Cryo-EM Analysis of the Effect of Seeding with Brain-derived Aβ Amyloid Fibrils

Aβ amyloid fibrils from Alzheimer's brain tissue are polymorphic and structurally different from typical in vitro formed Aβ fibrils. Here, we show that brain-derived (ex vivo) fibril structures can be proliferated by seeding in vitro. The proliferation reaction is only efficient for one of the three abundant ex vivo Aβ fibril morphologies, which consists of two peptide stacks, while the inefficiently proliferated fibril morphologies contain four or six peptide stacks. In addition to the seeded fibril structures, we find that de novo nucleated fibril structures can emerge in seeded samples if the seeding reaction is continued over multiple generations. These data imply a competition between de novo nucleation and seed extension and suggest further that seeding favours the outgrowth of fibril morphologies that contain fewer peptide stacks.

Insights into the Structural Basis of Amyloid Resistance Provided by Cryo-EM Structures of AApoAII Amyloid Fibrils

Amyloid resistance is the inability or the reduced susceptibility of an organism to develop amyloidosis. In this study we have analysed the molecular basis of the resistance to systemic AApoAII amyloidosis, which arises from the formation of amyloid fibrils from apolipoprotein A-II (ApoA-II). The disease affects humans and animals, including SAMR1C mice that express the C allele of ApoA-II protein, whereas other mouse strains are resistant to development of amyloidosis due to the expression of other ApoA-II alleles, such as ApoA-IIF. Using cryo-electron microscopy, molecular dynamics simulations and other methods, we have determined the structures of pathogenic AApoAII amyloid fibrils from SAMR1C mice and analysed the structural effects of ApoA-IIF-specific mutational changes. Our data show that these changes render ApoA-IIF incompatible with the specific fibril morphologies, with which ApoA-II protein can become pathogenic in vivo.

RNA G-quadruplex folding is a multi-pathway process driven by conformational entropy

The kinetics of folding is crucial for the function of many regulatory RNAs including RNA G-quadruplexes (rG4s). Here, we characterize the folding pathways of a G-quadruplex from the telomeric repeat-containing RNA by combining all-atom molecular dynamics and coarse-grained simulations with circular dichroism experiments. The quadruplex fold is stabilized by cations and thus, the ion atmosphere forming a double layer surrounding the highly charged quadruplex guides the folding process. To capture the ionic double layer in implicit solvent coarse-grained simulations correctly, we develop a matching procedure based on all-atom simulations in explicit water. The procedure yields quantitative agreement between simulations and experiments as judged by the populations of folded and unfolded states at different salt concentrations and temperatures. Subsequently, we show that coarse-grained simulations with a resolution of three interaction sites per nucleotide are well suited to resolve the folding pathways and their intermediate states. The results reveal that the folding progresses from unpaired chain via hairpin, triplex and double-hairpin constellations to the final folded structure. The two- and three-strand intermediates are stabilized by transient Hoogsteen interactions. Each pathway passes through two on-pathway intermediates. We hypothesize that conformational entropy is a hallmark of rG4 folding. Conformational entropy leads to the observed branched multi-pathway folding process for TERRA25. We corroborate this hypothesis by presenting the free energy landscapes and folding pathways of four rG4 systems with varying loop length.

pH-dependent structural transitions in cationic ionizable lipid mesophases are critical for lipid nanoparticle function

Lipid nanoparticles (LNPs) are advanced core-shell particles for messenger RNA (mRNA) based therapies that are made of polyethylene glycol (PEG) lipid, distearoylphosphatidylcholine (DSPC), cationic ionizable lipid (CIL), cholesterol (chol), and mRNA. Yet the mechanism of pH-dependent response that is believed to cause endosomal release of LNPs is not well understood. Here, we show that eGFP (enhanced green fluorescent protein) protein expression in the mouse liver mediated by the ionizable lipids DLin-MC3-DMA (MC3), DLin-KC2-DMA (KC2), and DLinDMA (DD) ranks MC3 ≥ KC2 > DD despite similar delivery of mRNA per cell in all cell fractions isolated. We hypothesize that the three CIL-LNPs react differently to pH changes and hence study the structure of CIL/chol bulk phases in water. Using synchrotron X-ray scattering a sequence of ordered CIL/chol mesophases with lowering pH values are observed. These phases show isotropic inverse micellar, cubic Fd3m inverse micellar, inverse hexagonal [Formula: see text] and bicontinuous cubic Pn3m symmetry. If polyadenylic acid, as mRNA surrogate, is added to CIL/chol, excess lipid coexists with a condensed nucleic acid lipid [Formula: see text] phase. The next-neighbor distance in the excess phase shows a discontinuity at the Fd3m inverse micellar to inverse hexagonal [Formula: see text] transition occurring at pH 6 with distinctly larger spacing and hydration for DD vs. MC3 and KC2. In mRNA LNPs, DD showed larger internal spacing, as well as retarded onset and reduced level of DD-LNP-mediated eGFP expression in vitro compared to MC3 and KC2. Our data suggest that the pH-driven Fd3m-[Formula: see text] transition in bulk phases is a hallmark of CIL-specific differences in mRNA LNP efficacy.

Adsorbing DNA to Mica by Cations: Influence of Valency and Ion Type

Ion-mediated attraction between DNA and mica plays a crucial role in biotechnological applications and molecular imaging. Here, we combine molecular dynamics simulations and single-molecule atomic force microscopy experiments to characterize the detachment forces of single-stranded DNA at mica surfaces mediated by the metal cations Li+, Na+, K+, Cs+, Mg2+, and Ca2+. Ion-specific adsorption at the mica/water interface compensates (Li+ and Na+) or overcompensates (K+, Cs+, Mg2+, and Ca2+) the bare negative surface charge of mica. In addition, direct and water-mediated contacts are formed between the ions, the phosphate oxygens of DNA, and mica. The different contact types give rise to low- and high-force pathways and a broad distribution of detachment forces. Weakly hydrated ions, such as Cs+ and water-mediated contacts, lead to low detachment forces and high mobility of the DNA on the surface. Direct ion-DNA or ion-surface contacts lead to significantly higher forces. The comprehensive view gained from our combined approach allows us to highlight the most promising cations for imaging in physiological conditions: K+, which overcompensates the negative mica charge and induces long-ranged attractions. Mg2+ and Ca2+, which form a few specific and long-lived contacts to bind DNA with high affinity.

Combining molecular dynamics simulations and x-ray scattering techniques for the accurate treatment of protonation degree and packing of ionizable lipids in monolayers

The pH-dependent change in protonation of ionizable lipids is crucial for the success of lipid-based nanoparticles as mRNA delivery systems. Despite their widespread application in vaccines, the structural changes upon acidification are not well understood. Molecular dynamics simulations support structure prediction but require an a priori knowledge of the lipid packing and protonation degree. The presetting of the protonation degree is a challenging task in the case of ionizable lipids since it depends on pH and on the local lipid environment and often lacks experimental validation. Here, we introduce a methodology of combining all-atom molecular dynamics simulations with experimental total-reflection x-ray fluorescence and scattering measurements for the ionizable lipid Dlin-MC3-DMA (MC3) in POPC monolayers. This joint approach allows us to simultaneously determine the lipid packing and the protonation degree of MC3. The consistent parameterization is expected to be useful for further predictive modeling of the action of MC3-based lipid nanoparticles.

Cryo-EM Structure of the Full-length hnRNPA1 Amyloid Fibril

Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) is a multifunctional RNA-binding protein that is associated with neurodegenerative diseases, such as amyotrophic lateral sclerosis and multisystem proteinopathy. In this study, we have used cryo-electron microscopy to investigate the three-dimensional structure of amyloid fibrils from full-length hnRNPA1 protein. We find that the fibril core is formed by a 45-residue segment of the prion-like low-complexity domain of the protein, whereas the remaining parts of the protein (275 residues) form a fuzzy coat around the fibril core. The fibril consists of two fibril protein stacks that are arranged into a pseudo-21 screw symmetry. The ordered core harbors several of the positions that are known to be affected by disease-associated mutations, but does not encompass the most aggregation-prone segments of the protein. These data indicate that the structures of amyloid fibrils from full-length proteins may be more complex than anticipated by current theories on protein misfolding.

Structural insights on ionizable Dlin-MC3-DMA lipids in DOPC layers by combining accurate atomistic force fields, molecular dynamics simulations and neutron reflectivity

Ionizable lipids such as the promising Dlin-MC3-DMA (MC3) are essential for the successful design of lipid nanoparticles (LNPs) as drug delivery agents. Combining molecular dynamics simulations with experimental data, such as neutron reflectivity experiments and other scattering techniques, is essential to provide insights into the internal structure of LNPs, which is not fully understood to date. However, the accuracy of the simulations relies on the choice of force field parameters and high-quality experimental data is indispensable to verify the parametrization. For MC3, different parameterizations in combination with the CHARMM and the Slipids force fields have recently emerged. Here, we complement the existing efforts by providing parameters for cationic and neutral MC3 compatible with the AMBER Lipid17 force field. Subsequently, we carefully assess the accuracy of the different force fields by providing a direct comparison to neutron reflectivity experiments of mixed lipid bilayers consisting of MC3 and DOPC at different pHs. At low pH (cationic MC3) and at high pH (neutral MC3) the newly developed MC3 parameters in combination with AMBER Lipid17 for DOPC give good agreement with the experiments. Overall, the agreement is similar compared to the Park-Im parameters for MC3 in combination with the CHARMM36 force field for DOPC. The Ermilova-Swenson MC3 parameters in combination with the Slipids force field underestimate the bilayer thickness. While the distribution of cationic MC3 is very similar, the different force fields for neutral MC3 reveal distinct differences ranging from strong accumulation in the membrane center (current MC3/AMBER Lipid17 DOPC), over mild accumulation (Park-Im MC3/CHARMM36 DOPC) to surface accumulation (Ermilova-Swenson MC3/Slipids DOPC). These pronounced differences highlight the importance of accurate force field parameters and their experimental validation.

Remembering the Work of Phillip L. Geissler: A Coda to His Scientific Trajectory

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 74 is April 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

RNA Captures More Cations than DNA: Insights from Molecular Dynamics Simulations

The distribution of cations around nucleic acids is essential for a broad variety of processes ranging from DNA condensation and RNA folding to the detection of biomolecules in biosensors. Predicting the exact distribution of ions remains challenging since the distribution and, hence, a broad variety of nucleic acid properties depend on the salt concentration, the valency of the ions, and the ion type. Despite the importance, a general theory to quantify ion-specific effects for highly charged biomolecules is still lacking. Moreover, recent experiments reveal that despite their similar building blocks, DNA and RNA duplexes can react differently to the same ionic conditions. The aim of our current work is to provide a comprehensive set of molecular dynamics simulations using more than 180 μs of simulation time. For the mono- and divalent cations Li⁺, Na⁺, K⁺, Cs⁺, Ca²⁺, Sr²⁺, and Ba²⁺, the simulations allow us to reveal the ion-specific distributions and binding patterns for DNA and RNA duplexes. The microscopic insights from the simulations display the origin of ion-specificity and shed light on the question of why DNA and RNA show opposing behavior in the same ionic conditions. Finally, the detailed binding patterns from the simulations reveal why RNA can capture more cations than DNA.

Twisting DNA by salt

The structure and properties of DNA depend on the environment, in particular the ion atmosphere. Here, we investigate how DNA twist -one of the central properties of DNA- changes with concentration and identity of the surrounding ions. To resolve how cations influence the twist, we combine single-molecule magnetic tweezer experiments and extensive all-atom molecular dynamics simulations. Two interconnected trends are observed for monovalent alkali and divalent alkaline earth cations. First, DNA twist increases monotonously with increasing concentration for all ions investigated. Second, for a given salt concentration, DNA twist strongly depends on cation identity. At 100 mM concentration, DNA twist increases as Na⁺ < K⁺ < Rb⁺ < Ba²⁺ < Li⁺ ≈ Cs⁺ < Sr²⁺ < Mg²⁺ < Ca²⁺. Our molecular dynamics simulations reveal that preferential binding of the cations to the DNA backbone or the nucleobases has opposing effects on DNA twist and provides the microscopic explanation of the observed ion specificity. However, the simulations also reveal shortcomings of existing force field parameters for Cs⁺ and Sr²⁺. The comprehensive view gained from our combined approach provides a foundation for understanding and predicting cation-induced structural changes both in nature and in DNA nanotechnology.

Combining Coarse-Grained Simulations and Single Molecule Analysis Reveals a Three-State Folding Model of the Guanidine-II Riboswitch

Riboswitch RNAs regulate gene expression by conformational changes induced by environmental conditions and specific ligand binding. The guanidine-II riboswitch is proposed to bind the small molecule guanidinium and to subsequently form a kissing loop interaction between the P1 and P2 hairpins. While an interaction was shown for isolated hairpins in crystallization and electron paramagnetic resonance experiments, an intrastrand kissing loop formation has not been demonstrated. Here, we report the first evidence of this interaction in cis in a ligand and Mg²⁺ dependent manner. Using single-molecule FRET spectroscopy and detailed structural information from coarse-grained simulations, we observe and characterize three interconvertible states representing an open and kissing loop conformation as well as a novel Mg²⁺ dependent state for the guanidine-II riboswitch from E. coli. The results further substantiate the proposed switching mechanism and provide detailed insight into the regulation mechanism for the guanidine-II riboswitch class. Combining single molecule experiments and coarse-grained simulations therefore provides a promising perspective in resolving the conformational changes induced by environmental conditions and to yield molecular insights into RNA regulation.

Magnesium Force Fields for OPC Water with Accurate Solvation, Ion-Binding, and Water-Exchange Properties: Successful Transfer from SPC/E

Magnesium plays a vital role in a large variety of biological processes. To model such processes by molecular dynamics simulations, researchers rely on accurate force field parameters for Mg2+ and water. OPC is one of the most promising water models yielding an improved description of biomolecules in water. The aim of this work is to provide force field parameters for Mg2+ that lead to accurate simulation results in combination with OPC water. Using twelve different Mg2+ parameter sets, that were previously optimized with different water models, we systematically assess the transferability to OPC based on a large variety of experimental properties. The results show that the Mg2+ parameters for SPC/E are transferable to OPC and closely reproduce the experimental solvation free energy, radius of the first hydration shell, coordination number, activity derivative, and binding affinity toward the phosphate oxygens on RNA. Two optimal parameter sets are presented: MicroMg yields water exchange in OPC on the microsecond timescale in agreement with experiments. NanoMg yields accelerated exchange on the nanosecond timescale and facilitates the direct observation of ion binding events for enhanced sampling purposes.

Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA

Magnesium is an indispensable cofactor in countless vital processes. In order to understand its functional role, the characterization of the binding pathways to biomolecules such as RNA is crucial. Despite the importance, a molecular description is still lacking since the transition from the water-mediated outer-sphere to the direct inner-sphere coordination is on the millisecond time scale and therefore out of reach for conventional simulation techniques. To fill this gap, we use transition path sampling to resolve the binding pathways and to elucidate the role of the solvent in the binding process. The results reveal that the molecular void provoked by the leaving phosphate oxygen of the RNA is immediately filled by an entering water molecule. In addition, water molecules from the first and second hydration shell couple to the concerted exchange. To capture the intimate solute-solvent coupling, we perform a committor analysis as the basis for a machine learning algorithm that derives the optimal deep learning model from thousands of scanned architectures using hyperparameter tuning. The results reveal that the properly optimized deep network architecture recognizes the important solvent structures, extracts the relevant information, and predicts the commitment probability with high accuracy. Our results provide detailed insights into the solute-solvent coupling which is ubiquitous for kosmotropic ions and governs a large variety of biochemical reactions in aqueous solutions.

Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties in SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D

Magnesium is essential in many vital processes. To correctly describe Mg2+ in physiological processes by molecular dynamics simulations, accurate force fields are fundamental. Despite the importance, force fields based on the commonly used 12-6 Lennard-Jones potential showed significant shortcomings. Recently progress was made by an optimization procedure that implicitly accounts for polarizability. The resulting microMg and nanoMg force fields (J. Chem. Theory Comput. 2021, 17, 2530-2540) accurately reproduce a broad range of experimental solution properties and the binding affinity to nucleic acids in TIP3P water. Since countless simulation studies rely on available water models and ion force fields, we here extend the optimization and provide Mg2+ parameters in combination with the SPC/E, TIP3P-fb, TIP4P/2005, TIP4P-Ew, and TIP4P-D water models. For each water model, the Mg2+ force fields reproduce the solvation free energy, the distance to oxygens in the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, and the binding affinity and distance to the phosphate oxygens on nucleic acids. We present two parameter sets: MicroMg yields water exchange on the microsecond time scale and matches the experimental exchange rate. Depending on the water model, nanoMg yields accelerated water exchange in the range of 106 to 108 exchanges per second. The nanoMg parameters can be used to enhance the sampling of binding events, to obtain converged distributions of Mg2+, or to predict ion binding sites in biomolecular simulations. The parameter files are freely available at https://github.com/bio-phys/optimizedMgFFs.

SAA fibrils involved in AA amyloidosis are similar in bulk and by single particle reconstitution: A MAS solid-state NMR study

AA amyloidosis is one of the most prevalent forms of systemic amyloidosis and affects both humans and other vertebrates. In this study, we compare MAS solid-state NMR data with a recent cryo-EM study of fibrils involving full-length murine SAA1.1. We address the question whether the specific requirements for the reconstitution of an amyloid fibril structure by cryo-EM can potentially yield a bias towards a particular fibril polymorph. We employ fibril seeds extracted from in to vivo material to imprint the fibril structure onto the biochemically produced protein. Sequential assignments yield the secondary structure elements in the fibril state. Long-range DARR and PAR experiments confirm largely the topology observed in the ex-vivo cryo-EM study. We find that the β-sheets identified in the NMR experiments are similar to the β-sheets found in the cryo-EM study, with the exception of amino acids 33–42. These residues cannot be assigned by solid-state NMR, while they adopt a stable β-sheet in the cryo-EM structure. We suggest that the differences between MAS solid-state NMR and cryo-EM data are a consequence of a second conformer involving residues 33–42. Moreover, we were able to characterize the dynamic C-terminal tail of SAA in the fibril state. The C-terminus is flexible, remains detached from the fibrils, and does not affect the SAA fibril structure as confirmed further by molecular dynamics simulations. As the C-terminus can potentially interact with other cellular components, binding to cellular targets can affect its accessibility for protease digestion.

Kinetic pathways of water exchange in the first hydration shell of magnesium: Influence of water model and ionic force field

Water exchange between the first and second hydration shell is essential for the role of Mg²⁺ in biochemical processes. In order to provide microscopic insights into the exchange mechanism, we resolve the exchange pathways by all-atom molecular dynamics simulations and transition path sampling. Since the exchange kinetics relies on the choice of the water model and the ionic force field, we systematically investigate the influence of seven different polarizable and non-polarizable water and three different Mg²⁺ models. In all cases, water exchange can occur either via an indirect or direct mechanism (exchanging molecules occupy different/same position on the water octahedron). In addition, the results reveal a crossover from an interchange dissociative (I_d) to an associative (I_a) reaction mechanism dependent on the range of the Mg²⁺-water interaction potential of the respective force field. Standard non-polarizable force fields follow the I_d mechanism in agreement with experimental results. By contrast, polarizable and long-ranged non-polarizable force fields follow the I_a mechanism. Our results provide a comprehensive view on the influence of the water model and the ionic force field on the exchange dynamics and the foundation to assess the choice of the force field in biomolecular simulations.

Extended magnesium and calcium force field parameters for accurate ion-nucleic acid interactions in biomolecular simulations

Magnesium and calcium play an essential role in the folding and function of nucleic acids. To correctly describe their interactions with DNA and RNA in biomolecular simulations, an accurate parameterization is crucial. In most cases, the ion parameters are optimized based on a set of experimental solution properties such as solvation free energies, radial distribution functions, water exchange rates, and activity coefficient derivatives. However, the transferability of such bulk-optimized ion parameters to quantitatively describe biomolecular systems is limited. Here, we extend the applicability of our previous bulk-optimized parameters by including experimental binding affinities toward the phosphate oxygen on nucleic acids. In particular, we systematically adjust the combination rules that are an integral part of the pairwise interaction potentials of classical force fields. This allows us to quantitatively describe specific ion binding to nucleic acids without changing the solution properties in the most simple and efficient way. We show the advancement of the optimized Lorentz combination rule for two representative nucleic acid systems. For double-stranded DNA, the optimized combination rule for Ca²⁺ significantly improves the agreement with experiments, while the standard combination rule leads to unrealistically distorted DNA structures. For the add A-riboswitch, the optimized combination rule for Mg²⁺ improves the structure of two specifically bound Mg²⁺ ions as judged by the experimental distance to the binding site. Including experimental binding affinities toward specific ion binding sites on biomolecules, therefore, provides a promising perspective to develop a more accurate description of metal cations for biomolecular simulations.

Optimized Magnesium Force Field Parameters for Biomolecular Simulations with Accurate Solvation, Ion-Binding, and Water-Exchange Properties

Magnesium ions play an essential role in many vital processes. To correctly describe their interactions in molecular dynamics simulations, an accurate parametrization is crucial. Despite the importance and considerable scientific effort, current force fields based on the commonly used 12-6 Lennard-Jones interaction potential fail to reproduce a variety of experimental solution properties. In particular, no parametrization exists so far that simultaneously reproduces the solvation free energy and the distance to the water oxygens in the first hydration shell. Moreover, current Mg2+ force fields significantly underestimate the rate of water exchange leading to unrealistically slow exchange kinetics. In order to make progress in the development of improved models, we systematically optimize the Mg2+ parameters in combination with the TIP3P water model in a much larger parameter space than previously done. The results show that a long-ranged interaction potential and modified Lorentz-Berthelot combination rules allow us to accurately reproduce multiple experimental properties including the solvation free energy, the distances to the oxygens of the first hydration shell, the hydration number, the activity coefficient derivative in MgCl2 solutions, the self-diffusion coefficient, and the binding affinity to the phosphate oxygen of RNA. Matching this broad range of thermodynamic properties, we present two sets of optimal parameters: MicroMg yields water exchange on the microsecond timescale in agreement with experiments. NanoMg yields water exchange on the nanosecond timescale facilitating the direct observation of ion-binding events. As shown for the example of the add A-riboswitch, the optimized parameters correctly reproduce the structure of specifically bound ions and permit the de novo prediction of Mg2+-binding sites in biomolecular simulations.

Kinetic pathways of water exchange in the first hydration shell of magnesium

Water exchange between the coordination shells of metal cations in aqueous solutions is fundamental in understanding their role in biochemical processes. Despite the importance, the microscopic mechanism of water exchange in the first hydration shell of Mg²⁺ has not been resolved since the exchange dynamics is out of reach for conventional all-atom simulations. To overcome this challenge, transition path sampling is applied to resolve the kinetic pathways, to characterize the reaction mechanism and to provide an accurate estimate of the exchange rate. The results reveal that water exchange involves the concerted motion of two exchanging water molecules and the collective rearrangement of all water molecules in the first hydration shell. Using a recently developed atomistic model for Mg²⁺, water molecules remain in the first hydration shell for about 40 ms, a time considerably longer compared to the 0.1 ms predicted by transition state theory based on the coordinates of a single water molecule. The discrepancy between these timescales arises from the neglected degrees of freedom of the second exchanging water molecule that plays a decisive role in the reaction mechanism. The approach presented here contributes molecular insights into the dynamics of water around metal cations and provides the basis for developing accurate atomistic models or for understanding complex biological processes involving metal cations.

Hofmeister Series for Metal-Cation-RNA Interactions: The Interplay of Binding Affinity and Exchange Kinetics

A large variety of physicochemical properties involving RNA depends on the type of metal cation present in solution. In order to gain microscopic insight into the origin of these ion specific effects, we apply molecular dynamics simulations to describe the interactions of metal cations and RNA. For the three most common ion binding sites on RNA, we calculate the binding affinities and exchange rates of eight different mono- and divalent metal cations. Our results reveal that binding sites involving phosphate groups preferentially bind metal cations with high charge density (such as Mg²⁺) in inner-sphere conformations while binding sites involving N7 or O6 atoms preferentially bind cations with low charge density (such as K⁺). The binding affinity therefore follows a direct Hofmeister series at the backbone but is reversed at the nucleobases leading to a high selectivity of ion binding sites on RNA. In addition, the exchange rates for cation binding cover almost 5 orders of magnitude, leading to a vastly different time scale for the lifetimes of contact pairs. Taken together, the site-specific binding affinities and the specific lifetime of contact pairs provide the microscopic explanation of ion specific effects observed in a wide variety of macroscopic RNA properties. Finally, combining the results from atomistic simulations with extended Poisson-Boltzmann theory allows us to predict the distribution of metal cations around double-stranded RNA at finite concentrations and to reproduce the results of ion counting experiments with good accuracy.

Ion-Specific and pH-Dependent Hydration of Mica-Electrolyte Interfaces

Hydration forces play a crucial role in a wide range of phenomena in physics, chemistry, and biology. Here, we study the hydration of mica surfaces in contact with various alkali chloride solutions over a wide range of concentrations and pH values. Using atomic force microscopy and molecular dynamics simulations, we demonstrate that hydration forces consist of a superposition of a monotonically decaying and an oscillatory part, each with a unique dependence on the specific type of cation. The monotonic hydration force gradually decreases in strength with decreasing bulk hydration energy, leading to a transition from an overall repulsive (Li⁺, Na⁺) to an attractive (Rb⁺, Cs⁺) force. The oscillatory part, in contrast, displays a binary character, being hardly affected by the presence of strongly hydrated cations (Li⁺, Na⁺), but it becomes completely suppressed in the presence of weakly hydrated cations (Rb⁺, Cs⁺), in agreement with a less pronounced water structure in simulations. For both aspects, K⁺ plays an intermediate role, and decreasing pH follows the trend of increasing Rb⁺ and Cs⁺ concentrations.

Coarse-Grained Double-Stranded RNA Model from Quantum-Mechanical Calculations

A coarse-grained model for simulating structural properties of double-stranded RNA is developed with parameters obtained from quantum-mechanical calculations. This model follows previous parametrization for double-stranded DNA, which is based on mapping the all-atom picture to a coarse-grained four-bead scheme. Chemical and structural differences between RNA and DNA have been taken into account for the model development. The parametrization is based on simulations using density functional theory (DFT) on separate units of the RNA molecule without implementing experimental data. The total energy is decomposed into four terms of physical significance: hydrogen bonding interaction, stacking interactions, backbone interactions, and electrostatic interactions. The first three interactions are treated within DFT, whereas the last one is included within a mean field approximation. Our double-stranded RNA coarse-grained model predicts stable helical structures for RNA. Other characteristics, such as structural or mechanical properties are reproduced with a very good accuracy. The development of the coarse-grained model for RNA allows extending the spatial and temporal length scales accessed by computer simulations and being able to model RNA-related biophysical processes, as well as novel RNA nanostructures.

Mechanism of Nucleation and Growth of Aβ40 Fibrils from All-Atom and Coarse-Grained Simulations

In this work, we characterize the nucleation and elongation mechanisms of the "diseased" polymorph of the amyloid-β 40 (Aβ40) fibril using an off-lattice coarse-grained (CG) protein model. After determining the nucleation size and subsequent stable protofibrillar structure from the CG model, validated with all-atom simulations, we consider the "lock and dock" and "activated monomer" fibril elongation mechanisms for the protofibril by statistical additions of a monomer drawn from four different ensembles of the free Aβ40 peptide to grow the fibril. Our CG model shows that the dominant mechanism for fibril elongation is the lock and dock mechanism across all monomer ensembles, even when the monomer is in the activated form. Although our CG model finds no thermodynamic difference between the two fibril elongation mechanisms, the activated monomer is found to be kinetically faster by a factor of 2 for the "locking" step compared with all other structured or unstructured monomer ensembles.

Mechanism of Reversible Peptide-Bilayer Attachment: Combined Simulation and Experimental Single-Molecule Study

The binding of peptides and proteins to lipid membrane surfaces is of fundamental importance for many membrane-mediated cellular processes. Using closely matched molecular dynamics simulations and atomic force microscopy experiments, we study the force-induced desorption of single peptide chains from phospholipid bilayers to gain microscopic insight into the mechanism of reversible attachment. This approach allows quantification of desorption forces and decomposition of peptide-membrane interactions into energetic and entropic contributions. In both simulations and experiments, the desorption forces of peptides with charged and polar side chains are much smaller than those for hydrophobic peptides. The adsorption of charged/polar peptides to the membrane surface is disfavored by the energetic components, requires breaking of hydrogen bonds involving the peptides, and is favored only slightly by entropy. By contrast, the stronger adsorption of hydrophobic peptides is favored both by energy and by entropy and the desorption forces increase with increasing side-chain hydrophobicity. Interestingly, the calculated net adsorption free energies per residue correlate with experimental results of single residues, indicating that side-chain free energy contributions are largely additive. This observation can help in the design of peptides with tailored adsorption properties and in the estimation of membrane binding properties of peripheral membrane proteins.

Dynamics of Seeded Aβ40-Fibril Growth from Atomistic Molecular Dynamics Simulations: Kinetic Trapping and Reduced Water Mobility in the Locking Step

Filamentous β-amyloid aggregates are crucial for the pathology of Alzheimer's disease. Despite the tremendous biomedical importance, the molecular pathway of growth propagation is not completely understood and remains challenging to investigate by simulations due to the long time scales involved. Here, we apply extensive all-atom molecular dynamics simulations in explicit water to obtain free energy profiles and kinetic information from position-dependent diffusion profiles for three different Aβ9-40-growth processes: fibril elongation by single monomers at the structurally unequal filament tips and association of larger filament fragments. Our approach provides insight into the molecular steps of the kinetic pathway and allows close agreement with experimental binding free energies and macroscopic growth rates. Water plays a decisive role, and solvent entropy is identified as the main driving force for assembly. Fibril growth is disfavored energetically due to cancellation of direct peptide-peptide interactions and solvation effects. The kinetics of growth is consistent with the characteristic dock/lock mechanism, and docking is at least 2 orders of magnitude faster. During initial docking, interactions are mediated by transient non-native hydrogen bonds, which efficiently catch the incoming monomer or fragment already at separations of about 3 nm. In subsequent locking, the dynamics is much slower due to formation of kinetically trapped conformations caused by long-lived non-native hydrogen bonds. Fibril growth additionally requires collective motion of water molecules to create a dry binding interface. Fibril growth is further retarded due to reduced mobility of the involved hydration water, evident from a 2-fold reduction of the diffusion coefficient.

Specific ion binding to carboxylic surface groups and the pH dependence of the Hofmeister series

Ion binding to acidic groups is a central mechanism for ion-specificity of macromolecules and surfaces. Depending on pH, acidic groups are either protonated or deprotonated and thus change not only charge but also chemical structure with crucial implications for their interaction with ions. In a two-step modeling approach, we first determine single-ion surface interaction potentials for a few selected halide and alkali ions at uncharged carboxyl (COOH) and charged carboxylate (COO(-)) surface groups from atomistic MD simulations with explicit water. Care is taken to subtract the bare Coulomb contribution due to the net charge of the carboxylate group and thereby to extract the nonelectrostatic ion-surface potential. Even at this stage, pronounced ion-specific effects are observed and the ion surface affinity strongly depends on whether the carboxyl group is protonated or not. In the second step, the ion surface interaction potentials are used in a Poisson-Boltzmann model to calculate the surface charge and the potential distribution in the solution depending on salt type, salt concentration, and solution pH in a self-consistent manner. Hofmeister phase diagrams are derived on the basis of the long-ranged forces between two carboxyl-functionalized surfaces. For cations we predict direct, reversed, and altered Hofmeister series as a function of the pH, qualitatively similar to recent experimental results for silica surfaces. The Hofmeister series reversal for cations is rationalized by a reversal of the single-cation affinity to the carboxyl group depending on its protonation state: the deprotonated carboxylate (COO(-)) surface group interacts most favorably with small cations such as Li(+) and Na(+), whereas the protonated carboxyl (COOH) surface group interacts most favorably with large cations such as Cs(+) and thus acts similarly to a hydrophobic surface group. Our results provide a general mechanism for the pH-dependent reversal of the Hofmeister series due to the different specific ion binding to protonated and deprotonated surface groups.

Anionic and cationic Hofmeister effects on hydrophobic and hydrophilic surfaces

Using a two-step modeling approach, we address the full spectrum of direct, reversed, and altered ionic sequences as the charge of the ion, the charge of the surface, and the surface polarity are varied. From solvent-explicit molecular dynamics simulations, we extract single-ion surface interaction potentials for halide and alkali ions at hydrophilic and hydrophobic surfaces. These are used within Poisson-Boltzmann theory to calculate ion density and electrostatic potential distributions at mixed polar/unpolar surfaces for varying surface charge. The resulting interfacial tension increments agree quantitatively with experimental data and capture the Hofmeister series, especially the anomaly of lithium, which is difficult to obtain using continuum theory. Phase diagrams that feature different Hofmeister series as a function of surface charge, salt concentration, and surface polarity are constructed from the long-range force between two surfaces interacting across electrolyte solutions. Large anions such as iodide have a high hydrophobic surface affinity and increase the effective charge magnitude on negatively charged unpolar surfaces. Large cations such as cesium also have a large hydrophobic surface affinity and thereby compensate an external negative charge surface charge most efficiently, which explains the well-known asymmetry between cations and anions. On the hydrophilic surface, the size-dependence of the ion surface affinity is reversed, explaining the Hofmeister series reversal when comparing hydrophobic with hydrophilic surfaces.

Effects of confinement and external fields on structure and transport in colloidal dispersions in reduced dimensionality

In this work, we focus on low-dimensional colloidal model systems, via simulation studies and also some complementary experiments, in order to elucidate the interplay between phase behavior, geometric structures and transport properties. In particular, we try to investigate the (nonlinear!) response of these very soft colloidal systems to various perturbations: uniform and uniaxial pressure, laser fields, shear due to moving boundaries and randomly quenched disorder. We study ordering phenomena on surfaces or in monolayers by Monte Carlo computer simulations of binary hard-disk mixtures, the influence of a substrate being modeled by an external potential. Weak external fields allow a controlled tuning of the miscibility of the mixture. We discuss the laser induced de-mixing for the three different possible couplings to the external potential. The structural behavior of hard spheres interacting with repulsive screened Coulomb or dipolar interaction in 2D and 3D narrow constrictions is investigated using Brownian dynamics simulations. Due to misfits between multiples of the lattice parameter and the channel widths, a variety of ordered and disordered lattice structures have been observed. The resulting local lattice structures and defect probabilities are studied for various cross sections. The influence of a self-organized order within the system is reflected in the velocity of the particles and their diffusive behavior. Additionally, in an experimental system of dipolar colloidal particles confined by gravity on a solid substrate we investigate the effect of pinning on the dynamics of a two-dimensional colloidal liquid. This work contains sections reviewing previous work by the authors as well as new, unpublished results. Among the latter are detailed studies of the phase boundaries of the de-mixing regime in binary systems in external light fields, configurations for shear induced effects at structured walls, studies on the effect of confinement on the structures and defect densities in three-dimensional systems, the effect of confinement and barriers on two-dimensional flow and diffusion, and the effect of pinning sites on the diffusion.

On the relationship between peptide adsorption resistance and surface contact angle: a combined experimental and simulation single-molecule study

The force-induced desorption of single peptide chains from mixed OH/CH(3)-terminated self-assembled monolayers is studied in closely matched molecular dynamics simulations and atomic force microscopy experiments with the goal to gain microscopic understanding of the transition between peptide adsorption and adsorption resistance as the surface contact angle is varied. In both simulations and experiments, the surfaces become adsorption resistant against hydrophilic as well as hydrophobic peptides when their contact angle decreases below θ ≈ 50°-60°, thus confirming the so-called Berg limit established in the context of protein and cell adsorption. Entropy/enthalpy decomposition of the simulation results reveals that the key discriminator between the adsorption of different residues on a hydrophobic monolayer is of entropic nature and thus is suggested to be linked to the hydrophobic effect. By pushing a polyalanine peptide onto a polar surface, simulations reveal that the peptide adsorption resistance is caused by the strongly bound water hydration layer and characterized by the simultaneous gain of both total entropy in the system and total number of hydrogen bonds between water, peptide, and surface. This mechanistic insight into peptide adsorption resistance might help to refine design principles for anti-fouling surfaces.

Effective interaction between two ion-adsorbing plates: Hofmeister series and salting-in/salting-out phase diagrams from a global mean-field analysis

Interactions between ions and solutes are key to ion-specificity. A generic model in which ions interact via square well potentials of finite range with charged plates is solved analytically on the Poisson-Boltzmann level and analyzed globally for varying surface charge, salt concentration, and ion-surface affinity. Ion adsorption as well as depletion can lead to stably bound plates at finite separation, relevant for the equilibrium salting-out of small solutes such as proteins. The interplate pressure at large plate separation, relevant for aggregation kinetics of large solutes, exhibits direct as well as indirect Hofmeister ordering, depending on surface charge and salt concentration. A simple method for mapping explicit ion-surface potentials of mean force as obtained from solvent-explicit molecular dynamics simulations onto square-well potential parameters is demonstrated.

The effect of temperature on single-polypeptide adsorption

The hydrophobic attraction (HA) is believed to be one of the main driving forces for protein folding. Understanding its temperature dependence promises a deeper understanding of protein folding. Herein, we present an approach to investigate the HA with a combined experimental and simulation approach, which is complementary to previous studies on the temperature dependence of the solvation of small hydrophobic spherical particles. We determine the temperature dependence of the free-energy change and detachment length upon desorption of single polypeptides from hydrophobic substrates in aqueous environment. Both the atomic force microscopy (AFM) based experiments and the molecular dynamics (MD) simulations show only a weak dependence of the free energy change on temperature. In fact, depending on the substrate, we find a maximum or a minimum in the temperature-dependent free energy change, meaning that the entropy increases or decreases with temperature for different substrates. These observations are in contrast to the solvation of small hydrophobic particles and can be rationalized by a compensation mechanism between the various contributions to the desorption force. On the one hand this is reminiscent of the protein folding process, where large entropic and enthalpic contributions compensate each other to result in a small free energy difference between the folded and unfolded state. On the other hand, the protein folding process shows much stronger temperature dependence, pointing to a fundamental difference between protein folding and adsorption. Nevertheless such temperature dependent single molecule desorption studies open large possibilities to study equilibrium and non-equilibrium processes dominated by the hydrophobic attraction.

Attractive double-layer forces between neutral hydrophobic and neutral hydrophilic surfaces

The interaction between surface patches of proteins with different surface properties has a vital role to play driving conformational changes in proteins in different salt solutions. We demonstrate the existence of ion-specific attractive double-layer forces between neutral hydrophobic and hydrophilic surfaces in the presence of certain salt solutions. This is performed by solving a generalized Poisson-Boltzmann equation for two unequal surfaces. In the calculations, we utilize parametrized ion-surface potentials and dielectric-constant profiles deduced from recent non-primitive-model molecular dynamics simulations that partially account for molecular structure and hydration effects.

Colloidal systems in three-dimensional microchannels: lattice control via channel width and external force

The structural behavior of hard spheres interacting with repulsive (screened Coulomb) interaction in narrow constrictions is investigated using Brownian dynamics simulations. The system of particles adapts to the confining potential and the interaction energies by a self-consistent arrangement of the particles. It results in the formation of planes throughout the three-dimensional channel. The presence of hard walls leads to structural deviations from the unbounded (infinite) crystal. The arrangement of the particles is perturbed by diffusion and an external driving force leading to a density gradient along the channel. The particles accommodate to the density gradient by reducing the number of planes if it is energetically favorable. This reduction in the number of planes is analogous to the reduction in the number of layers in two-dimensional systems. The influence of a self-organized order within the system is reflected in the velocity of the particles and their diffusive behavior.

Reversed anionic Hofmeister series: the interplay of surface charge and surface polarity

We describe a two-scale modeling approach toward anion specificity at surfaces of varying charge and polarity. Explicit-solvent atomistic molecular dynamics simulations at neutral hydrophobic (i.e., nonpolar) and neutral hydrophilic (i.e., polar) self-assembled monolayers furnish potentials of mean force for Na(+) and the halide anions F(-), Cl(-), and I(-) which are then used within Poisson-Boltzmann theory to calculate ionic distributions at surfaces of arbitrary charge for finite ion concentration. On the basis of calculated long-ranged electrostatic forces and coagulation properties, we obtain the direct anionic Hofmeister series at negatively charged hydrophobic surfaces. Reversal takes place when going to negative polar or to positive nonpolar surfaces, leading to the indirect series, while for positive polar surfaces the direct series is again obtained. This is in full accordance with a recent experimental classification of colloidal coagulation kinetics and also reflects the trends of the ion specific solubility properties of proteins. A schematic Hofmeister phase diagram is proposed. Partial series reversal is understood as a transient phenomenon for surfaces of intermediate polarity or charge.