Kinetics and mechanical stability of the fibril state control fibril formation time of polypeptide chains: A computational study

Substitution of Met-38 to Ile in γ-synuclein found in two patients with amyotrophic lateral sclerosis induces aggregation into amyloid

α-, β-, and γ-Synuclein are intrinsically disordered proteins implicated in physiological processes in the nervous system of vertebrates. α-synuclein (αSyn) is the amyloidogenic protein associated with Parkinson's disease and certain other neurodegenerative disorders. Intensive research has focused on the mechanisms that cause αSyn to form amyloid structures, identifying its NAC region as being necessary and sufficient for amyloid assembly. Recent work has shown that a 7-residue sequence (P1) is necessary for αSyn amyloid formation. Although γ-synuclein (γSyn) is 55% identical in sequence to αSyn and its pathological deposits are also observed in association with neurodegenerative conditions, γSyn is resilient to amyloid formation in vitro. Here, we report a rare single nucleotide polymorphism (SNP) in the SNCG gene encoding γSyn, found in two patients with amyotrophic lateral sclerosis (ALS). The SNP results in the substitution of Met38 with Ile in the P1 region of the protein. These individuals also had a second, common and nonpathological, SNP in SNCG resulting in the substitution of Glu110 with Val. In vitro studies demonstrate that the Ile38 variant accelerates amyloid fibril assembly. Contrastingly, Val110 retards fibril assembly and mitigates the effect of Ile38. Substitution of residue 38 with Leu had little effect, while Val retards, and Ala increases the rate of amyloid formation. Ile38 γSyn also results in the formation of γSyn-containing inclusions in cells. The results show how a single point substitution can enhance amyloid formation of γSyn and highlight the P1 region in driving amyloid formation in another synuclein family member.

Epitope alteration by small molecules and applications in drug discovery

Small molecules and antibodies are normally considered separately in drug discovery, except in the case of covalent conjugates. We unexpectedly discovered several small molecules that could inhibit or enhance antibody–epitope interactions which opens new possibilities in drug discovery and therapeutic modulation of auto-antibodies. We first discovered a small molecule, CRANAD-17, that enhanced the binding of an antibody to amyloid beta (Aβ), one of the major hallmarks of Alzheimer's disease, by stable triplex formation. Next, we found several small molecules that altered antibody–epitope interactions of tau and PD-L1 proteins, demonstrating the generality of this phenomenon. We report a new screening technology for ligand discovery, screening platform based on epitope alteration for drug discovery (SPEED), which is label-free for both the antibody and small molecule. SPEED, applied to an Aβ antibody, led to the discovery of a small molecule, GNF5837, that inhibits Aβ aggregation and another, obatoclax, that binds Aβ plaques and can serve as a fluorescent reporter in brain slices of AD mice. We also found a small molecule that altered the binding between Aβ and auto-antibodies from AD patient serum. SPEED reveals the sensitivity of antibody–epitope interactions to perturbation by small molecules and will have multiple applications in biotechnology and drug discovery.

A screening platform based on epitope alteration for drug discovery (SPEED).

Assessing the Stability of Biological Fibrils by Molecular-Scale Simulations

The nanomechanical characterization of several biological fibrils that are the result of protein aggregation via molecular dynamics simulation is nowadays feasible, and together with atomic force microscopy experiments has widened our understanding of the forces in the regime of pN-nN and system sizes of about hundreds of nanometers. Several methodologies have been developed to achieve this target, and they range from the atomistic representation via molecular force fields to coarse-grained strategies that provide comparable results with experiments in a systematic way. In this chapter, we discuss several methodologies for the calculation of mechanical parameters, such as the elastic constants of relevant biological systems. They are presented together with details about parameterization and current limitations. Then, we discuss some of the applications of such methodologies for the description of bacterial filament and β-amyloid systems. Finally, the latest lines of development are discussed.

Computational Models for the Study of Protein Aggregation

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Systematic Search for a Predictor for the Clinical Observables of Alzheimer's Disease

One of the prevailing life-threatening incurable neurodegenerative diseases that are presently endangering human society as a whole, and hence, baffling the entire spectrum of the scientific and pharmaceutical world, is Alzheimer's disease (AD). AD is a manifestation of self-assembly of both wild-type (sporadic) and mutated (familial) forms of the amyloid-β peptide, a proteolytic product of the amyloid precursor protein, where the self-assembly results in the genesis of pathogenic fibrillar aggregates. Currently prevailing diagnostic and hence therapeutic challenges originate from the unavailability of a specific predictor for clinical observables. The continuous emergence of novel pathogenic mutants with unpredictable phenotypes adds immensely to the nonspecific nature of the problem. The current research reports a simple physical parameter, the binding affinity of a protofilament to its protofibril, which predicts the clinical observables of familial AD with astounding accuracy and more importantly, without any adjustable parameters.

Nanomechanical Stability of Aβ Tetramers and Fibril-like Structures: Molecular Dynamics Simulations

Alzheimer's disease (AD) is a neurodegenerative disorder and one of the main causes of dementia. The disease is associated with amyloid beta (Aβ) peptide aggregation forming initial clusters and then fibril structure and plaques. Other neurodegenerative diseases such as type 2 diabetes, amyotrophic lateral sclerosis, and Parkinson's disease follow a similar mechanism. Therefore, inhibition of Aβ aggregation is considered an effective way to prevent AD. Recent experiments have provided evidence that oligomers are more toxic agents than mature fibrils, prompting researchers to investigate various factors that may influence their properties. One of these factors is nanomechanical stability, which plays an important role in the self-assembly of Aβ and possibly other proteins. This stability is also likely to be related to cell toxicity. In this work, we compare the mechanical stability of Aβ-tetramers and fibrillar structures using a structure-based coarse-grained (CG) approach and all-atom molecular dynamics simulation. Our results support the evidence for an increase in mechanical stability during the Aβ fibrillization process, which is consistent with in vitro AFM characterization of Aβ42 oligomers. Namely, using a CG model, we showed that the Young modulus of tetramers is lower than that of fibrils and, as follows from the experiment, is about 1 GPa. Hydrogen bonds are the dominant contribution to the detachment of one chain from the Aβ fibril fragment. They tend to be more organized along the pulling direction, whereas in the Aβ tetramers no preference is observed.

Enhancing the binding of the β-sheet breaker peptide LPFFD to the amyloid-β fibrils by aromatic modifications: A molecular dynamics simulation study

Alzheimer's is a fatal neurodegenerative disease for which there is no cure at present. The disease is characterized by the presence of plaques in the brains of a patient, which are composed mainly of aggregates of the amyloid-β peptide in the form of β-sheet fibrils. Here, we investigated the possibility of exploiting the superior binding ability of aromatic amino acids to a particular model of the amyloid-β fibrils. which is a difficult target for drug design. The β-sheet breaker peptide LPFFD was modified with aromatic amino acids and its binding to these fibrils was studied. We found that the orientation and the electrostatic complementarity of the modified peptide with respect to the fibrils played a crucial role in determining whether its binding was improved by the aromatic amino acids. The modified LPFFD peptides were able to bind to those fibril residues. which are important in the aggregation of amyloid-β peptides and thus can potentially inhibit the further aggregation of the amyloid-beta peptides by blocking their interactions. We found that the tryptophan modified LPFFD peptides had the best binding affinities. In most cases, the aromatic amino acids in the N-terminus of the modified peptides made more contacts with the fibrils than those in the C-terminus. We also found that increasing the aromatic content did not significantly improve the binding of the LPFFD peptide to the fibrils. Our study can serve as a basis for the design of novel peptide-based drugs for Alzheimer's disease in which aromatic interactions play an important role.

d-Retro Inverso Amylin and the Stability of Amylin Fibrils

Motivated by the role that amylin aggregates play in type-II diabetes, we compare the stability of regular amylin fibrils with the stability of fibrils where l-amino acid chains are replaced by d-retro inverso (DRI) amylin, that is, peptides where the sequence of amino acids is reversed, and at the same time, the l-amino acids are replaced by their mirror images. Our molecular dynamics simulations show that despite leading to only a marginal difference in the fibril structure and stability, aggregating DRI-amylin peptides have different patterns of contacts and hydrogen bonding. Because of these differences, DRI-amylin, when interacting with regular (l) amylin, alters the elongation process and lowers the stability of hybrid amylin fibrils. Our results not only suggest the potential use of DRI-amylin as an inhibitor of amylin fibril formation but also point to the possibility of using the insertion of DRI proteins in l-assemblies as a way to probe the role of certain kinds of hydrogen bonds in supramolecular assemblies or aggregates.

Revealing Cooperation between Knotted Conformation and Dimerization in Protein Stabilization by Molecular Dynamics Simulations

The topological knot is thought to play a stabilizing role in maintaining the global fold and nature of proteins with the underlying mechanism yet to be elucidated. Given that most proteins containing trefoil knots exist and function as homodimers with a large part of the dimer interface occupied by the knotted region, we reason that the knotted conformation cooperates with dimerization in protein stabilization. Here, we take YbeA from Escherichia coli as the knotted protein model, using molecular dynamics (MD) simulations to compare the stability of two pairs of dimeric proteins having the same sequence and secondary structures but differing in the presence or absence of a trefoil knot in each subunit. The dimer interface of YbeA is identified to involve favorable contacts among three α-helices (α1, α3, and α5), one of which (α5) is threaded through a loop connected with α3 to form the knot. Upon removal of the knot by appropriate change of the knot-making crossing of the polypeptide chain, relevant domains are less constrained and exhibit enhanced fluctuations to decrease contacts at the interface. Unknotted subunits are less compact and undergo structural changes to ease the dimer separation. Such a stabilizing effect is evidenced by steered MD simulations, showing that the mechanical force required for dimer separation is significantly reduced by removing the knot. In addition to the knotted conformation, dimerization further improves the protein stability by restricting the α1-α5 separation, which is defined as a leading step for protein unfolding. These results provide important insights into the structure-function relationship of dimerization in knotted proteins.

Pharmacophoric Site Identification and Inhibitor Design for Autotaxin

Autotaxin (ATX) is a potential drug target that is associated with inflammatory diseases and various cancers. In our previous studies, we have designed several inhibitors targeting ATX using computational and experimental approaches. Here, we have analyzed topological water networks (TWNs) in the binding pocket of ATX. TWN analysis revealed a pharmacophoric site inside the pocket. We designed and synthesized compounds considering the identified pharmacophoric site. Furthermore, we performed biological experiments to determine their ATX inhibitory activities. High potency of the designed compounds supports the predictions of the TWN analysis.

The Role of Structural Polymorphism in Driving the Mechanical Performance of the Alzheimer's Beta Amyloid Fibrils

Alzheimer's Disease (AD) is related with the abnormal aggregation of amyloid β-peptides Aβ₁₋₄₀ and Aβ₁₋₄₂, the latter having a polymorphic character which gives rise to U- or S-shaped fibrils. Elucidating the role played by the nanoscale-material architecture on the amyloid fibril stability is a crucial breakthrough to better understand the pathological nature of amyloid structures and to support the rational design of bio-inspired materials. The computational study here presented highlights the superior mechanical behavior of the S-architecture, characterized by a Young's modulus markedly higher than the U-shaped architecture. The S-architecture showed a higher mechanical resistance to the enforced deformation along the fibril axis, consequence of a better interchain hydrogen bonds' distribution. In conclusion, this study, focusing the attention on the pivotal multiscale relationship between molecular phenomena and material properties, suggests the S-shaped Aβ₁₋₄₂ species as a target of election in computational screen/design/optimization of effective aggregation modulators.

Mechanical and thermodynamic properties of Aβ42, Aβ40, and α-synuclein fibrils: a coarse-grained method to complement experimental studies

We perform molecular dynamics simulation on several relevant biological fibrils associated with neurodegenerative diseases such as Aβ₄₀, Aβ₄₂, and α-synuclein systems to obtain a molecular understanding and interpretation of nanomechanical characterization experiments. The computational method is versatile and addresses a new subarea within the mechanical characterization of heterogeneous soft materials. We investigate both the elastic and thermodynamic properties of the biological fibrils in order to substantiate experimental nanomechanical characterization techniques that are quickly developing and reaching dynamic imaging with video rate capabilities. The computational method qualitatively reproduces results of experiments with biological fibrils, validating its use in extrapolation to macroscopic material properties. Our computational techniques can be used for the co-design of new experiments aiming to unveil nanomechanical properties of biological fibrils from a point of view of molecular understanding. Our approach allows a comparison of diverse elastic properties based on different deformations , i.e., tensile (Y _L), shear (S), and indentation (Y _T) deformation. From our analysis, we find a significant elastic anisotropy between axial and transverse directions (i.e., Y _T > Y _L) for all systems. Interestingly, our results indicate a higher mechanostability of Aβ₄₂ fibrils compared to Aβ₄₀, suggesting a significant correlation between mechanical stability and aggregation propensity (rate) in amyloid systems. That is, the higher the mechanical stability the faster the fibril formation. Finally, we find that α-synuclein fibrils are thermally less stable than β-amyloid fibrils. We anticipate that our molecular-level analysis of the mechanical response under different deformation conditions for the range of fibrils considered here will provide significant insights for the experimental observations.

Role of Resultant Dipole Moment in Mechanical Dissociation of Biological Complexes

Protein-peptide interactions play essential roles in many cellular processes and their structural characterization is the major focus of current experimental and theoretical research. Two decades ago, it was proposed to employ the steered molecular dynamics (SMD) to assess the strength of protein-peptide interactions. The idea behind using SMD simulations is that the mechanical stability can be used as a promising and an efficient alternative to computationally highly demanding estimation of binding affinity. However, mechanical stability defined as a peak in force-extension profile depends on the choice of the pulling direction. Here we propose an uncommon choice of the pulling direction along resultant dipole moment (RDM) vector, which has not been explored in SMD simulations so far. Using explicit solvent all-atom MD simulations, we apply SMD technique to probe mechanical resistance of ligand-receptor system pulled along two different vectors. A novel pulling direction—when ligand unbinds along the RDM vector—results in stronger forces compared to commonly used ligand unbinding along center of masses vector. Our observation that RDM is one of the factors influencing the mechanical stability of protein-peptide complex can be used to improve the ranking of binding affinities by using mechanical stability as an effective scoring function.