Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations.

Parallel in-register contact propensity predicts the Amyloidogenicity of ADan and ABri in familial dementias.

Both senile plaques formed by amyloid-β (Aβ) and neurofibrillary tangles (NFTs) comprised of tau are pathological hallmarks of Alzheimer's disease (AD). The accumulation of NFTs better correlates with the loss of cognitive function than senile plaques, but NFTs are rarely observed without the presence of senile plaques. Hence, cross-seeding of tau by preformed Aβ amyloid fibril seeds has been proposed to drive the aggregation of tau and exacerbate AD progression, but the molecular mechanism remains unknown. Here, we first identified cross-interaction hotspots between Aβ and tau using atomistic discrete molecular dynamics simulations (DMD) and confirmed the critical role of the four microtubule-binding repeats of tau (R1-R4) in the cross-interaction with Aβ. We further investigated the binding structure and dynamics of each tau repeat with a preformed Aβ fibril seed. Specifically, R1 and R3 preferred to bind the Aβ fibril lateral surface instead of the elongation end. In contrast, R2 and R4 had higher binding propensities to the fibril elongation end than the lateral surface, enhancing β-sheet content by forming hydrogen bonds with the exposed hydrogen bond donors and acceptors. Together, our results suggest that the four repeats play distinct roles in driving the binding of tau to different surfaces of an Aβ fibril seed. Binding of tau to the lateral surface of Aβ fibril can increase the local concentration, while the binding to the elongation surface promotes β-sheet formation, both of which reduce the free energy barrier for tau aggregation nucleation and subsequent fibrillization.

Zinc is reported to play a complex role in islet amyloid polypeptide (IAPP) aggregation, which is associated with β-cell death in type II diabetes (T2D). Depending on their relative concentrations in vitro, zinc could either promote or inhibit IAPP aggregation. Interestingly, genomewide association studies suggested both positive and negative correlations between T2D risks and activities of a β-cell-specific zinc transporter upon mutations, which determines zinc concentration in vivo. To decipher the effect of zinc coordination on IAPP aggregation, we performed atomistic discrete molecular dynamics simulations to systemically study aggregation propensities of zinc-coordinated IAPP oligomers with different molecular weights (MWs), whose populations are determined by zinc concentration. We find that at low zinc:IAPP stoichiometry, zinc coordination promotes aggregation by forming high-MW oligomers. The aggregation is inhibited when the stoichiometry increases and zinc binds individual peptides. Our computationally derived predictions are validated by the complementary thioflavin-T fluorescence assay measuring the dependence of IAPP aggregation on a wide range of zinc concentrations. Our combined computational and experimental study offers detailed mechanistic insight into the complex role of zinc on IAPP aggregation and T2D development.

Abnormal aggregation of α-synuclein (αS) into amyloid fibrils is a hallmark of neurodegenerative diseases such as Parkinson's disease. In contrast, its homologue β-synuclein (βS), colocalized at presynaptic terminals, resists amyloid formation and can even inhibit αS fibrillization. However, how sequence variations affect their structural dynamics remains poorly understood. To address this, we conducted 100 independent 1000 ns atomistic discrete molecular dynamics simulations for both αS and βS monomers. Our results revealed that both proteins predominantly adopted intrinsically disordered conformations, punctuated by transient helices and β-sheets. Both αS and βS exhibited a conserved helical tendency in the first half of the N-terminal domain, while the latter half showed dynamic β-sheet characteristics with αS displaying greater abundance. Notably, the nonamyloid component (NAC) region in αS─critical for its aggregation─frequently adopted dynamic β-sheet structures, whereas the homologous region in βS displayed a greater tendency toward dynamic helices. Despite being largely disordered, the C-terminal regions transiently interacted with β-sheet-prone segments, potentially acting as dynamic caps that limit β-sheet growth in both proteins. Free-energy landscape analysis indicated a clear enthalpy-entropy trade-off: structured conformations were stabilized by lower potential energy but penalized by reduced entropy, whereas disordered states, despite higher potential energy, were entropically favored. Importantly, potential energy reduction in αS was primarily associated with β-sheet formation, while in βS, it was mainly driven by helix formation. These findings offer mechanistic insights into the distinct conformational landscapes of αS and βS and establish a thermodynamic framework for understanding how sequence differences modulate their structural properties and functional roles.

Computational exploration of the self-aggregation mechanisms of phenol-soluble modulins β1 and β2 in Staphylococcus aureus biofilms.

Bri2 BRICHOS, a folded domain of the transmembrane protein Bri2 expressed in both the brain and pancreas, is an experimentally known substoichiometric inhibitor of amyloid aggregation. The molecular chaperone effectively delays fibrillization at low molar ratios for both β-amyloid (Aβ) in Alzheimer's disease (AD) and islet amyloid polypeptide (IAPP) in type 2 diabetes (T2D). While discovering effective antiamyloid inhibitors that work at low doses is an appealing strategy to mitigate amyloid toxicity, the molecular mechanism underlying the broad and efficient antiamyloid activity of Bri2 BRICHOS remains unknown. Here, we computationally demonstrated that Bri2 BRICHOS exhibits a stronger binding affinity to fibril seeds than to monomers using atomistic discrete molecular dynamic simulations. By competing with monomers to bind the active elongation sites on newly nucleated, weakly populated fibril seeds, a small amount of Bri2 BRICHOS could block rapid fibril growth via monomer addition. The experimentally observed differential inhibition efficiency against IAPP and Aβ aggregation was found to depend on the relative fibril-binding affinities of the inhibitor compared to those of self-seeding monomers. Our computationally derived determinants for substoichiometric inhibition against amyloid aggregation by Bri2 BRICHOS may inform the future design of potent antiamyloid therapies for AD, T2D, and other amyloid diseases.

ABSTRACTIn this work we present preliminary results from multi-million fully atomistic classical molecular dynamics simulations carried out to test different existing mechanisms that have been proposed in the literature to explain the drawing of yarns from carbon nanotube forests. Despite the fact that it has been almost ten years since yarns were first drawn, there are still controversies on the mechanisms and necessary conditions that can produce yarns and sheets drawn from carbon nanotube forests. Moreover, few works have tried to understand at atomistic level the details of yarn drawing mechanisms, and no fully atomistic simulations have been carried out so far on this particular subject. Our preliminary results suggest that only direct van der Waals interactions among large bundles seem not to be enough to explain the yarn drawing process. Bundle interconnectors (such as small bundles connecting large bundles) were observed to play a critical role in our simulations. Depending on the topology of these interconnectors it was possible to observe from the simulations fibers/yarn formation from proposed structural models. These models were built based on structural information inferred from scanning electron microscopy data.

A coarse-grained model previously used to simulate Nafion using dissipative particle dynamics (DPD) is modified to describe sulfonated Diels-Alder poly(phenylene) (SDAPP) polymers. The model includes a proton-hopping mechanism similar to the Grotthuss mechanism. The intramolecular parameters for SDAPP are derived from atomistic molecular dynamics (MD) simulation using the iterative Boltzmann inversion. The polymer radii of gyration, domain morphologies, and cluster distributions obtained from our DPD model are in good agreement with previous atomistic MD simulations. As found in the atomistic simulations, the DPD simulations predict that the SDAPP nanophase separates into hydrophobic polymer domains and hydrophilic domains that percolate through the system at sufficiently high sulfonation and hydration levels. Increasing sulfonation and/or hydration leads to larger proton and water diffusion constants, in agreement with experimental measurements in SDAPP. In the DPD simulations, the proton hopping (Grotthuss) mechanism becomes important as sulfonation and hydration increase, in qualitative agreement with experiment. The turning on of the hopping mechanism also roughly correlates with the point at which the DPD simulations exhibit clear percolated, hydrophilic domains, demonstrating the important effects of morphology on proton transport.

Mirrored continuum and molecular scale simulations of deflagration in a nano-slab of HMX

In this chapter, we provide a practical guide on how to plan, execute, and interpret atomistic and coarse-grained molecular dynamics (MD) simulations of lipid-modified proteins in model membranes. After outlining some key practical considerations when planning such simulations, we survey resources and techniques to obtain force field parameters for nonconventional amino acids, such as posttranslationally lipid-modified amino acids that are unique to this class of proteins. We then describe the protocols to build, setup, and run the simulations, followed by a brief comment on the analysis and interpretation of the simulations. Finally, examples of insights that could be gained from atomistic and coarse-grained MD simulations of lipidated proteins will be provided, using RAS proteins as illustrative examples. Throughout the chapter, we highlight the main advantages and limitations of simulating RAS and related lipid-modified G-proteins in biomimetic membranes.

A didactic multiscale approach for drone modeling is proposed. Specifically, we investigate the drone structure at both macroscopic and microscopic scales, by making use of finite element and atomistic simulations, respectively. The structural analysis is performed with the aim to equip the drone with specific sensors and measuring instruments capable to detect the existence of volcanic ash, SO 2 , CO 2 and other pollutants in the atmosphere after a volcanic eruption. We show that, by modeling the tubular structure of the drone with a sandwich constituted by a a polystyrene core, carbon fiber skins and epoxy matrix, a weight saving of 7 grams for each drone arm can be obtained, in comparison to the standard commercial drones, although a slight worsening of the mechanical performances is observed. In addition, the molecular structure of the polystyrene chains has been investigated by using atomistic Molecular Dynamics simulations, providing further information on the local structure of the polymer chains. Additional improvements of the weight saving could be obtained by means of the the topological optimization techniques on the body of the drone and on the supports for landing.

We have developed a graphical user interface based dendrimer builder toolkit (DBT) which can be used to generate the dendrimer configuration of desired generation for various dendrimer architectures. The validation of structures generated by this tool was carried out by studying the structural properties of two well known classes of dendrimers: ethylenediamine cored poly(amidoamine) (PAMAM) dendrimer, diaminobutyl cored poly(propylene imine) (PPI) dendrimer. Using full atomistic molecular dynamics (MD) simulation we have calculated the radius of gyration, shape tensor and monomer density distribution for PAMAM and PPI dendrimer at neutral and high pH. A good agreement between the available simulation and experimental (small angle X-ray and neutron scattering; SAXS, SANS) results and calculated radius of gyration was observed. With this validation we have used DBT to build another new class of nitrogen cored poly(propyl ether imine) dendrimer and study it's structural features using all atomistic MD simulation. DBT is a versatile tool and can be easily used to generate other dendrimer structures with different chemistry and topology. The use of general amber force field to describe the intra-molecular interactions allows us to integrate this tool easily with the widely used molecular dynamics software AMBER. This makes our tool a very useful utility which can help to facilitate the study of dendrimer interaction with nucleic acids, protein and lipid bilayer for various biological applications.

The abnormal aggregation of human calcitonin (hCT) hormone peptides impairs their physiological function, leading to harmful immune responses and cytotoxicity, which limits their clinical utility. Interestingly, a representative hCT analog incorporating Y12L and N17H substitutions (DM-hCT) has shown reduced aggregation tendencies while maintaining bioactivity. But the molecular mechanism of Y12L and N17H substitutions on the conformational dynamics of hCT remains unclear. Here, we systematically investigated the folding and self-assembly dynamics of hCT and DM-hCT using atomistic discrete molecular dynamics (DMD) simulations. Our findings revealed that hCT monomers predominantly adopted unstructured conformations with dynamic helices. Oligomerization of hCT resulted in the formation of β-sheet-rich aggregates and β-barrel intermediates. The Y12L and N17H substitutions enhanced helical conformations and suppressed β-sheet formation in both monomers and oligomers. These substitutions stabilized the dynamic helices and disrupted aromatic interactions responsible for β-sheet formation at residue 12. Notably, DM-hCT assemblies still exhibited β-sheets in phenylalanine-rich and C-terminal hydrophobic regions, suggesting that future optimizations should focus on these areas. Our simulations provide insights into the molecular mechanisms underlying hCT aggregation and the amyloid-resistant effects of Y12L and N17H substitutions. These findings have valuable implications for the development of clinical hCT analogs.

Modern experimental kinetics of protein folding began in the early 1990s with the introduction of nanosecond laser pulses to trigger the folding reaction, providing an almost 106-fold improvement in time resolution over the stopped-flow method being employed at the time. These experiments marked the beginning of the “fast-folding” subfield that enabled investigation of the kinetics of formation of secondary structural elements and disordered loops for the first time, as well as the fastest folding proteins. When I started to work on this subject, a fast folding protein was one that folded in milliseconds. There were, moreover, no analytical theoretical models and no atomistic or coarse-grained molecular dynamics simulations to describe the mechanism. Two of the most important discoveries from my lab since then are a protein that folds in hundreds of nanoseconds, as determined from nanosecond laser temperature experiments, and the discovery that the theoretically predicted barrier crossing time is about the same for proteins that differ in folding rates by 104-fold, as determined from single molecule fluorescence measurements. We also developed what has been called the “Hückel model” of protein folding, which quantitatively explains a wide range of equilibrium and kinetic measurements. This retrospective traces the history of contributions to the “fast folding” subfield from my lab until about 3 years ago, when I left protein folding to spend the rest of my research career trying to discover an inexpensive drug for treating sickle cell disease.

ABSTRACTDuring the last years carbon-based nanostructures (such as, fullerenes, carbon nanotubes and graphene) have been object of intense investigations. The great interest in these nanostructures can be attributed to their remarkable electrical and mechanical properties. Their inorganic equivalent structures do exist and are based on boron nitride (BN) motifs. BN fullerenes, nanotubes and single layers have been already synthesized. Recently, the fracture patterns of single layer graphene and multi-walled carbon nanotubes under stress have been studied by theoretical and experimental methods. In this work we investigated the fracturing process of defective carbon and boron nitride nanotubes under similar stress conditions. We have carried out fully atomistic molecular reactive molecular dynamics simulations using the ReaxFF force field. The similarities and differences between carbon and boron nitride fracture patterns are addressed.