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Using a coarse-grained lipid and peptide model, we show that the free energy stabilization of amyloid-β in heterogeneous lipid membranes is predicted to have a dependence on asymmetric distributions of cholesterol compositions across the membrane leaflets. We find that a highly asymmetric cholesterol distribution that is depleted on the exofacial leaflet but enhanced on the cytofacial leaflet of the model lipid membrane thermodynamically favors membrane retention of a fully embedded Aβ peptide. However, in the case of cholesterol redistribution that increases concentration of cholesterol on the exofacial layer, typical of aging or Alzheimer's disease, the free energy favors peptide extrusion of the highly reactive N-terminus into the extracellular space that may be vulnerable to aggregation, oligomerization, or deleterious oxidative reactivity.

Using homonuclear (1)H NOESY spectra, with chemical shifts, (3)JH(N)H(α) scalar couplings, residual dipolar couplings, and (1)H-(15)N NOEs, we have optimized and validated the conformational ensembles of the amyloid-β 1-40 (Aβ40) and amyloid-β 1-42 (Aβ42) peptides generated by molecular dynamics simulations. We find that both peptides have a diverse set of secondary structure elements including turns, helices, and antiparallel and parallel β-strands. The most significant difference in the structural ensembles of the two peptides is the type of β-hairpins and β-strands they populate. We find that Aβ42 forms a major antiparallel β-hairpin involving the central hydrophobic cluster residues (16-21) with residues 29-36, compatible with known amyloid fibril forming regions, whereas Aβ40 forms an alternative but less populated antiparallel β-hairpin between the central hydrophobic cluster and residues 9-13, that sometimes forms a β-sheet by association with residues 35-37. Furthermore, we show that the two additional C-terminal residues of Aβ42, in particular Ile-41, directly control the differences in the β-strand content found between the Aβ40 and Aβ42 structural ensembles. Integrating the experimental and theoretical evidence accumulated over the last decade, it is now possible to present monomeric structural ensembles of Aβ40 and Aβ42 consistent with available information that produce a plausible molecular basis for why Aβ42 exhibits greater fibrillization rates than Aβ40.

We have recently introduced a method termed Poisson-Boltzmann semianalytical method (PB-SAM) for solving the linearized Poisson-Boltzmann equation for large numbers of arbitrarily shaped dielectric cavities with controlled precision. In this work we extend the applicability of the PB-SAM approach by deriving force and torque expressions that fully account for mutual polarization in both the zero- and first-order derivatives of the surface charges, that can now be embedded into a Brownian dynamics scheme to look at electrostatic-driven mesoscale assembly and kinetics. We demonstrate the capabilities of the PB-SAM approach by simulating the protein concentration effects on the bimolecular rate of association of barnase and barstar, under periodic boundary conditions and evaluated through mean first passage times. We apply PB-SAM to the pseudo-first-order reaction rate conditions in which either barnase or barstar are in great excess relative to the other protein (124:1). This can be considered a specific case in which the PB-SAM approach can be applied to crowding conditions in which crowders are not inert but can form interactions with other molecules.

The energy landscape is analyzed for off-lattice bead models of protein L and protein G as a function of a static pulling force. Two different pairs of attachment points (pulling directions) are compared in each case, namely, residues 1/56 and 10/32. For the terminal residue pulling direction 1/56, the distinct global minimum structures are all extended, aside from the compact geometry that correlates with zero force. The helical turns finally disappear at the highest pulling forces considered. For the 10/32 pulling direction, the changes are more complicated, with a variety of competing arrangements for beads outside the region where the force is directly applied. These alternatives produce frustrated energy landscapes, with low-lying minima separated by high barriers. The calculated folding pathways in the absence of force are in good agreement with previous work. The N-terminal hairpin folds first for protein L and the C-terminal hairpin for protein G, which exhibits an intermediate. However, for a relatively low static force, where the global minimum retains its structure, the folding mechanisms change, sometimes dramatically, depending on the protein and the attachment points. The scaling relations predicted by catastrophe theory are found to hold in the limit of short path lengths.

An accurate representation of solute-water interactions is necessary for molecular dynamics simulations of biomolecules that reside in aqueous environments. Modern force fields and advanced water models describe solute-solute and water-water interactions reasonably accurately but have known shortcomings in describing solute-water interactions, demonstrated by the large differences between calculated and experimental solvation free energies across a range of peptide and drug chemistries. In this work, we introduce a method for optimizing solute-water van der Waals interactions to reproduce experimental solvation free energy data and apply it to the optimization of a fixed charge force field (AMBER ff99SB/GAFF) and advanced water model (TIP4P-Ew). We show that, with these optimizations, the combination of AMBER ff99SB/GAFF and TIP4P-Ew is able to reproduce the solvation free energies of a variety of biologically relevant small molecules to within 1.0 k(B)T. We further validate these optimizations by examining the aggregation propensities of dipeptide-water solutions, the conformational preferences of short disordered peptides, and the native state stability and dynamics of a folded protein.

We present a reinvestigation of sulfate-water clusters SO4(2-) (H2O)(n=3-7), which involves several new aspects. Using a joint molecular mechanics/first principles approach, we perform exhaustive searches for stable cluster geometries, showing that the sulfate-water landscape is much richer than anticipated previously. We check the compatibility of the new structures with experiment by comparing vertical detachment energies (VDEs) calculated at the B3LYP/6-311++G** level of theory and determine the energetic ordering of the isomers at the RI-MP2/aug-cc-pVTZ level. Our results are bench-marked carefully against reference energies of estimated CCSD(T)/aug-cc-VTZ quality and VDEs of CCSD(T)/aug-cc-pVDZ quality. Furthermore, we calculate anharmonic vibrational corrections for up to the n = 6 clusters, which are shown to be significant for isomer energy ordering. We use energy decomposition analysis (EDA) based on the absolutely localized fragment (ALMO) expansion to gain chemical insight into the binding motifs.

We present a reinvestigation of sulfate-water clusters SO4(2-) (H2O)(n=3-7), which involves several new aspects. Using a joint molecular mechanics/first principles approach, we perform exhaustive searches for stable cluster geometries, showing that the sulfate-water landscape is much richer than anticipated previously. We check the compatibility of the new structures with experiment by comparing vertical detachment energies (VDEs) calculated at the B3LYP/6-311++G** level of theory and determine the energetic ordering of the isomers at the RI-MP2/aug-cc-pVTZ level. Our results are bench-marked carefully against reference energies of estimated CCSD(T)/aug-cc-VTZ quality and VDEs of CCSD(T)/aug-cc-pVDZ quality. Furthermore, we calculate anharmonic vibrational corrections for up to the n = 6 clusters, which are shown to be significant for isomer energy ordering. We use energy decomposition analysis (EDA) based on the absolutely localized fragment (ALMO) expansion to gain chemical insight into the binding motifs.

The interplay of modern molecular simulation and high-quality nuclear magnetic resonance (NMR) experiments has reached a fruitful stage for quantitative characterization of structural ensembles of disordered peptides. Amyloid-β 1-42 (Aβ42), the primary peptide associated with Alzheimer's disease, and fragments such as Aβ21-30 are both classified as intrinsically disordered peptides (IDPs). We use a variety of NMR observables to validate de novo molecular dynamics simulations in explicit water to characterize the tertiary structure ensemble of Aβ42 and Aβ21-30 from the perspective of their classification as IDPs. Unlike the Aβ21-30 fragment that conforms to expectations of an IDP that is primarily extended, we find that Aβ42 samples conformations reflecting all possible secondary structure categories and spans the range of IDP classifications from collapsed structured states to highly extended conformations, making it an IDP with a far more heterogeneous tertiary ensemble.

We use a novel normal mode analysis of an elastic network model drawn from configurations generated during microsecond all-atom molecular dynamics simulations to analyze the mechanism of auto-inhibition of AMP-activated protein kinase (AMPK). A recent X-ray and mutagenesis experiment (Chen, et al Nature 2009, 459, 1146) of the AMPK homolog S. Pombe sucrose non-fermenting 1 (SNF1) has proposed a new conformational switch model involving the movement of the kinase domain (KD) between an inactive unphosphorylated open state and an active or semi-active phosphorylated closed state, mediated by the autoinhibitory domain (AID), and a similar mutagenesis study showed that rat AMPK has the same auto-inhibition mechanism. However, there is no direct dynamical evidence to support this model and it is not clear whether other functionally important local structural components are equally inhibited. By using the same SNF1 KD-AID fragment as that used in experiment, we show that AID inhibits the catalytic function by restraining the KD into an unproductive open conformation, thereby limiting local structural rearrangements, while mutations that disrupt the interactions between the KD and AID allow for both the local structural rearrangement and global interlobe conformational transition. Our calculations further show that the AID also greatly impacts the structuring and mobility of the activation loop.

We present the simulated photoelectron spectrum (PES) for cyanide-water CN(H(2)O)(-) based on quasiclassical trajectory molecular dynamics (QCT-MD). Using density functional theory to generate trajectories and to calculate vertical detachment energies, we obtain simulated spectra that are in qualitative agreement with experiment. We obtain a theoretical 12 → 300 K temperature red shift of 0.1 eV as compared to an experimental redshift of 0.25 eV. The calculated linewidths of 0.3 eV are in excellent agreement with experiment. Our trajectories show that the temperature red shift as being dominated by dynamics within the basin of the N-bound minimum, however, at 300 K we predict conversion into the basin of the C-bound minimum, equilibrating at a 80:20 ratio of N- vs C-bound mixture. We discuss the potential advantages of QCT-MD over anharmonic Franck-Condon analysis such as natural incorporation of anharmonicity (as necessary for weakly bound systems), and reduced computational scaling, but also drawbacks such as neglect of final-state (e.g., Duschinsky) effects.

While most force field efforts in biomolecular simulation have focused on the parametrization of the protein, relatively little attention has been paid to the quality of the accompanying solvent model. These considerations are especially relevant for simulations of intrinsically disordered peptides and proteins, for which energy differences between conformations are small and interactions with water are enhanced. In this work, we investigate the accuracy of the AMBER ff99SB force field when combined with the standard TIP3P model or the more recent TIP4P-Ew water model, to generate conformational ensembles for disordered trialanine (Ala3), triglycine (Gly3), and trivaline (Val3) peptides. We find that the TIP4P-Ew water model yields significantly better agreement with experimentally measured scalar couplings-and therefore more accurate conformational ensembles-for both Ala3 and Gly3. For Val3, however, we find that the TIP3P and TIP4P-Ew ensembles are equivalent in their performance. To further improve the protein-water force field combination and obtain more accurate intrinsic conformational preferences, we derive a straightforward perturbation to the ϕ' backbone dihedral potential that shifts the β-PPII equilibrium. We find that the revised ϕ' backbone dihedral potential yields improved conformational ensembles for a variety of small peptides and maintains the stability of the globular ubiquitin protein in TIP4P-Ew water.

While most force field efforts in biomolecular simulation have focused on the parametrization of the protein, relatively little attention has been paid to the quality of the accompanying solvent model. These considerations are especially relevant for simulations of intrinsically disordered peptides and proteins, for which energy differences between conformations are small and interactions with water are enhanced. In this work, we investigate the accuracy of the AMBER ff99SB force field when combined with the standard TIP3P model or the more recent TIP4P-Ew water model, to generate conformational ensembles for disordered trialanine (Ala3), triglycine (Gly3), and trivaline (Val3) peptides. We find that the TIP4P-Ew water model yields significantly better agreement with experimentally measured scalar couplings-and therefore more accurate conformational ensembles-for both Ala3 and Gly3. For Val3, however, we find that the TIP3P and TIP4P-Ew ensembles are equivalent in their performance. To further improve the protein-water force field combination and obtain more accurate intrinsic conformational preferences, we derive a straightforward perturbation to the ϕ' backbone dihedral potential that shifts the β-PPII equilibrium. We find that the revised ϕ' backbone dihedral potential yields improved conformational ensembles for a variety of small peptides and maintains the stability of the globular ubiquitin protein in TIP4P-Ew water.

In the past decade, significant progress has been made in protein structure prediction. However, refining models to a level of resolution that is comparable with experimental results and can be used in studies like enzymatic activity still remains a major challenge. We have previously demonstrated that our modular protein-solvent energy function, uniquely involving a potential of mean force description for hydrophobic solvation, works well in protein globular structure prediction and loop modeling. In this work, we couple protein-solvent energy function with our global optimization method stochastic perturbation with soft constraints and use them to refine a collection of template models from submitted predictions to recent Critical Assessment of Techniques for Protein Structure Prediction blind prediction contests. A prediction protocol based on a selection of structures with the lowest energy is able to successfully refine all of the test proteins, and, more importantly, our energy function does not show degradation in prediction when sampling is exhausted.

It is widely recognized that representing a protein as a single static conformation is inadequate to describe the dynamics essential to the performance of its biological function. We contrast the amino acid displacements below and above the protein dynamical transition temperature, T(D)∼215K, of hen egg white lysozyme using X-ray crystallography ensembles that are analyzed by molecular dynamics simulations as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above T(D), and they remain virtually identical to structural motions measured at 300K. Our results highlight the ability to observe functional structural variations across an ensemble of X-ray crystallographic data, and that residue fluctuations measured in MD simulations at room temperature are in quantitative agreement with the experimental observable.

Structural polyamorphism has been promoted as a means for understanding the anomalous thermodynamics and dynamics of water in the experimentally inaccessible supercooled region. In the metastable liquid region, theory has hypothesized the existence of a liquid-liquid critical point from which a dividing line separates two water species of high and low density. A recent small-angle X-ray scattering study has claimed that the two structural species postulated in the supercooled state are seen to exist in bulk water at ambient conditions. We analyze new small-angle X-ray scattering data on ambient liquid water taken at third generation synchrotron sources, and large 32,000 water molecule simulations using the TIP4P-Ew model of water, to show that the small-angle region measures standard number density fluctuations consistent with water's isothermal compressibility temperature trends. Our study shows that there is no support or need for heterogeneities in water structure at room temperature to explain the small-angle scattering data, as it is consistent with a unimodal density of the tetrahedral liquid at ambient conditions.

We derive a new numerical approach to solving the linearized Poisson Boltzmann equation (PBE) by representing the protein surface as a collection of spheres in which the surface charges can then be iteratively solved by new analytical multipole methods previously introduced by us [Lotan & Head-Gordon, 2006]. We show that our Poisson Boltzmann semi-analytical method, PB-SAM, realizes better accuracy, more flexible memory management, and at reduced cost relative to either finite difference or boundary element method PBE solvers. We provide two new benchmarks of PBE solution accuracy to test the numerical PBE solutions based on (1) arrays of up to hundreds of spherical low dielectric geometries with asymmetric charges in which mutual polarization is treated exactly, and (2) two overlapping spheres with increasing charge asymmetry by solving the PB-SAM method to very high pole order. We illustrate the strength of the PB-SAM approach by computing the potential profile of an array of 60 T1-particle forming monomers of the bromine mosaic virus.

We present what we believe to be a novel statistical contact potential based on solved structures of transmembrane (TM) alpha-helical bundles, and we use this contact potential to investigate the amino acid likelihood of stabilizing helix-helix interfaces. To increase statistical significance, we have reduced the full contact energy matrix to a four-flavor alphabet of amino acids, automatically determined by our methodology, in which we find that polarity is a more dominant factor of group identity than is size, with charged or polar groups most often occupying the same face, whereas polar/apolar residue pairs tend to occupy opposite faces. We found that the most polar residues strongly influence interhelical contact formation, although they occur rarely in TM helical bundles. Two-body contact energies in the reduced letter code are capable of determining native structure from a large decoy set for a majority of test TM proteins, at the same time illustrating that certain higher-order sequence correlations are necessary for more accurate structure predictions.

We present what we believe to be a novel statistical contact potential based on solved structures of transmembrane (TM) alpha-helical bundles, and we use this contact potential to investigate the amino acid likelihood of stabilizing helix-helix interfaces. To increase statistical significance, we have reduced the full contact energy matrix to a four-flavor alphabet of amino acids, automatically determined by our methodology, in which we find that polarity is a more dominant factor of group identity than is size, with charged or polar groups most often occupying the same face, whereas polar/apolar residue pairs tend to occupy opposite faces. We found that the most polar residues strongly influence interhelical contact formation, although they occur rarely in TM helical bundles. Two-body contact energies in the reduced letter code are capable of determining native structure from a large decoy set for a majority of test TM proteins, at the same time illustrating that certain higher-order sequence correlations are necessary for more accurate structure predictions.

We review the spectroscopic techniques and scattering experiments used to probe the structure of water, and their interpretation using empirical and ab initio models, over the last 5 years. We show that all available scientific evidence overwhelmingly favors the view of classifying water near ambient conditions as a uniform, continuous tetrahedral liquid. While there are controversial issues in our understanding of water in the supercooled state, in confinement, at interfaces, or in solution, there is no real controversy in what is understood as regards bulk liquid water under ambient conditions. © 2010 Taylor & Francis.

We derive a new numerical approach to solving the linearized Poisson Boltzmann equation (PBE) by representing the protein surface as a collection of spheres in which the surface charges can then be iteratively solved by new analytical multipole methods previously introduced by us [Lotan & Head-Gordon, 2006]. We show that our Poisson Boltzmann semi-analytical method, PB-SAM, realizes better accuracy, more flexible memory management, and at reduced cost relative to either finite difference or boundary element method PBE solvers. We provide two new benchmarks of PBE solution accuracy to test the numerical PBE solutions based on (1) arrays of up to hundreds of spherical low dielectric geometries with asymmetric charges in which mutual polarization is treated exactly, and (2) two overlapping spheres with increasing charge asymmetry by solving the PB-SAM method to very high pole order. We illustrate the strength of the PB-SAM approach by computing the potential profile of an array of 60 T1-particle forming monomers of the bromine mosaic virus.

We develop a coarse-grained parametrization strategy for lipid membranes that we illustrate for a dipalmitoylphosphatidylcholine bilayer. Our coarse-graining approach eliminates the high cost of explicit solvent but maintains more lipid interaction sites. We use a broad attractive tail-tail potential and extract realistic bonded potentials of mean force from all-atom simulations, resulting in a model with a sharp gel to fluid transition, a correct bending modulus, and overall very reasonable dynamics when compared with experiment. We also determine a quantitative stress profile and correct breakdown of contributions from lipid components when compared with detailed all-atom simulation benchmarks, which has been difficult to achieve for implicit membrane models. Such a coarse-grained lipid model will be necessary for efficiently simulating complex constructs of the membrane, such as protein assembly and lipid raft formation, within these nonaqueous chemical environments.

We present a novel sampling approach to explore large protein conformational transitions by determining unique substates from instantaneous normal modes calculated from an elastic network model, and applied to a progression of atomistic molecular dynamics snapshots. This unbiased sampling scheme allows us to direct the path sampling between the conformational end states over simulation timescales that are greatly reduced relative to the known experimental timescales. We use adenylate kinase as a test system to show that instantaneous normal modes can be used to identify substates that drive the structural fluctuations of adenylate kinase from its closed to open conformations, in which we observe 16 complete transitions in 4 mus of simulation time, reducing the timescale over conventional simulation timescales by two orders of magnitude. Analysis shows that the unbiased determination of substates is consistent with known pathways determined experimentally.

Molecular force fields have been approaching a generational transition over the past several years, moving away from well-established and well-tuned, but intrinsically limited, fixed point charge models toward more intricate and expensive polarizable models that should allow more accurate description of molecular properties. The recently introduced AMOEBA force field is a leading publicly available example of this next generation of theoretical model, but to date, it has only received relatively limited validation, which we address here. We show that the AMOEBA force field is in fact a significant improvement over fixed charge models for small molecule structural and thermodynamic observables in particular, although further fine-tuning is necessary to describe solvation free energies of drug-like small molecules, dynamical properties away from ambient conditions, and possible improvements in aromatic interactions. State of the art electronic structure calculations reveal generally very good agreement with AMOEBA for demanding problems such as relative conformational energies of the alanine tetrapeptide and isomers of water sulfate complexes. AMOEBA is shown to be especially successful on protein-ligand binding and computational X-ray crystallography where polarization and accurate electrostatics are critical.

We have devised a systematic approach to converge a replica exchange molecular dynamics simulation by dividing the full temperature range into a series of higher temperature reservoirs and a finite number of lower temperature subreplicas. A defined highest temperature reservoir of equilibrium conformations is used to help converge a lower but still hot temperature subreplica, which in turn serves as the high-temperature reservoir for the next set of lower temperature subreplicas. The process is continued until an optimal temperature reservoir is reached to converge the simulation at the target temperature. This gradual convergence of subreplicas allows for better and faster convergence at the temperature of interest and all intermediate temperatures for thermodynamic analysis, as well as optimizing the use of multiple processors. We illustrate the overall effectiveness of our multiple reservoir replica exchange strategy by comparing sampling and computational efficiency with respect to replica exchange, as well as comparing methods when converging the structural ensemble of the disordered Abeta(21-30) peptide simulated with explicit water by comparing calculated Rotating Overhauser Effect Spectroscopy intensities to experimentally measured values.

We perform neutron diffraction and quasi-elastic neutron scattering (QENS) to probe hydration water structure, and dynamics down to supercooled temperatures, of a concentrated amphiphilic peptide system with the co-solvents glycerol and dimethyl sulfoxide. We find that the kosmotropic co-solvent glycerol preserves the hydration structure near the peptide that is observed in the water solvent alone, that in turn preserves the dynamical temperature trends of two water relaxation processes--one corresponding to a localized relaxation process of the peptide bound surface water and a second relaxation process of the outer hydration layers. By contrast the chaotropic co-solvent, by disrupting the hydration layer near the peptide surface, eliminates the inner hydration layer relaxation process induced by the peptide, to show a single time scale for translational water dynamics.

We evaluate the molecular response of hydration water as a function of temperature and proximity to the surface of the peptide N-acetyl-leucine-methylamide (NALMA) when in the presence of the kosmotrope co-solvent glycerol or the chaotrope co-solvent dimethyl sulfoxide (DMSO), using molecular dynamics simulation with a polarizable force field. These detailed microscopic studies complement established thermodynamic analysis on the role of co-solvents in shifting the equilibrium for proteins away from or towards the native folded state. We find that the structure of the water at the peptide interfaces reflects an increase in hydration number in the glycerol solution and a decrease in hydration numbers in the DMSO solution. While the water dynamics around NALMA in the presence of both co-solvents is slower than that observed with the water solvent alone, in the DMSO mixture we no longer measure a separation in water motion time scales at low temperatures as is seen in the pure water solvent, but rather one single relaxation time. In the glycerol, however, we do observe a separation of time scales at low temperatures, supporting the hypothesis that hydration water near a hydrophobic solute evolves on a separate time scale than the extensive hydrogen-bonding network of more bulk-like water. Our simulation studies highlight the differences in the two co-solvent solutions due to the relative frequency of water contacts with the hydrophobic vs. hydrophilic peptide surface, and direct water interactions with the co-solvents.

We characterize the molecular dynamics of a previously described computational de novo designed enzyme optimized to perform a multistep retrol-aldol reaction when engineered into a TIM barrel protein scaffold. The molecular dynamics simulations show that the protein dynamics under physiological conditions of temperature and aqueous environment distorts the designed geometric factors of the substrate-enzyme reaction intermediates, such that catalysis is limited by the primary retrol-aldol step of proton abstraction from the covalently bound substrate and its interactions with a histidine-aspartate dyad. These results emphasize that computational enzyme designs will benefit from considerations of dynamical fluctuations when optimizing active site geometries.

Here we investigate a family of isotropic waterlike glass-forming liquids, in which each thermodynamic state point corresponds to a different potential energy surface which is prescribed to reproduce the g(OO)(r;T,rho) of the reference TIP4P-Ew water model potential. Although each isotropic potential is simulated separately, together the family of isotropic potentials displays anomalous dynamics with density and fragile diffusivity with temperature. By removing a common energy landscape, and therefore expected thermodynamic trends with temperature within a single potential, we can more rigorously evaluate whether various entropic measures used in popular phenomenological thermodynamic theories can quantitatively predict the diffusivity or viscosity. We find that the Adam-Gibbs relation between diffusion (or viscosity) and the temperature scaled configurational entropy, S(c), is a poor predictor of fragility trends and density anomalies when necessary anharmonic corrections are added. By contrast the Dzugutov scaling relationship that uses the pair correlation approximation to S(excess) approximately S(2) provides excellent agreement for diffusion anomalies and for fragile dynamics for weakly supercooled states for the family of isotropic potentials, within a single isotropic potential, and for the TIP4P-Ew model, but deviates strongly in all three cases at more deeply supercooled temperatures. By studying the microscopic dynamics at these low temperatures, we find an increased heterogeneity in the mobility of particle populations reflected in a highly non-Gaussian distribution of particle displacements, even at very long time scales. We conclude that after the onset of dynamical heterogeneity, new consideration of higher structural correlations and/or more complex connectivity paths between basins through barriers appear to be critical for the formulation of a predictive theory for dynamics.

We performed classical molecular dynamics simulations using both fixed-charge and polarizable water and protein force fields to contrast the hydration dynamics near hydrophilic and amphiphilic peptides as a function of temperature. The high peptide concentrations we use serve as a model for the surface of folded proteins where hydration layers around each residue overlap significantly. Through simulation we determine that there are notable differences in the water dynamics analyzed from the outer and inner hydration layer regions of the amphiphilic peptide solution that explains the experimentally observed presence of two translational relaxations, while the hydrophilic peptide solution shows only a single non-Arrhenius translational process with no distinction between hydration layers. Given that water dynamics for the amphiphilic peptide system reproduces all known rotational and translational hydration dynamical anomalies exhibited by hydration water near protein surfaces, our analysis provides strong evidence that dynamical signatures near biological interfaces arises because of frustration in the hydration dynamics induced by chemical heterogeneity, as opposed to just topological roughness, of the protein surface.

We have devised a systematic approach to converge a replica exchange molecular dynamics simulation by dividing the full temperature range into a series of higher temperature reservoirs and a finite number of lower temperature subreplicas. A defined highest temperature reservoir of equilibrium conformations is used to help converge a lower but still hot temperature subreplica, which in turn serves as the high-temperature reservoir for the next set of lower temperature subreplicas. The process is continued until an optimal temperature reservoir is reached to converge the simulation at the target temperature. This gradual convergence of subreplicas allows for better and faster convergence at the temperature of interest and all intermediate temperatures for thermodynamic analysis, as well as optimizing the use of multiple processors. We illustrate the overall effectiveness of our multiple reservoir replica exchange strategy by comparing sampling and computational efficiency with respect to replica exchange, as well as comparing methods when converging the structural ensemble of the disordered Abeta(21-30) peptide simulated with explicit water by comparing calculated Rotating Overhauser Effect Spectroscopy intensities to experimentally measured values.

[Figurre: see text]. Protein aggregation can be defined as the sacrifice of stabilizing intrachain contacts of the functional state that are replaced with interchain contacts to form non-functional states. The resulting aggregate morphologies range from amorphous structures without long-range order typical of nondisease proteins involved in inclusion bodies to highly structured fibril assemblies typical of amyloid disease proteins. In this Account, we describe the development and application of computational models for the investigation of nondisease and disease protein aggregation as illustrated for the proteins L and G and the Alzheimer's Abeta systems. In each case, we validate the models against relevant experimental observables and then expand on the experimental window to better elucidate the link between molecular properties and aggregation outcomes. Our studies show that each class of protein exhibits distinct aggregation mechanisms that are dependent on protein sequence, protein concentration, and solution conditions. Nondisease proteins can have native structural elements in the denatured state ensemble or rapidly form early folding intermediates, which offers avenues of protection against aggregation even at relatively high concentrations. The possibility that early folding intermediates may be evolutionarily selected for their protective role against unwanted aggregation could be a useful strategy for reengineering sequences to slow aggregation and increase folding yield in industrial protein production. The observed oligomeric aggregates that we see for nondisease proteins L and G may represent the nuclei for larger aggregates, not just for large amorphous inclusion bodies, but potentially as the seeds of ordered fibrillar aggregates, since most nondisease proteins can form amyloid fibrils under conditions that destabilize the native state. By contrast, amyloidogenic protein sequences such as Abeta 1-40,42 and the familial Alzheimer's disease (FAD) mutants favor aggregation into ordered fibrils once the free-energy barrier for forming a critical nucleus is crossed. However, the structural characteristics and oligomer size of the soluble nucleation species have yet to be determined experimentally for any disease peptide sequence, and the molecular mechanism of polymerization that eventually delineates a mature fibril is unknown. This is in part due to the limited experimental access to very low peptide concentrations that are required to characterize these early aggregation events, providing an opportunity for theoretical studies to bridge the gap between the monomer and fibril end points and to develop testable hypotheses. Our model shows that Abeta 1-40 requires as few as 6-10 monomer chains (depending on sequence) to begin manifesting the cross-beta order that is a signature of formation of amyloid filaments or fibrils assessed in dye-binding kinetic assays. The richness of the oligomeric structures and viable filament and fibril polymorphs that we observe may offer structural clues to disease virulence variations that are seen for the WT and hereditary mutants.

We report quasi-elastic neutron scattering experiments to contrast the water dynamics as a function of temperature for hydrophilic and amphiphilic peptides under the same level of confinement, as models for understanding hydration dynamics near chemically heterogeneous protein surfaces. We find that the hydrophilic peptide shows only a single non-Arrhenius translational process with no evidence of spatial heterogeneity unlike the amphiphilic peptide solution that exhibits two translational relaxations with an Arrhenius and non-Arrhenius dependence on temperature. Together these results provide experimental proof that heterogeneous dynamical signatures near protein surfaces arise in part from chemical heterogeneity (energy disorder) as opposed to mere topological roughness of the protein surface.

We combine molecular dynamics simulations and new high-field NMR experiments to describe the solution structure of the Abeta(21-30) peptide fragment that may be relevant for understanding structural mechanisms related to Alzheimer's disease. By using two different empirical force-field combinations, we provide predictions of the three-bond scalar coupling constants ((3)J(H(N)H(alpha))), chemical-shift values, (13)C relaxation parameters, and rotating-frame nuclear Overhauser effect spectroscopy (ROESY) crosspeaks that can then be compared directly to the same observables measured in the corresponding NMR experiment of Abeta(21-30). We find robust prediction of the (13)C relaxation parameters and medium-range ROESY crosspeaks by using new generation TIP4P-Ew water and Amber ff99SB protein force fields, in which the NMR validates that the simulation yields both a structurally and dynamically correct ensemble over the entire Abeta(21-30) peptide. Analysis of the simulated ensemble shows that all medium-range ROE restraints are not satisfied simultaneously and demonstrates the structural diversity of the Abeta(21-30) conformations more completely than when determined from the experimental medium-range ROE restraints alone. We find that the structural ensemble of the Abeta(21-30) peptide involves a majority population (approximately 60%) of unstructured conformers, lacking any secondary structure or persistent hydrogen-bonding networks. However, the remaining minority population contains a substantial percentage of conformers with a beta-turn centered at Val24 and Gly25, as well as evidence of the Asp23 to Lys28 salt bridge important to the fibril structure. This study sets the stage for robust theoretical work on Abeta(1-40) and Abeta(1-42), for which collection of detailed NMR data on the monomer will be more challenging because of aggregation and fibril formation on experimental timescales at physiological conditions. In addition, we believe that the interplay of modern molecular simulation and high-quality NMR experiments has reached a fruitful stage for characterizing structural ensembles of disordered peptides and proteins in general.

The solvation of large hydrophobic solutes, modeled as repulsive and attractive Gay-Berne oblate ellipsoids, is characterized in several modified water liquids using the SPC/E model as the reference water fluid. We find that small amounts of attraction between the Gay-Berne particle and any model fluid result in wetting of the hydrophobic surface. However, significant differences are found among the modified and SPC/E water models and the critical distances in which they dewet the hydrophobic surfaces of pairs of repulsive Gay-Berne particles. We find that the dewetting trends for repulsive Gay-Berne particles in the various model liquids correlate directly with their surface tensions, the widths of the interfaces they form, and the openness of their network structure. The largest critical separations are found in liquids with the smallest surface tensions and the broadest interfaces as measured by the Egelstaff-Widom length.

We demonstrate the performance of a new implicit solvent model on native protein loop prediction from a large set of loop decoys of 4- to 12-residue in length. The physics-based energy function combines a hydrophobic potential of mean force (HPMF) description with a Generalized Born model for polarization of protein charge by the high dielectric solvent, which we combine with AMBER force field for the protein chain. The novelty of our energy function is the stabilizing effect of hydrophobic exposure to aqueous solvent that defines the HPMF hydration physics, which in principle should be an important stabilizing factor for loop conformations of a protein that typically are more solvent exposed. While our results for short loop decoy sets are comparably good to existing energy functions, we find demonstrable superiority for loop lengths of 8-residue and greater, and the quality of our predictions is largely insensitive to the length of the target loop on a filtered set of decoys. Given that the current weakness in loop modeling is the ability to select the most nativelike loop conformers from loop ensembles, this energy function provides a means for greater prediction accuracy in structure prediction of homologous and distantly related proteins, thereby aiding large-scale genomics efforts in comparative modeling.

Using a coarse-grained model of the Abeta peptide, we analyze the Arctic (E22G), Dutch (E22Q), and Flemish (A21G) familial Alzheimer's disease (FAD) mutants for any changes in the stability of amyloid assemblies with respect to the wild-type (WT) sequence. Based on a structural reference state of two protofilaments aligned to create the "agitated" protofibril as determined by solid-state NMR, we determine free energy trends for Abeta assemblies for the WT and FAD familial sequences. We find that the structural characteristics and oligomer size of the critical nucleus vary dramatically among the hereditary mutants. The Arctic mutant's disorder in the turn region introduces new stabilizing interactions that better align the two protofilaments, yielding a well-defined protofibril axis at relatively small oligomer sizes with respect to WT. By contrast, the critical nucleus for the Flemish mutant is beyond the 20 chains characterized in this study, thereby showing a strong shift in the equilibrium toward monomers with respect to larger protofibril assemblies. The Dutch mutant forms more ordered protofilaments than WT, but exhibits greater disorder in protofibril structure that includes an alternative polymorph of the WT fibril. An important conclusion of this work is that the Dutch mutant does not support the agitated protofibril assembly. We discuss the implications of the structural ensembles and free energy profiles for the FAD mutants in regards to interpretation of the kinetics of fibril assembly using chromatography and dye-binding experiments.

We develop a sequence based alpha-carbon model to incorporate a mean field estimate of the orientation dependence of the polypeptide chain that gives rise to specific hydrogen bond pairing to stabilize alpha-helices and beta-sheets. We illustrate the success of the new protein model in capturing thermodynamic measures and folding mechanism of proteins L and G. Compared to our previous coarse-grained model, the new model shows greater folding cooperativity and improvements in designability of protein sequences, as well as predicting correct trends for kinetic rates and mechanism for proteins L and G. We believe the model is broadly applicable to other protein folding and protein-protein co-assembly processes, and does not require experimental input beyond the topology description of the native state. Even without tertiary topology information, it can also serve as a mid-resolution protein model for more exhaustive conformational search strategies that can bridge back down to atomic descriptions of the polypeptide chain.

We develop a sequence based alpha-carbon model to incorporate a mean field estimate of the orientation dependence of the polypeptide chain that gives rise to specific hydrogen bond pairing to stabilize alpha-helices and beta-sheets. We illustrate the success of the new protein model in capturing thermodynamic measures and folding mechanism of proteins L and G. Compared to our previous coarse-grained model, the new model shows greater folding cooperativity and improvements in designability of protein sequences, as well as predicting correct trends for kinetic rates and mechanism for proteins L and G. We believe the model is broadly applicable to other protein folding and protein-protein co-assembly processes, and does not require experimental input beyond the topology description of the native state. Even without tertiary topology information, it can also serve as a mid-resolution protein model for more exhaustive conformational search strategies that can bridge back down to atomic descriptions of the polypeptide chain.