Optimizing Protein-Solvent Force Fields to Reproduce Intrinsic Conformational Preferences of Model Peptides

Intrinsic α-helical and β-sheet conformational preferences: a computational case study of alanine

A fundamental question in protein science is what is the intrinsic propensity for an amino acid to be in an α-helix, β-sheet, or other backbone dihedral angle ( ϕ-ψ) conformation. This question has been hotly debated for many years because including all protein crystal structures from the protein database, increases the probabilities for α-helical structures, while experiments on small peptides observe that β-sheet-like conformations predominate. We perform molecular dynamics (MD) simulations of a hard-sphere model for Ala dipeptide mimetics that includes steric interactions between nonbonded atoms and bond length and angle constraints with the goal of evaluating the role of steric interactions in determining protein backbone conformational preferences. We find four key results. For the hard-sphere MD simulations, we show that (1) β-sheet structures are roughly three and half times more probable than α-helical structures, (2) transitions between α-helix and β-sheet structures only occur when the backbone bond angle τ (NCα C) is greater than 110°, and (3) the probability distribution of τ for Ala conformations in the "bridge" region of ϕ-ψ space is shifted to larger angles compared to other regions. In contrast, (4) the distributions obtained from Amber and CHARMM MD simulations in the bridge regions are broader and have increased τ compared to those for hard sphere simulations and from high-resolution protein crystal structures. Our results emphasize the importance of hard-sphere interactions and local stereochemical constraints that yield strong correlations between ϕ-ψ conformations and τ.

Temperature-dependent solvation modulates the dimensions of disordered proteins

For disordered proteins, the dimensions of the chain are an important property that is sensitive to environmental conditions. We have used single-molecule Förster resonance energy transfer to probe the temperature-induced chain collapse of five unfolded or intrinsically disordered proteins. Because this behavior is sensitive to the details of intrachain and chain-solvent interactions, the collapse allows us to probe the physical interactions governing the dimensions of disordered proteins. We find that each of the proteins undergoes a collapse with increasing temperature, with the most hydrophobic one, λ-repressor, undergoing a reexpansion at the highest temperatures. Although such a collapse might be expected due to the temperature dependence of the classical "hydrophobic effect," remarkably we find that the largest collapse occurs for the most hydrophilic, charged sequences. Using a combination of theory and simulation, we show that this result can be rationalized in terms of the temperature-dependent solvation free energies of the constituent amino acids, with the solvation properties of the most hydrophilic residues playing a large part in determining the collapse.

Sensitivity of local hydration behaviour and conformational preferences of peptides to choice of water model

Secondary structural preferences of the beta-hairpin of the 2GB1 protein in the folded and unfolded ensembles are shown to be sensitive to the choice of water model.

Advanced potential energy surfaces for condensed phase simulation

Computational modeling at the atomistic and mesoscopic levels has undergone dramatic development in the past 10 years to meet the challenge of adequately accounting for the many-body nature of intermolecular interactions. At the heart of this challenge is the ability to identify the strengths and specific limitations of pairwise-additive interactions, to improve classical models to explicitly account for many-body effects, and consequently to enhance their ability to describe a wider range of reference data and build confidence in their predictive capacity. However, the corresponding computational cost of these advanced classical models increases significantly enough that statistical convergence of condensed phase observables becomes more difficult to achieve. Here we review a hierarchy of potential energy surface models used in molecular simulations for systems with many degrees of freedom that best meet the trade-off between accuracy and computational speed in order to define a sweet spot for a given scientific problem of interest.

Predicting the Thermodynamics and Kinetics of Helix Formation in a Cyclic Peptide Model

The peptide Ac-(cyclo-2,6)-R[KAAAD]-NH2 (cyc-RKAAAD) is a short cyclic peptide known to adopt a remarkably stable single turn α-helix in water. Due to its simplicity and the availability of thermodynamic and kinetic experimental data, cyc-RKAAAD poses as an ideal model for evaluating the aptness of current molecular dynamics (MD) simulation methodologies to accurately sample conformations that reproduce experimentally observed properties. In this work, we extensively sample the conformational space of cyc-RKAAAD using microsecond-timescale MD simulations. We characterize the peptide conformational preferences in terms of secondary structure propensities and, using Cartesian-coordinate principal component analysis (cPCA), construct its free energy landscape, thus obtaining a detailed weighted discrimination between the helical and nonhelical subensembles. The cPCA state discrimination, together with a Markov model built from it, allowed us to estimate the free energy of unfolding (-0.57 kJ/mol) and the relaxation time (∼0.435 μs) at 298.15 K, which are in excellent agreement with the experimentally reported values (-0.22 kJ/mol and 0.42 μs, Serrano, A. L.; Tucker, M. J.; Gai, F. J. Phys. Chem. B, 2011, 115, 7472-7478.). Additionally, we present simulations conducted using two enhanced sampling methods: replica-exchange molecular dynamics (REMD) and bias-exchange metadynamics (BE-MetaD). We compare the free energy landscape obtained by these two methods with the results from MD simulations and discuss the sampling and computational gains achieved. Overall, the results obtained attest to the suitability of modern simulation methods to explore the conformational behavior of peptide systems with a high level of realism.

Ligand clouds around protein clouds: a scenario of ligand binding with intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) were found to be widely associated with human diseases and may serve as potential drug design targets. However, drug design targeting IDPs is still in the very early stages. Progress in drug design is usually achieved using experimental screening; however, the structural disorder of IDPs makes it difficult to characterize their interaction with ligands using experiments alone. To better understand the structure of IDPs and their interactions with small molecule ligands, we performed extensive simulations on the c-Myc₃₇₀₋₄₀₉ peptide and its binding to a reported small molecule inhibitor, ligand 10074-A4. We found that the conformational space of the apo c-Myc₃₇₀₋₄₀₉ peptide was rather dispersed and that the conformations of the peptide were stabilized mainly by charge interactions and hydrogen bonds. Under the binding of the ligand, c-Myc₃₇₀₋₄₀₉ remained disordered. The ligand was found to bind to c-Myc₃₇₀₋₄₀₉ at different sites along the chain and behaved like a 'ligand cloud'. In contrast to ligand binding to more rigid target proteins that usually results in a dominant bound structure, ligand binding to IDPs may better be described as ligand clouds around protein clouds. Nevertheless, the binding of the ligand and a non-ligand to the c-Myc₃₇₀₋₄₀₉ target could be clearly distinguished. The present study provides insights that will help improve rational drug design that targets IDPs.

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

Water and water-like liquids: relationships between structure, entropy and mobility

Liquids with very diverse underlying interactions share the thermodynamic and transport anomalies of water, including metalloids, ionic melts and mesoscopic fluids. The generic feature that characterises such water-like liquids is a density-driven shift in the nature of local order in the condensed phases. The key semiquantitative relationships between structural order, thermodynamics and transport that are necessary in order to map out the consequences of this common qualitative feature for liquid-state properties and phase transformations of such systems are reviewed here. The application of these ideas to understand and model tetrahedral liquids, especially water, is discussed and possible extensions to other complex fluids are considered.

CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data

Protein structure and dynamics can be characterized on the atomistic level with both nuclear magnetic resonance (NMR) experiments and molecular dynamics (MD) simulations. Here, we quantify the ability of the recently presented CHARMM36 (C36) force field (FF) to reproduce various NMR observables using MD simulations. The studied NMR properties include backbone scalar couplings across hydrogen bonds, residual dipolar couplings (RDCs) and relaxation order parameter, as well as scalar couplings, RDCs, and order parameters for side-chain amino- and methyl-containing groups. It is shown that the C36 FF leads to better correlation with experimental data compared to the CHARMM22/CMAP FF and suggest using C36 in protein simulations. Although both CHARMM FFs contains the same nonbond parameters, our results show how the changes in the internal parameters associated with the peptide backbone via CMAP and the χ1 and χ2 dihedral parameters leads to improved treatment of the analyzed nonbond interactions. This highlights the importance of proper treatment of the internal covalent components in modeling nonbond interactions with molecular mechanics FFs.

A coupled two-dimensional main chain torsional potential for protein dynamics: generation and implementation

Main chain torsions of alanine dipeptide are parameterized into coupled 2-dimensional Fourier expansions based on quantum mechanical (QM) calculations at M06 2X/aug-cc-pvtz//HF/6-31G** level. Solvation effect is considered by employing polarizable continuum model. Utilization of the M06 2X functional leads to precise potential energy surface that is comparable to or even better than MP2 level, but with much less computational demand. Parameterization of the 2D expansions is against the full main chain torsion space instead of just a few low energy conformations. This procedure is similar to that for the development of AMBER03 force field, except unique weighting factor was assigned to all the grid points. To avoid inconsistency between quantum mechanical calculations and molecular modeling, the model peptide is further optimized at molecular mechanics level with main chain dihedral angles fixed before the calculation of the conformational energy on molecular mechanical level at each grid point, during which generalized Born model is employed. Difference in solvation models at quantum mechanics and molecular mechanics levels makes this parameterization procedure less straightforward. All force field parameters other than main chain torsions are taken from existing AMBER force field. With this new main chain torsion terms, we have studied the main chain dihedral distributions of ALA dipeptide and pentapeptide in aqueous solution. The results demonstrate that 2D main chain torsion is effective in delineating the energy variation associated with rotations along main chain dihedrals. This work is an implication for the necessity of more accurate description of main chain torsions in the future development of ab initio force field and it also raises a challenge to the development of quantum mechanical methods, especially the quantum mechanical solvation models.

Transient access to the protein interior: simulation versus NMR

Many proteins rely on rare structural fluctuations for their function, whereby solvent and other small molecules gain transient access to internal cavities. In magnetic relaxation dispersion (MRD) experiments, water molecules buried in such cavities are used as intrinsic probes of the intermittent protein motions that govern their exchange with external solvent. While this has allowed a detailed characterization of exchange kinetics for several proteins, little is known about the exchange mechanism. Here, we use a millisecond all-atom MD trajectory produced by Shaw et al. (Science2010, 330, 341) to characterize water exchange from the four internal hydration sites in the protein bovine pancreatic trypsin inhibitor. Using a recently developed stochastic point process approach, we compute the survival correlation function probed by MRD experiments as well as other quantities designed to validate the exchange-mediated orientational randomization (EMOR) model used to interpret the MRD data. The EMOR model is found to be quantitatively accurate, and the simulation reproduces the experimental mean survival times for all four sites with activation energy discrepancies in the range 0-3 kBT. On the other hand, the simulated hydration sites are somewhat too flexible, and the water flip barrier is underestimated by up to 6 kBT. The simulation reveals that water molecules gain access to the internal sites by a transient aqueduct mechanism, migrating as single-file water chains through transient (<5 ns) tunnels or pores. The present study illustrates the power of state-of-the-art molecular dynamics simulations in validating and extending experimental results.

α-helix to β-hairpin transition of human amylin monomer

The human islet amylin polypeptide is produced along with insulin by pancreatic islets. Under some circumstances, amylin can aggregate to form amyloid fibrils, whose presence in pancreatic cells is a common pathological feature of Type II diabetes. A growing body of evidence indicates that small, early stage aggregates of amylin are cytotoxic. A better understanding of the early stages of the amylin aggregation process and, in particular, of the nucleation events leading to fibril growth could help identify therapeutic strategies. Recent studies have shown that, in dilute solution, human amylin can adopt an α-helical conformation, a β-hairpin conformation, or an unstructured coil conformation. While such states have comparable free energies, the β-hairpin state exhibits a large propensity towards aggregation. In this work, we present a detailed computational analysis of the folding pathways that arise between the various conformational states of human amylin in water. A free energy surface for amylin in explicit water is first constructed by resorting to advanced sampling techniques. Extensive transition path sampling simulations are then employed to identify the preferred folding mechanisms between distinct minima on that surface. Our results reveal that the α-helical conformer of amylin undergoes a transformation into the β-hairpin monomer through one of two mechanisms. In the first, misfolding begins through formation of specific contacts near the turn region, and proceeds via a zipping mechanism. In the second, misfolding occurs through an unstructured coil intermediate. The transition states for these processes are identified. Taken together, the findings presented in this work suggest that the inter-conversion of amylin between an α-helix and a β-hairpin is an activated process and could constitute the nucleation event for fibril growth.

pH-Independence of trialanine and the effects of termini blocking in short peptides: a combined vibrational, NMR, UVCD, and molecular dynamics study

Several lines of evidence now well establish that unfolded peptides in general, and alanine in specific, have an intrinsic preference for the polyproline II (pPII) conformation. Investigation of local order in the unfolded state is, however, complicated by experimental limitations and the inherent dynamics of the system, which has in some cases yielded inconsistent results from different types of experiments. One method of studying these systems is the use of short model peptides, and specifically short alanine peptides, known for predominantly sampling pPII structure in aqueous solution. Recently, He et al. ( J. Am. Chem. Soc. 2012 , 134 , 1571 - 1576 ) proposed that unblocked tripeptides may not be suitable models for studying conformational propensities in unfolded peptides due to the presence of end effect, that is, electrostatic interactions between investigated amino acid residues and terminal charges. To determine whether changing the protonation states of the N- and C-termini influence the conformational manifold of the central amino acid residue in tripeptides, we have examined the pH-dependence of unblocked trialanine and the conformational preferences of alanine in the alanine dipeptide. To this end, we measured and globally analyzed amide I' band profiles and NMR J-coupling constants. We described conformational distributions as the superposition of two-dimensional Gaussian distributions assignable to specific subspaces of the Ramachandran plot. Results show that the conformational ensemble of trialanine as a whole, and the pPII content (χpPII = 0.84) in particular, remains practically unaffected by changing the protonation state. We found that compared to trialanine, the alanine dipeptide has slightly lower pPII content (χpPII = 0.74) and an ensemble more reminiscent of the unblocked Gly-Ala-Gly model peptide. In addition, a two-state thermodynamic analysis of the conformational sensitive Δε(T) and (3)J(H(N)H(α))(T) data obtained from electronic circular dichroism and H NMR spectra indicate that the free energy landscape of trialanine is similar in all protonation states. MD simulations for the investigated peptides corroborate this notion and show further that the hydration shell around unblocked trialanine is unaffected by the protonation/deprotonation of the C-terminal group. In contrast, the alanine dipeptide shows a reduced water density around the central residue as well as a less ordered hydration shell, which decreases the pPII propensity and reduces the lifetime of sampled conformations.

Inclusion of many-body effects in the additive CHARMM protein CMAP potential results in enhanced cooperativity of α-helix and β-hairpin formation

Folding simulations on peptides and proteins using empirical force fields have demonstrated the sensitivity of the results to details of the backbone potential. A recently revised version of the additive CHARMM protein force field, which includes optimization of the backbone CMAP potential to achieve good balance between different types of secondary structure, correcting the α-helical bias present in the former CHARMM22/CMAP energy function, is shown to result in improved cooperativity for the helix-coil transition. This is due to retention of the empirical corrections introduced in the original CMAP to reproduce folded protein structures-corrections that capture many-body effects missing from an energy surface fitted to gas phase calculations on dipeptides. The experimental temperature dependence of helix formation in (AAQAA)(3) and parameters for helix nucleation and elongation are in much better agreement with experiment than those obtained with other recent force fields. In contrast, CMAP parameters derived by fitting to a vacuum quantum mechanical surface for the alanine dipeptide do not reproduce the enhanced cooperativity, showing that the empirical backbone corrections, and not some other feature of the force field, are responsible. We also find that the cooperativity of β-hairpin formation is much improved relative to other force fields we have studied. Comparison with (ϕ,ψ) distributions from the Protein Data Bank further justifies the inclusion of many-body effects in the CMAP. These results suggest that the revised energy function will be suitable for both simulations of unfolded or intrinsically disordered proteins and for investigating protein-folding mechanisms.

Critical Assessment of Current Force Fields. Short Peptide Test Case

The applicability of molecular dynamics simulations for studies of protein folding or intrinsically disordered proteins critically depends on quality of energetic functions-force fields. The four popular force fields for biomolecular simulations, CHARMM22/CMAP, AMBER FF03, AMBER FF99SB, and OPLS-AA/L, were compared in prediction of conformational propensities of all common proteinogenic amino acids. The minimalistic model of terminally block amino acids (dipeptides) was chosen for assessment of side chain effects on backbone propensities. The precise metadynamics simulations revealed striking inconsistency of trends in conformational preferences as manifested by investigated force fields for both backbone and side chains. To trace this disapproval between force fields, the two related AMBER force fields were studied more closely. In the cases of FF99SB and FF03, we uncovered that the distinct tends were driven by different charge models. Additionally, the effects of recent correction for side chain torsion (FF99SB-ILDN) were examined on affected amino acids and exposed significant coupling between free energy profiles and propensities of backbone and side chain conformers. These findings have important consequences for further force field development.

To milliseconds and beyond: challenges in the simulation of protein folding

Quantitatively accurate all-atom molecular dynamics (MD) simulations of protein folding have long been considered a holy grail of computational biology. Due to the large system sizes and long timescales involved, such a pursuit was for many years computationally intractable. Further, sufficiently accurate forcefields needed to be developed in order to realistically model folding. This decade, however, saw the first reports of folding simulations describing kinetics on the order of milliseconds, placing many proteins firmly within reach of these methods. Progress in sampling and forcefield accuracy, however, presents a new challenge: how to turn huge MD datasets into scientific understanding. Here, we review recent progress in MD simulation techniques and show how the vast datasets generated by such techniques present new challenges for analysis. We critically discuss the state of the art, including reaction coordinate and Markov state model (MSM) methods, and provide a perspective for the future.

Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data

We introduce ForceBalance, a method and free software package for systematic force field optimization with the ability to parametrize a wide variety of functional forms using flexible combinations of reference data. We outline several important challenges in force field development and how they are addressed in ForceBalance, and present an example calculation where these methods are applied to develop a highly accurate polarizable water model. ForceBalance is available for free download at https://simtk.org/home/forcebalance.

Water and other tetrahedral liquids: order, anomalies and solvation

In order to understand the common features of tetrahedral liquids with water-like anomalies, the relationship between local order and anomalies has been studied using molecular dynamics simulations for three categories of such liquids: (a) atomistic rigid-body models for water (TIP4P, TIP4P/2005, mTIP3P, SPC/E), (b) ionic melts, BeF(2) (TRIM model) and SiO(2) (BKS potential) and (c) Stillinger-Weber liquids parametrized to model water (mW) and silicon. Rigid-body, atomistic models for water and the Stillinger-Weber liquids show a strong correlation between tetrahedral and pair correlation order and the temperature for the onset of the density anomaly is close to the melting temperature. In contrast, the ionic melts show weaker and more variable degrees of correlation between tetrahedral and pair correlation metrics, and the onset temperature for the density anomaly is more than twice the melting temperature. In the case of water, the relationship between water-like anomalies and solvation is studied by examining the hydration of spherical solutes (Na(+), Cl(-), Ar) in water models with different temperature regimes of anomalies (SPC/E, TIP4P and mTIP3P). For both ionic and nonpolar solutes, the local structure and energy of water molecules is essentially the same as in bulk water beyond the second-neighbour shell. The local order and binding energy of water molecules are not perturbed by the presence of a hydrophobic solute. In the case of ionic solutes, the perturbation is largely localized within the first hydration shell. The binding energies for the ions are strongly dependent on the water models and clearly indicate that the geometry of the partial charge distributions, and the associated multipole moments, play an important role. However the anomalous behaviour of the water network has been found to be unimportant for polar solvation.

Dimer formation enhances structural differences between amyloid β-protein (1-40) and (1-42): an explicit-solvent molecular dynamics study

Amyloid β-protein (Aβ) is central to the pathology of Alzheimer's disease. A 5% difference in the primary structure of the two predominant alloforms, Aβ(1-40) and Aβ(1-42), results in distinct assembly pathways and toxicity properties. Discrete molecular dynamics (DMD) studies of Aβ(1-40) and Aβ(1-42) assembly resulted in alloform-specific oligomer size distributions consistent with experimental findings. Here, a large ensemble of DMD-derived Aβ(1-40) and Aβ(1-42) monomers and dimers was subjected to fully atomistic molecular dynamics (MD) simulations using the OPLS-AA force field combined with two water models, SPCE and TIP3P. The resulting all-atom conformations were slightly larger, less compact, had similar turn and lower β-strand propensities than those predicted by DMD. Fully atomistic Aβ(1-40) and Aβ(1-42) monomers populated qualitatively similar free energy landscapes. In contrast, the free energy landscape of Aβ(1-42) dimers indicated a larger conformational variability in comparison to that of Aβ(1-40) dimers. Aβ(1-42) dimers were characterized by an increased flexibility in the N-terminal region D1-R5 and a larger solvent exposure of charged amino acids relative to Aβ(1-40) dimers. Of the three positively charged amino acids, R5 was the most and K16 the least involved in salt bridge formation. This result was independent of the water model, alloform, and assembly state. Overall, salt bridge propensities increased upon dimer formation. An exception was the salt bridge propensity of K28, which decreased upon formation of Aβ(1-42) dimers and was significantly lower than in Aβ(1-40) dimers. The potential relevance of the three positively charged amino acids in mediating the Aβ oligomer toxicity is discussed in the light of available experimental data.

Are Protein Force Fields Getting Better? A Systematic Benchmark on 524 Diverse NMR Measurements

Recent hardware and software advances have enabled simulation studies of protein systems on biophysically-relevant timescales, often revealing the need for improved force fields. Although early force field development was limited by the lack of direct comparisons between simulation and experiment, recent work from several labs has demonstrated direct calculation of NMR observables from protein simulations. Here we quantitatively evaluate recent molecular dynamics force fields against a suite of 524 chemical shift and J coupling ((3)JH(N)H(α), (3)JH(N)C(β), (3)JH(α)C', (3)JH(N)C', and (3)JH(α)N) measurements on dipeptides, tripeptides, tetra-alanine, and ubiquitin. Of the force fields examined (ff96, ff99, ff03, ff03*, ff03w, ff99sb*, ff99sb-ildn, ff99sb-ildn-phi, ff99sb-ildn-nmr, CHARMM27, OPLS-AA), two force fields (ff99sb-ildn-phi, ff99sb-ildn-nmr) combining recent side chain and backbone torsion modifications achieve high accuracy in our benchmark. For the two optimal force fields, the calculation error is comparable to the uncertainty in the experimental comparison. This observation suggests that extracting additional force field improvements from NMR data may require increased accuracy in J coupling and chemical shift prediction. To further investigate the limitations of current force fields, we also consider conformational populations of dipeptides, which were recently estimated using vibrational spectroscopy.

Derivation and systematic validation of a refined all-atom force field for phosphatidylcholine lipids

An all-atomistic force field (FF) has been developed for fully saturated phospholipids. The parametrization has been largely based on high-level ab initio calculations in order to keep the empirical input to a minimum. Parameters for the lipid chains have been developed based on knowledge about bulk alkane liquids, for which thermodynamic and dynamic data are excellently reproduced. The FFs ability to simulate lipid bilayers in the liquid crystalline phase in a tensionless ensemble was tested in simulations of three lipids: 1,2-diauroyl-sn-glycero-3-phospocholine (DLPC), 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), and 1,2-dipalmitoyl-sn-glycero-3-phospcholine (DPPC). Computed areas and volumes per lipid, and three different kinds of bilayer thicknesses, have been investigated. Most importantly NMR order parameters and scattering form factors agree in an excellent manner with experimental data under a range of temperatures. Further, the compatibility with the AMBER FF for biomolecules as well as the ability to simulate bilayers in gel phase was demonstrated. Overall, the FF presented here provides the important balance between the hydrophilic and hydrophobic forces present in lipid bilayers and therefore can be used for more complicated studies of realistic biological membranes with protein insertions.

Atomistic molecular simulations of protein folding

Theory and experiment have provided answers to many of the fundamental questions of protein folding; a remaining challenge is an accurate, high-resolution picture of folding mechanism. Atomistic molecular simulations with explicit solvent are the most promising method for providing this information, by accounting more directly for the physical interactions that stabilize proteins. Although simulations of folding with such force fields are extremely challenging, they have become feasible as a result of recent advances in computational power, accuracy of the energy functions or 'force fields', and methods for improving sampling of folding events. I review the recent progress in these areas, and highlight future challenges and questions that we may hope to address with these methods. I also attempt to place atomistic models into the context of the energy landscape view of protein folding, and coarse-grained simulations.

A study of the α-helical intermediate preceding the aggregation of the amino-terminal fragment of the β amyloid peptide (Aβ(1-28))

The β amyloid (Aβ) peptide aggregates to form β-rich structures that are known to trigger Alzheimer's disease. Experiments suggest that an α-helical intermediate precedes the formation of these aggregates. However, a description at the molecular level of the α-to-β transition has not been obtained. Because it has been proposed that the transition might be initiated in the amino-terminal region of Aβ, we studied the aggregation of the 28-residue amino-terminal fragment of Aβ (Aβ(1-28)) using molecular dynamics and a coarse-grained force field. Simulations starting from extended and helical conformations showed that oligomerization is initiated by the formation of intermolecular β-sheets between the residues in the N-terminal regions. In simulations starting from the α-helical conformation, forcing residues 17-21 to remain in the initial (helical) conformation prevents aggregation but allows for the formation of dimers, indicating that oligomerization, initiated along the nonhelical N-terminal regions, cannot progress without the α-to-β transition propagating along the chains.

Influence of water-protein hydrogen bonding on the stability of Trp-cage miniprotein. A comparison between the TIP3P and TIP4P-Ew water models

We report extensive replica exchange molecular dynamics (REMD) simulations on the folding/unfolding equilibrium of Trp-cage miniprotein using the Amber ff99SB all atom forcefield and TIP3P and TIP4P-Ew explicit water solvent models. REMD simulation-lengths in the 500 ns to the microsecond regime per replica are required to adequately sample the folding/unfolding equilibrium. We observe that this equilibrium is significantly affected by the choice of the water model. Compared with experimental data, simulations using the TIP3P solvent describe the stability of the Trp-cage quite realistically, providing a melting point which is just a few Kelvins above the experimental transition temperature of 317 K. The TIP4P-Ew model shifts the equilibrium towards the unfolded state and lowers the free energy of unfolding by about 3 kJ mol(-1) at 280 K, demonstrating the need to fine-tune the protein-forcefield depending on the chosen water model. We report evidence that the main difference between the two water models is mostly due to the different solvation of polar groups of the peptide. The unfolded state of the Trp-cage is stabilized by an increasing number of hydrogen bonds, destabilizing the α-helical part of the molecule and opening the R-D salt bridge. By reweighting the strength of solvent-peptide hydrogen bonds by adding a hydrogen bond square well potential, we can fully recover the effect of the different water models and estimate the shift in population as due to a difference in hydrogen bond-strength of about 0.4 kJ mol(-1) per hydrogen bond.

Homogeneous and heterogeneous tertiary structure ensembles of amyloid-β peptides

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.