, and toxic forms of the peptide that act in the extracellular space before assembling into protofibrils and fibrils. Therefore, oligomers play an important role in the mechanism of Alzheimer's disease. Since it is difficult to determine by experiment the atomic structures of oligomers, which accumulate fast and are polymorphic, computer simulation is a useful tool to investigate elusive oligomers' structures. In this work, we report extended all-atom molecular dynamics simulations, both canonical and replica exchange, of Aß(1-42) trimer starting from two different initial conformations: (i) the pose produced by the best docking of a monomer aside of a dimer (simulation 1), representing oligomers freshly formed by assembling monomers, and (ii) a configuration extracted from an experimental mature fibril structure (simulation 2), representing settled oligomers in equilibrium with extended fibrils. We showed that in simulation 1, regions with small ß-barrels are populated, indicating the chance of spontaneous formation of domains resembling channel-like structures. These structural domains are alternative to those more representative of mature fibrils (simulation 2), the latter showing a stable bundle of C-termini that is not sampled in simulation 1. Moreover, trimer of Aß(1-42) can form internal pores that are large enough to be accessed by water molecules and Ca2+ ions.

Computational Model to Unravel the Function of Amyloid-ß Peptides in Contact with a Phospholipid Membrane.

Divalent cations have a strong impact on the properties of phospholipid membranes, where amyloid-ß peptides exert effects related to possible functional or pathological roles. In this work, we use an atomistic computational model of dimyristoyl-phosphatidylcholine (DMPC) membrane bilayers. We perturb this model with a simple model of divalent cations (Mg2+) and with a single amyloid-ß (Aß) peptide of 42 residues, both with and without a single Cu2+ ion bound to the N-terminus. In agreement with the experimental results reported in the literature, the model confirms that divalent cations locally destabilize the DMPC membrane bilayer and, for the first time, that the monomeric form of Aß helps in avoiding the interactions between divalent cations and DMPC, preventing significant effects on the DMPC bilayer properties. These results are discussed in the frame of a protective role of the diluted Aß peptide floating around phospholipid membranes.

Nanoscopic insights into the surface conformation of neurotoxic amyloid ß oligomers.

Raman spectroscopy assisted by localized plasmon resonances generating effective hot spots at the gaps between intertwined silver nanowires is herein adopted to unravel characteristic molecular motifs on the surface of Aß42 misfolded oligomers that are critical in driving intermolecular interactions in neurodegeneration.

Dealing with Cu reduction in X-ray absorption spectroscopy experiments.

In this paper we prove in the exemplary case of the amyloid-ß peptide in complex with Cu(ii) that at the current low temperatures employed in XAS experiments, the time needed for collecting a good quality XAS spectrum is significantly shorter than the time after which structural damage becomes appreciable. Our method takes advantage of the well-known circumstance that the transition of Cu from the oxidized to the reduced form under ionizing radiation can be quantified by monitoring a characteristic peak in the pre-edge region. We show that there exists a sufficiently large time window in which good XAS spectra can be acquired before the structure around the oxidized Cu(ii) ion reorganizes itself into the reduced Cu(i) "resting" structure. We suggest that similar considerations apply to other cases of biological interest, especially when dealing with macromolecules in complex with transition metal ions.

Computational models explain how copper binding to amyloid-ß peptide oligomers enhances oxidative pathways.

Amyloid-ß (Aß) peptides are intrinsically disordered peptides and their aggregation is the major hallmark of Alzheimer's disease (AD) development. The interactions between copper ions and Aß peptides create catalysts that activate the production of reactive oxygen species in the synaptic region, a reactivity that is strongly related to AD onset. Recent experimental work [Gu et al., Sci. Rep., 2018, 8(1), 16190] confirmed that the oxidative reactivity of Cu-Aß catalyzes the formation of Tyr-Tyr crosslinks in peptide dimers. This work provides a structural basis to these observations, describing structures of Cu-Aß dimers that enhance the propagation of the oxidative pathways activated around the Cu center. Among these, the formation of Tyr-Tyr crosslinks becomes more likely when previous crosslinks involve Cu forming bridges between different peptides. Peptides are, therefore, easily assembled into dimers and tetramers, the latter being dimers of dimers. The size of such dimers and tetramers fits with ion mobility mass spectrometry results [Sitkiewicz et al., J. Mol. Biol., 2014, 426(15), 2871].

Understanding the Exceptional Properties of Nitroacetamides in Water: A Computational Model Including the Solvent.

Proton transfer in water involving C⁻H bonds is a challenge and nitro compounds have been studied for many years as good examples. The effect of substituents on acidity of protons geminal to the nitro group is exploited here with new p K a measurements and electronic structure models, the latter including explicit water environment. Substituents with the amide moiety display an exceptional combination of acidity and solubility in water. In order to find a rationale for the unexpected p K a changes in the (ZZ ' )NCO- substituents, we measured and modeled the p K a with Z=Z ' =H and Z=Z ' =methyl. The dominant contribution to the observed p K a can be understood with advanced computational experiments, where the geminal proton is smoothly moved to the solvent bath. These models, mostly based on density-functional theory (DFT), include the explicit solvent (water) and statistical thermal fluctuations. As a first approximation, the change of p K a can be correlated with the average energy difference between the two tautomeric forms (aci and nitro, respectively). The contribution of the solvent molecules interacting with the solute to the proton transfer mechanism is made evident.

Multi-scale theoretical approach to X-ray absorption spectra in disordered systems: an application to the study of Zn(ii) in water.

We develop a multi-scale theoretical approach aimed at calculating from first principles X-ray absorption spectra of liquid solutions and disordered systems. We test the method by considering the paradigmatic case of Zn(ii) in water which, besides being relevant in itself, is also of interest for biology. With the help of classical molecular dynamics simulations we start by producing bunches of configurations differing for the Zn(ii)-water coordination mode. Different coordination modes are obtained by making use of the so-called dummy atoms method. From the collected molecular dynamics trajectories, snapshots of a more manageable subsystem encompassing the metal site and two solvation layers are cut out. Density functional theory is used to optimize and relax these reduced system configurations employing a uniform dielectric to mimic the surrounding bulk liquid water. On the resulting structures, fully quantum mechanical X-ray absorption spectra calculations are performed by including core-hole effects and core-level shifts. The proposed approach does not rely on any guessing or fitting of the force field or of the atomic positions of the system. The comparison of the theoretically computed spectrum with the experimental Zn K-edge XANES data unambiguously demonstrates that among the different a priori possible geometries, Zn(ii) in water lives in an octahedral coordination mode.

Copper Binding Induces Polymorphism in Amyloid-ß Peptide: Results of Computational Models.

Amyloid-ß (Aß) peptides are intrinsically disordered peptides, and their aggregation is the hallmark of Alzheimer's disease development. The propensity of the Aß peptide to intermolecular interactions, the latter favoring different types of oligomers and aggregated forms, has been the object of a huge number of studies. Several facts are now established: the presence of large amount of d-block (M) ions (Zn, Cu, and Fe) in the aggregated forms; the 1:1 M/Aß ratio favors the formation of amorphous aggregates, with an aggregation rate lower than that in the absence of such ions. In particular, statistical models describing the interactions between copper and amyloid peptides are mandatory to explain the relationship between neurodegeneration, copper dyshomeostasis, and overproduction of reactive oxygen species, the latter event occurring with aging. In this work, we show, by replica-exchange molecular dynamics simulations, that a copper ion (Cu2+) bound as in the experimentally observed prevailing coordination enhances the probability of closed structures that hinder the formation of extended intermolecular hydrogen bonds that stabilize fibrillar ordered aggregated forms. On the other hand, this effect enhances the catalytic role of the complex during the lifetime of soluble forms.