Elucidating the role of water in collagen self-assembly by isotopically modulating collagen hydration.

Water is known to play an important role in collagen self-assembly, but it is still largely unclear how water-collagen interactions influence the assembly process and determine the fibril network properties. Here, we use the H[Formula: see text]O/D[Formula: see text]O isotope effect on the hydrogen-bond strength in water to investigate the role of hydration in collagen self-assembly. We dissolve collagen in H[Formula: see text]O and D[Formula: see text]O and compare the growth kinetics and the structure of the collagen assemblies formed in these water isotopomers. Surprisingly, collagen assembly occurs ten times faster in D[Formula: see text]O than in H[Formula: see text]O, and collagen in D[Formula: see text]O self-assembles into much thinner fibrils, that form a more inhomogeneous and softer network, with a fourfold reduction in elastic modulus when compared to H[Formula: see text]O. Combining spectroscopic measurements with atomistic simulations, we show that collagen in D[Formula: see text]O is less hydrated than in H[Formula: see text]O. This partial dehydration lowers the enthalpic penalty for water removal and reorganization at the collagen-water interface, increasing the self-assembly rate and the number of nucleation centers, leading to thinner fibrils and a softer network. Coarse-grained simulations show that the acceleration in the initial nucleation rate can be reproduced by the enhancement of electrostatic interactions. These results show that water acts as a mediator between collagen monomers, by modulating their interactions so as to optimize the assembly process and, thus, the final network properties. We believe that isotopically modulating the hydration of proteins can be a valuable method to investigate the role of water in protein structural dynamics and protein self-assembly.

Binding Dynamics of a Stapled Peptide Targeting the Transcription Factor NF-Y.

Transcription factors (TFs) play a central role in gene regulation, and their malfunction can result in a plethora of severe diseases. TFs are therefore interesting therapeutic targets, but their involvement in protein-protein interaction networks and the frequent lack of well-defined binding pockets render them challenging targets for classical small molecules. As an alternative, peptide-based scaffolds have proven useful, in particular with an α-helical active conformation. Peptide-based strategies often require extensive structural optimization efforts, which could benefit from a more detailed understanding of the dynamics in inhibitor/protein interactions. In this study, we investigate how truncated stapled α-helical peptides interact with the transcription factor Nuclear Factor-Y (NF-Y). We identified a 13-mer minimal binding core region, for which two crystal structures with an altered C-terminal peptide conformation when bound to NF-Y were obtained. Subsequent molecular dynamics simulations confirmed that the C-terminal part of the stapled peptide is indeed relatively flexible while still showing defined interactions with NF-Y. Our findings highlight the importance of flexibility in the bound state of peptides, which can contribute to overall binding affinity.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning.

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Decrypting Integrins by Mixed-Solvent Molecular Dynamics Simulations.

Integrins are a family of α/ß heterodimeric cell surface adhesion receptors which are capable of transmitting signals bidirectionally across membranes. They are known for their therapeutic potential in a wide range of diseases. However, the development of integrin-targeting medications has been impacted by unexpected downstream effects including unwanted agonist-like effects. Allosteric modulation of integrins is a promising approach to potentially overcome these limitations. Applying mixed-solvent molecular dynamics (MD) simulations to integrins, the current study uncovers hitherto unknown allosteric sites within the integrin α I domains of LFA-1 (αLß2; CD11a/CD18), VLA-1 (α1ß1; CD49a/CD29), and Mac-1 (αMß2, CD11b/CD18). We show that these pockets are putatively accessible to small-molecule modulators. The findings reported here may provide opportunities for the design of novel allosteric integrin inhibitors lacking the unwanted agonism observed with earlier as well as current integrin-targeting drugs.

Interactions of Curcumin's Degradation Products with the Aß42 Dimer: A Computational Study.

Amyloid-ß (Aß) dimers are the smallest toxic species along the amyloid-aggregation pathway and among the most populated oligomeric accumulations present in the brain affected by Alzheimer's disease (AD). A proposed therapeutic strategy to avoid the aggregation of Aß into higher-order structures is to develop molecules that inhibit the early stages of aggregation, i.e., dimerization. Under physiological conditions, the Aß dimer is highly dynamic and does not attain a single well-defined structure but is rather characterized by an ensemble of conformations. In a recent study, a highly heterogeneous library of conformers of the Aß dimer was generated by an efficient sampling method with constraints based on ion mobility mass spectrometry data. Here, we make use of the Aß dimer library to study the interaction with two curcumin degradation products, ferulic aldehyde and vanillin, by molecular dynamics (MD) simulations. Ensemble docking and MD simulations are used to provide atomistic detail of the interactions between the curcumin degradation products and the Aß dimer. The simulations show that the aromatic residues of Aß, and in particular 19FF20, interact with ferulic aldehyde and vanillin through π-π stacking. The binding of these small molecules induces significant changes on the 16KLVFF20 region.

Antibody binding increases the flexibility of the prion protein.

Prion diseases are associated with the conversion of the cellular prion protein (PrP) into a pathogenic conformer (PrPSc). A proposed therapeutic approach to avoid the pathogenic transformation is to develop antibodies that bind to PrP and stabilize its structure. POM1 and POM6 are two monoclonal antibodies that bind the globular domain of PrP and have different biological responses, i.e., trigger neurotoxicity mimicking prion infections (POM1) or prevent neurotoxicity (POM6). The crystal structures of PrP in complex with the two antibodies show similar epitopes which seems inconsistent with the opposite phenotypes. Here, we investigate the influence of the POM1 and POM6 antibodies on the flexibility of the mouse PrP by molecular dynamics simulations. The simulations reveal that the POM6/PrP interface is less stable than the POM1/PrP interface, ascribable to localized polar mismatches at the interface, despite the former complex having a larger epitope than the latter. In the presence of any of the two antibodies, the flexibility of the globular domain increases everywhere except for the ß1-α1 loop in the POM1/PrP complex which suggests the involvement of this loop in the pathological conversion. The secondary structure of PrP is preserved whereas the polar interactions involving residues Glu146, Arg156 and Arg208 are modified upon antibody binding.

Antibody binding modulates the dynamics of the membrane-bound prion protein.

Misfolding of the cellular prion protein (PrPC) is associated with lethal neurodegeneration. PrPC consists of a flexible tail (residues 23-123) and a globular domain (residues 124-231) whose C-terminal end is anchored to the cell membrane. The neurotoxic antibody POM1 and the innocuous antibody POM6 recognize the globular domain. Experimental evidence indicates that POM1 binding to PrPC emulates the influence on PrPC of the misfolded prion protein (PrPSc) while the binding of POM6 has the opposite biological response. Little is known about the potential interactions between flexible tail, globular domain, and the membrane. Here, we used atomistic simulations to investigate how these interactions are modulated by the binding of the Fab fragments of POM1 and POM6 to PrPC and by interstitial sequence truncations to the flexible tail. The simulations show that the binding of the antibodies restricts the range of orientations of the globular domain with respect to the membrane and decreases the distance between tail and membrane. Five of the six sequence truncations influence only marginally this distance and the contact patterns between tail and globular domain. The only exception is a truncation coupled to a charge inversion mutation of four N-terminal residues, which increases the distance of the flexible tail from the membrane. The interactions of the flexible tail and globular domain are modulated differently by the two antibodies.

Silybins inhibit human IAPP amyloid growth and toxicity through stereospecific interactions.

Type 2 Diabetes is a major public health threat, and its prevalence is increasing worldwide. The abnormal accumulation of islet amyloid polypeptide (IAPP) in pancreatic ß-cells is associated with the onset of the disease. Therefore, the design of small molecules able to inhibit IAPP aggregation represents a promising strategy in the development of new therapies. Here we employ in vitro, biophysical, and computational methods to inspect the ability of Silybin A and Silybin B, two natural diastereoisomers extracted from milk thistle, to interfere with the toxic self-assembly of human IAPP (hIAPP). We show that Silybin B inhibits amyloid aggregation and protects INS-1 cells from hIAPP toxicity more than Silybin A. Molecular dynamics simulations revealed that the higher efficiency of Silybin B is ascribable to its interactions with precise hIAPP regions that are notoriously involved in hIAPP self-assembly i.e., the S20-S29 amyloidogenic core, H18, the N-terminal domain, and N35. These results highlight the importance of stereospecific ligand-peptide interactions in regulating amyloid aggregation and provide a blueprint for future studies aimed at designing Silybin derivatives with enhanced drug-like properties.

The role of the N-terminal amphipathic helix in bacterial YidC: Insights from functional studies, the crystal structure and molecular dynamics simulations.

The evolutionary conserved YidC is a unique dual-function membrane protein that adopts insertase and chaperone conformations. The N-terminal helix of Escherichia coli YidC functions as an uncleaved signal sequence and is important for membrane insertion and interaction with the Sec translocon. Here, we report the first crystal structure of Thermotoga maritima YidC (TmYidC) including the N-terminal amphipathic helix (N-AH) (PDB ID: 6Y86). Molecular dynamics simulations show that N-AH lies on the periplasmic side of the membrane bilayer forming an angle of about 15° with the membrane surface. Our functional studies suggest a role of N-AH for the species-specific interaction with the Sec translocon. The reconstitution data and the superimposition of TmYidC with known YidC structures suggest an active insertase conformation for YidC. Molecular dynamics (MD) simulations of TmYidC provide evidence that N-AH acts as a membrane recognition helix for the YidC insertase and highlight the flexibility of the C1 region underlining its ability to switch between insertase and chaperone conformations. A structure-based model is proposed to rationalize how YidC performs the insertase and chaperone functions by re-positioning of N-AH and the other structural elements.

Simulation Studies of Amyloidogenic Polypeptides and Their Aggregates.

Amyloids, fibrillar assembly of (poly)peptide chains, are associated with neurodegenerative illnesses such as Alzheimer's and Parkinson's diseases, for which there are no cures. The molecular mechanisms of the formation of toxic species are still elusive. Some peptides and proteins can form functional amyloid-like aggregates mainly in bacteria and fungi but also in humans. Little is known on the differences in self-assembly mechanisms of functional and pathogenic (poly)peptides. We review atomistic and coarse-grained simulation studies of amyloid peptides in their monomeric, oligomeric, and fibrillar states. Particular emphasis is given to the challenges one faces to characterize at atomic level of detail the conformational space of disordered (poly)peptides and their aggregation. We discuss the difficulties in comparing simulation results and experimental data, and we propose new simulation studies to shed light on the aggregation processes associated with amyloid diseases.

Disorder at the Tips of a Disease-Relevant Aß42 Amyloid Fibril: A Molecular Dynamics Study.

We present a simulation study of the early events of peptide dissociation from a fibril of the Alzheimer's Aß42 peptide. The fibril consists of layers of two adjacent Aß42 peptides each folded in an S-shaped structure which has been determined by solid state NMR spectroscopy of a monomorphic disease-relevant species. Multiple molecular dynamics runs (16 at 310 K and 15 at 370 K) were carried out starting from an 18-peptide protofibril for a cumulative sampling of about 15 µs. The simulations show structural stability of the fibrillar core and an overall increase in the twist to about 3 degrees. The N-terminal segment 1-14 is disordered in all peptides. At both ends of the fibril, the central segment 21-29, which includes part of the ß2 strand, dissociates in some of the simulations. The ß1 and ß3 strands, residues 15-20 and 35-41, respectively, are structurally stable. The transient binding of the N-terminal stretch to the ß3 strand of the adjacent peptide at the tip is likely to contribute to the arrest phase of the stop-and-go mechanism.

Intrinsic Conformational Preferences and Interactions in α-Synuclein Fibrils: Insights from Molecular Dynamics Simulations.

Amyloid formation by the intrinsically disordered α-synuclein protein is the hallmark of Parkinson's disease. We present atomistic Molecular Dynamics simulations of the core of α-synuclein using enhanced sampling techniques to describe the conformational and binding free energy landscapes of fragments implicated in fibril stabilization. The theoretical framework is derived to combine the free energy profiles of the fragments into the reaction free energy of a protein binding to a fibril. Our study shows that individual fragments in solution have a propensity toward attaining non-ß conformations, indicating that in a fibril ß-strands are stabilized by interactions with other strands. We show that most dimers of hydrogen-bonded fragments are unstable in solution, while hydrogen bonding stabilizes the collective binding of five fragments to the end of a fibril. Hydrophobic effects make further contributions to the stability of fibrils. This study is the first of its kind where structural and binding preferences of the five major fragments of the hydrophobic core of α-synuclein have been investigated. This approach improves sampling of intrinsically disordered proteins, provides information on the binding mechanism between the core sequences of α-synuclein, and enables the parametrization of coarse grained models.

The attachment of α-synuclein to a fiber: A coarse-grain approach.

We present simulations of the amyloidogenic core of α-synuclein, the protein causing Parkinson's disease, as a short chain of coarse-grain patchy particles. Each particle represents a sequence of about a dozen amino acids. The fluctuating secondary structure of this intrinsically disordered protein is modelled by dynamic variations of the shape and interaction characteristics of the patchy particles, ranging from spherical with weak isotropic attractions for the disordered state to spherocylindrical with strong directional interactions for a ß-sheet. Flexible linkers between the particles enable sampling of the tertiary structure. This novel model is applied here to study the growth of an amyloid fibril, by calculating the free energy profile of a protein attaching to the end of a fibril. The simulation results suggest that the attaching protein readily becomes trapped in a mis-folded state, thereby inhibiting further growth of the fibril until the protein has readjusted to conform to the fibril structure, in line with experimental findings and previous simulations on small fragments of other proteins.

A coarse grained protein model with internal degrees of freedom. Application to α-synuclein aggregation.

Particles in simulations are traditionally endowed with fixed interactions. While this is appropriate for particles representing atoms or molecules, objects with significant internal dynamics--like sequences of amino acids or even an entire protein--are poorly modelled by invariable particles. We develop a highly coarse grained polymorph patchy particle with the ultimate aim of simulating proteins as chains of particles at the secondary structure level. Conformational changes, e.g., a transition between disordered and ß-sheet states, are accommodated by internal coordinates that determine the shape and interaction characteristics of the particles. The internal coordinates, as well as the particle positions and orientations, are propagated by Brownian Dynamics in response to their local environment. As an example of the potential offered by polymorph particles, we model the amyloidogenic intrinsically disordered protein α-synuclein, involved in Parkinson's disease, as a single particle with two internal states. The simulations yield oligomers of particles in the disordered state and fibrils of particles in the "misfolded" cross-ß-sheet state. The aggregation dynamics is complex, as aggregates can form by a direct nucleation-and-growth mechanism and by two-step-nucleation through conversions between the two cluster types. The aggregation dynamics is complex, with fibrils formed by direct nucleation-and-growth, by two-step-nucleation through the conversion of an oligomer and by auto-catalysis of this conversion.

An elementary singularity-free Rotational Brownian Dynamics algorithm for anisotropic particles.

Brownian Dynamics is the designated technique to simulate the collective dynamics of colloidal particles suspended in a solution, e.g., the self-assembly of patchy particles. Simulating the rotational dynamics of anisotropic particles by a first-order Langevin equation, however, gives rise to a number of complications, ranging from singularities when using a set of three rotational coordinates to subtle metric and drift corrections. Here, we derive and numerically validate a quaternion-based Rotational Brownian Dynamics algorithm that handles these complications in a simple and elegant way. The extension to hydrodynamic interactions is also discussed.

Rotational Brownian dynamics simulations of clathrin cage formation.

The self-assembly of nearly rigid proteins into ordered aggregates is well suited for modeling by the patchy particle approach. Patchy particles are traditionally simulated using Monte Carlo methods, to study the phase diagram, while Brownian Dynamics simulations would reveal insights into the assembly dynamics. However, Brownian Dynamics of rotating anisotropic particles gives rise to a number of complications not encountered in translational Brownian Dynamics. We thoroughly test the Rotational Brownian Dynamics scheme proposed by Naess and Elsgaeter [Macromol. Theory Simul. 13, 419 (2004); Naess and Elsgaeter Macromol. Theory Simul. 14, 300 (2005)], confirming its validity. We then apply the algorithm to simulate a patchy particle model of clathrin, a three-legged protein involved in vesicle production from lipid membranes during endocytosis. Using this algorithm we recover time scales for cage assembly comparable to those from experiments. We also briefly discuss the undulatory dynamics of the polyhedral cage.