De novo folding of membrane proteins: an exploration of the structure and NMR properties of the fd coat protein

CHARMM-GUI Implicit Solvent Modeler for Various Generalized Born Models in Different Simulation Programs

Implicit solvent models are widely used because they are advantageous to speed up simulations by drastically decreasing the number of solvent degrees of freedom, which allows one to achieve long simulation time scales for large system sizes. CHARMM-GUI, a web-based platform, has been developed to support the setup of complex multicomponent molecular systems and prepare input files. This study describes an Implicit Solvent Modeler (ISM) in CHARMM-GUI for various generalized Born (GB) implicit solvent simulations in different molecular dynamics programs such as AMBER, CHARMM, GENESIS, NAMD, OpenMM, and Tinker. The GB models available in ISM include GB-HCT, GB-OBC, GB-neck, GBMV, and GBSW with the CHARMM and Amber force fields for protein, DNA, RNA, glycan, and ligand systems. Using the system and input files generated by ISM, implicit solvent simulations of protein, DNA, and RNA systems produce similar results for different simulation packages with the same input information. Protein-ligand systems are also considered to further validate the systems and input files generated by ISM. Simple ligand root-mean-square deviation (RMSD) and molecular mechanics generalized Born surface area (MM/GBSA) calculations show that the performance of implicit simulations is better than docking and can be used for early stage ligand screening. These reasonable results indicate that ISM is a useful and reliable tool to provide various implicit solvent simulation applications.

Applications of Molecular Dynamics Simulation in Protein Study

Molecular Dynamics (MD) Simulations is increasingly used as a powerful tool to study protein structure-related questions. Starting from the early simulation study on the photoisomerization in rhodopsin in 1976, MD Simulations has been used to study protein function, protein stability, protein-protein interaction, enzymatic reactions and drug-protein interactions, and membrane proteins. In this review, we provide a brief review for the history of MD Simulations application and the current status of MD Simulations applications in protein studies.

REDCRAFT: A computational platform using residual dipolar coupling NMR data for determining structures of perdeuterated proteins in solution

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the three primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by solution NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination from Residual Dipolar Couplings (RDCs) is relatively less well developed. Here, we describe the new features of the protein structure modeling program REDCRAFT and focus on the new Adaptive Decimation (AD) feature. The AD plays a critical role in improving the robustness of REDCRAFT to missing or noisy data, while allowing structure determination of larger proteins from less data. In this report we demonstrate the successful application of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data, and of larger proteins (145 to 573 residues) using simulated RDC data. In both cases, REDCRAFT uses only RDC data that can be collected from perdeuterated proteins. Finally, we compare the accuracy of structure determination from RDCs alone with traditional NOE-based methods for the structurally novel PF.2048.1 protein. The RDC-based structure of PF.2048.1 exhibited 1.0 Å BB-RMSD with respect to a high-quality NOE-based structure. Although optimal strategies would include using RDC data together with chemical shift, NOE, and other NMR data, these studies provide proof-of-principle for robust structure determination of largely-perdeuterated proteins from RDC data alone using REDCRAFT.

Residual Dipolar Couplings have the potential to improve the accuracy and reduce the time needed to characterize protein structures. In addition, RDC data have been demonstrated to concurrently elucidate structure of proteins, provide assignment of resonances, and characterize the internal dynamics of proteins. Given all the advantages associated with the study of proteins from RDC data, based on the statistics provided by the Protein Databank (PDB), surprisingly only 124 proteins (out of nearly 150,000 proteins) have utilized RDCs as part of their structure determination. Even a smaller subset of these proteins (approximately 7) have utilized RDCs as the primary source of data for structure determination. One key factor in the use of RDCs is the challenging computational and analytical aspects of this source of data. In this report, we demonstrate the success of the REDCRAFT software package in structure determination of proteins using RDC data that can be collected from small and large proteins in a routine fashion. REDCRAFT accomplishes the challenging task of structure determination from RDCs by introducing a unique search and optimization technique that is both robust and computationally tractable. Structure determination from routinely collectable RDC data using REDCRAFT can complement existing methods to provide faster and more accurate studies of larger and more complex protein structures by NMR spectroscopy in solution state.

Whole-Cell Models and Simulations in Molecular Detail

Comprehensive data about the composition and structure of cellular components have enabled the construction of quantitative whole-cell models. While kinetic network-type models have been established, it is also becoming possible to build physical, molecular-level models of cellular environments. This review outlines challenges in constructing and simulating such models and discusses near- and long-term opportunities for developing physical whole-cell models that can connect molecular structure with biological function.

Applications of NMR to membrane proteins

Membrane proteins present a challenge for structural biology. In this article, we review some of the recent developments that advance the application of NMR to membrane proteins, with emphasis on structural studies in detergent-free, lipid bilayer samples that resemble the native environment. NMR spectroscopy is not only ideally suited for structure determination of membrane proteins in hydrated lipid bilayer membranes, but also highly complementary to the other principal techniques based on X-ray and electron diffraction. Recent advances in NMR instrumentation, spectroscopic methods, computational methods, and sample preparations are driving exciting new efforts in membrane protein structural biology.

Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions

A scoring protocol based on implicit membrane-based scoring functions and a new protocol for optimizing the positioning of proteins inside the membrane was evaluated for its capacity to discriminate native-like states from misfolded decoys. A decoy set previously established by the Baker lab (Proteins: Struct., Funct., Genet. 2006, 62, 1010-1025) was used along with a second set that was generated to cover higher resolution models. The Implicit Membrane Model 1 (IMM1), IMM1 model with CHARMM 36 parameters (IMM1-p36), generalized Born with simple switching (GBSW), and heterogeneous dielectric generalized Born versions 2 (HDGBv2) and 3 (HDGBv3) were tested along with the new HDGB van der Waals (HDGBvdW) model that adds implicit van der Waals contributions to the solvation free energy. For comparison, scores were also calculated with the distance-scaled finite ideal-gas reference (DFIRE) scoring function. Z-scores for native state discrimination, energy vs root-mean-square deviation (RMSD) correlations, and the ability to select the most native-like structures as top-scoring decoys were evaluated to assess the performance of the scoring functions. Ranking of the decoys in the Baker set that were relatively far from the native state was challenging and dominated largely by packing interactions that were captured best by DFIRE with less benefit of the implicit membrane-based models. Accounting for the membrane environment was much more important in the second decoy set where especially the HDGB-based scoring functions performed very well in ranking decoys and providing significant correlations between scores and RMSD, which shows promise for improving membrane protein structure prediction and refinement applications. The new membrane structure scoring protocol was implemented in the MEMScore web server ( http://feiglab.org/memscore ).

Membrane insertion of fusion peptides from Ebola and Marburg viruses studied by replica-exchange molecular dynamics simulations

This work presents replica-exchange molecular dynamics simulations of inserting a 16-residue Ebola virus fusion peptide into a membrane bilayer. A computational approach is applied for modeling the peptide at the explicit all-atom level and the membrane-aqueous bilayer by a generalized Born continuum model with a smoothed switching function (GBSW). We provide an assessment of the model calculations in terms of three metrics: (1) the ability to reproduce the NMR structure of the peptide determined in the presence of SDS micelles and comparable structural data on other fusion peptides; (2) determination of the effects of the mutation Trp-8 to Ala and sequence discrimination of the homologous Marburg virus; and (3) calculation of potentials of mean force for estimating the partitioning free energy and their comparison to predictions from the Wimley-White interfacial hydrophobicity scale. We found the GBSW implicit membrane model to produce results of limited accuracy in conformational properties of the peptide when compared to the NMR structure, yet the model resolution is sufficient to determine the effect of sequence differentiation on peptide-membrane integration. © 2016 Wiley Periodicals, Inc.

High quality NMR structures: a new force field with implicit water and membrane solvation for Xplor-NIH

Structure determination of proteins by NMR is unique in its ability to measure restraints, very accurately, in environments and under conditions that closely mimic those encountered in vivo. For example, advances in solid-state NMR methods enable structure determination of membrane proteins in detergent-free lipid bilayers, and of large soluble proteins prepared by sedimentation, while parallel advances in solution NMR methods and optimization of detergent-free lipid nanodiscs are rapidly pushing the envelope of the size limit for both soluble and membrane proteins. These experimental advantages, however, are partially squandered during structure calculation, because the commonly used force fields are purely repulsive and neglect solvation, Van der Waals forces and electrostatic energy. Here we describe a new force field, and updated energy functions, for protein structure calculations with EEFx implicit solvation, electrostatics, and Van der Waals Lennard-Jones forces, in the widely used program Xplor-NIH. The new force field is based primarily on CHARMM22, facilitating calculations with a wider range of biomolecules. The new EEFx energy function has been rewritten to enable OpenMP parallelism, and optimized to enhance computation efficiency. It implements solvation, electrostatics, and Van der Waals energy terms together, thus ensuring more consistent and efficient computation of the complete nonbonded energy lists. Updates in the related python module allow detailed analysis of the interaction energies and associated parameters. The new force field and energy function work with both soluble proteins and membrane proteins, including those with cofactors or engineered tags, and are very effective in situations where there are sparse experimental restraints. Results obtained for NMR-restrained calculations with a set of five soluble proteins and five membrane proteins show that structures calculated with EEFx have significant improvements in accuracy, precision, and conformation, and that structure refinement can be obtained by short relaxation with EEFx to obtain improvements in these key metrics. These developments broaden the range of biomolecular structures that can be calculated with high fidelity from NMR restraints.

Molecular dynamics simulations of biological membranes and membrane proteins using enhanced conformational sampling algorithms

This paper reviews various enhanced conformational sampling methods and explicit/implicit solvent/membrane models, as well as their recent applications to the exploration of the structure and dynamics of membranes and membrane proteins. Molecular dynamics simulations have become an essential tool to investigate biological problems, and their success relies on proper molecular models together with efficient conformational sampling methods. The implicit representation of solvent/membrane environments is reasonable approximation to the explicit all-atom models, considering the balance between computational cost and simulation accuracy. Implicit models can be easily combined with replica-exchange molecular dynamics methods to explore a wider conformational space of a protein. Other molecular models and enhanced conformational sampling methods are also briefly discussed. As application examples, we introduce recent simulation studies of glycophorin A, phospholamban, amyloid precursor protein, and mixed lipid bilayers and discuss the accuracy and efficiency of each simulation model and method. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Folding Simulations of the Transmembrane Helix of Virus Protein U in an Implicit Membrane Model

Vpu is an 81-amino-acid auxiliary membrane protein encoded by human immunodeficiency virus type 1 (HIV-1). One of its roles is to amplify viral release by self-assembling in homo-oligomers to form functional water-filled pores enabling the flux of ions across the membrane. Various NMR and CD studies have shown that the transmembrane domain of Vpu has a helical conformation. With a recently developed implicit membrane model and an efficient Monte Carlo (MC) algorithm using concerted backbone rotations, we simulate the folding of the transmembrane domain of Vpu at atomic resolution. The implicit membrane environment is based on the generalized Born theory and enables very long time scale events, such as folding to be observed using detailed all-atom representation of the protein. Such studies are currently computationally unfeasible with fully explicit lipid bilayer molecular dynamics simulations. The correct helical transmembrane structure of Vpu is predicted from extended conformations and remains stably inserted. Tilt and kink angles agree well with experimental estimates from NMR measurements. The experimentally observed change in tilt angle in membranes of varying hydrophobic width is accurately reproduced. The extensive simulation of a pentamer of the Vpu transmembrane domain in the implicit membrane gives results similar to the ones reported previously for fully explicit bilayer simulations.

United Atom Lipid Parameters for Combination with the Optimized Potentials for Liquid Simulations All-Atom Force Field

We have developed a new united-atom set of lipid force field parameters for dipalmitoylphosphatidylcholine (DPPC) lipid bilayers that can be combined with the all-atom optimized potentials for liquid simulations (OPLS-AA) protein force field. For this, all torsions have been refitted for a nonbonded 1-4 scale factor of 0.5, which is the standard in OPLS-AA. Improved van der Waals parameters have been obtained for the acyl lipid tails by matching simulation results of bulk pentadecane against recently improved experimental measurements. The charge set has been adjusted from previous lipid force fields to allow for an identical treatment of the alkoxy ester groups. This reduces the amount of parameters required for the model. Simulation of DPPC bilayers in the tension-free NPT ensemble at 50 °C gives the correct area per lipid of 62.9 ± 0.1 Å(2), which compares well with the recently refined experimental value of 63.0 Å(2). Electron density profiles and deuterium order parameters are similarly well reproduced. The new parameters will allow for improved simulation results in microsecond scale peptide partitioning simulations, which have proved problematic with prior parametrizations.

A Practical Implicit Membrane Potential for NMR Structure Calculations of Membrane Proteins

The highly anisotropic environment of the lipid bilayer membrane imposes significant constraints on the structures and functions of membrane proteins. However, NMR structure calculations typically use a simple repulsive potential that neglects the effects of solvation and electrostatics, because explicit atomic representation of the solvent and lipid molecules is computationally expensive and impractical for routine NMR-restrained calculations that start from completely extended polypeptide templates. Here, we describe the extension of a previously described implicit solvation potential, eefxPot, to include a membrane model for NMR-restrained calculations of membrane protein structures in XPLOR-NIH. The key components of eefxPot are an energy term for solvation free energy that works together with other nonbonded energy functions, a dedicated force field for conformational and nonbonded protein interaction parameters, and a membrane function that modulates the solvation free energy and dielectric screening as a function of the atomic distance from the membrane center, relative to the membrane thickness. Initial results obtained for membrane proteins with structures determined experimentally in lipid bilayer membranes show that eefxPot affords significant improvements in structural quality, accuracy, and precision. Calculations with eefxPot are straightforward to implement and can be used to both fold and refine structures, as well as to run unrestrained molecular-dynamics simulations. The potential is entirely compatible with the full range of experimental restraints measured by various techniques. Overall, it provides a useful and practical way to calculate membrane protein structures in a physically realistic environment.

De novo peptide structure prediction: an overview

Peptide structure identification is an important contribution to the further characterization of the residues involved in functional interactions. De novo structure peptide prediction has, in the past few years, made significant progresses that make reasonable, for peptides up to 50 amino acids, its use for the fast identification of their structural topologies. Here, we introduce some of the concepts underlying approaches of the field, together with their limits.

Ab initio calculations and validation of the pH-dependent structures of the His37-Trp41 quartet, the heart of acid activation and proton conductance in the M2 protein of Influenza A virus

The M2 protein of Influenza A virus forms a homotetrameric proton channel activated by low pH. The His37-Trp41 quartet is the heart of acid activation and proton conductance, but the functional mechanism is still controversial. We carried out ab initio calculations to model the pH-dependent structures of the His37-Trp41 quartet. In our model at neutral pH, the four His37 residues are configured into a pair of dimers; in each dimer, a proton is shared between Nδ1 on one residue and Nε2 on the other, and, under the restraint of the backbone, the two imidazole rings are nearly parallel, in contrast to a perpendicular arrangement for a free imidazole-imidazolium dimer. Within each dimer the +1 charge is highly delocalized, contributing to its stabilization in a low dielectric environment. The Nδ1-H-Nε2 strong hydrogen bonds result in significantly downfield shifted Nδ1 and Nε2 chemical shifts (at 169.7 and 167.6 ppm, respectively), in good agreement with experiments. In our model at acidic pH (where the channel becomes activated), a third proton binds to an imidazole-imidazolium dimer; the imidazole rings rotate away (each by ~55°) from each other, destroying the dimer structure. The two imidazoliums are stabilized by hydrogen bonds with water molecules and a cation-π interaction with Trp41. The Raman spectra calculated for the His37-Trp41 quartet at neutral and acidic pH are in agreement with experiments. Our calculations support an activation and conductance mechanism in which a hydronium ion from the N-terminal side passes a proton to an imidazole-imidazolium dimer; when the Trp41 gate is open, relaying of a proton onto a water molecule from the C-terminal side then allows the imidazole-imidazolium dimer to reform and be ready for the next round of proton conductance.

Multiscale molecular dynamics simulations of membrane proteins

The time and length scales accessible by biomolecular simulations continue to increase. This is in part due to improvements in algorithms and computing performance, but is also the result of the emergence of coarse-grained (CG) potentials, which complement and extend the information obtainable from fully detailed models. CG methods have already proven successful for a range of applications that benefit from the ability to rapidly simulate spontaneous self-assembly within a lipid membrane environment, including the insertion and/or oligomerization of a range of "toy models," transmembrane peptides, and single- and multi-domain proteins. While these simplified approaches sacrifice atomistic level detail, it is now straightforward to "reverse map" from CG to atomistic descriptions, providing a strategy to assemble membrane proteins within a lipid environment, prior to all-atom simulation. Moreover, recent developments have been made in "dual resolution" techniques, allowing different molecules in the system to be modeled with atomistic or CG resolution simultaneously.

Integrated prediction of one-dimensional structural features and their relationships with conformational flexibility in helical membrane proteins

Background

Many structural properties such as solvent accessibility, dihedral angles and helix-helix contacts can be assigned to each residue in a membrane protein. Independent studies exist on the analysis and sequence-based prediction of some of these so-called one-dimensional features. However, there is little explanation of why certain residues are predicted in a wrong structural class or with large errors in the absolute values of these features. On the other hand, membrane proteins undergo conformational changes to allow transport as well as ligand binding. These conformational changes often occur via residues that are inherently flexible and hence, predicting fluctuations in residue positions is of great significance.

Results

We performed a statistical analysis of common patterns among selected one-dimensional equilibrium structural features (ESFs) and developed a method for simultaneously predicting all of these features using an integrated system. Our results show that the prediction performance can be improved if multiple structural features are trained in an integrated model, compared to the current practice of developing individual models. In particular, the performance of the solvent accessibility and bend-angle prediction improved in this way. The well-performing bend-angle prediction can be used to predict helical positions with severe kinks at a modest success rate. Further, we showed that single-chain conformational dynamics, measured by B-factors derived from normal mode analysis, could be predicted from observed and predicted ESFs with good accuracy. A web server was developed (http://tardis.nibio.go.jp/netasa/htmone/) for predicting the one-dimensional ESFs from sequence information and analyzing the differences between the predicted and observed values of the ESFs.

Conclusions

The prediction performance of the integrated model is significantly better than that of the models performing the task separately for each feature for the solvent accessibility and bend-angle predictions. The predictability of the features also plays a role in determining flexible positions. Although the dynamics studied here concerns local atomic fluctuations, a similar analysis in terms of global structural features will be helpful in predicting large-scale conformational changes, for which work is in progress.

Structures of beta-amyloid peptide 1-40, 1-42, and 1-55-the 672-726 fragment of APP-in a membrane environment with implications for interactions with gamma-secretase

Aggregation of Amyloid beta (Abeta) peptide has been linked to the neurodegenerative Alzheimer's Disease and implicated in other amyloid diseases including cerebral amyloid angiopathy. Abeta peptide is generated by cleavage of the amyloid precursor protein (APP) by transmembrane proteases. It is crucial to determine the structures of beta-amyloid peptides in a membrane to provide a molecular basis for the cleavage mechanism. We report the structures of amyloid beta peptide (Abeta(1-40) and Abeta(1-42)) as well as the 672-726 fragment of APP (referred to as Abeta(1-55)) in a membrane environment determined by replica-exchange molecular dynamics simulation. Abeta(1-40) is found to have two helical domains A (13-22) and B(30-35) and a type I beta-turn at 23-27. The peptide is localized at the interface between membrane and solvent. Substantial fluctuations in domain A are observed. The dominant simulated tertiary structure of Abeta(1-40) is observed to be similar to the simulated Abeta(1-42) structure. However, there are differences observed in the overall conformational ensemble, as characterized by the two-dimensional free energy surfaces. The fragment of APP (Abeta(1-55)) is observed to have a long transmembrane helix. The position of the transmembrane region and ensemble of membrane structures are elucidated. The conformational transition between the transmembrane Abeta(1-55) structure, prior to cleavage, and the Abeta(1-40) structure, following cleavage, is proposed.

Rapid equilibrium sampling initiated from nonequilibrium data

Simulating the conformational dynamics of biomolecules is extremely difficult due to the rugged nature of their free energy landscapes and multiple long-lived, or metastable, states. Generalized ensemble (GE) algorithms, which have become popular in recent years, attempt to facilitate crossing between states at low temperatures by inducing a random walk in temperature space. Enthalpic barriers may be crossed more easily at high temperatures; however, entropic barriers will become more significant. This poses a problem because the dominant barriers to conformational change are entropic for many biological systems, such as the short RNA hairpin studied here. We present a new efficient algorithm for conformational sampling, called the adaptive seeding method (ASM), which uses nonequilibrium GE simulations to identify the metastable states, and seeds short simulations at constant temperature from each of them to quantitatively determine their equilibrium populations. Thus, the ASM takes advantage of the broad sampling possible with GE algorithms but generally crosses entropic barriers more efficiently during the seeding simulations at low temperature. We show that only local equilibrium is necessary for ASM, so very short seeding simulations may be used. Moreover, the ASM may be used to recover equilibrium properties from existing datasets that failed to converge, and is well suited to running on modern computer clusters.

Parallel tempering: theory, applications, and new perspectives

We review the history of the parallel tempering simulation method. From its origins in data analysis, the parallel tempering method has become a standard workhorse of physicochemical simulations. We discuss the theory behind the method and its various generalizations. We mention a selected set of the many applications that have become possible with the introduction of parallel tempering, and we suggest several promising avenues for future research.

A refinement protocol to determine structure, topology, and depth of insertion of membrane proteins using hybrid solution and solid-state NMR restraints

To fully describe the fold space and ultimately the biological function of membrane proteins, it is necessary to determine the specific interactions of the protein with the membrane. This property of membrane proteins that we refer to as structural topology cannot be resolved using X-ray crystallography or solution NMR alone. In this article, we incorporate into XPLOR-NIH a hybrid objective function for membrane protein structure determination that utilizes solution and solid-state NMR restraints, simultaneously defining structure, topology, and depth of insertion. Distance and angular restraints obtained from solution NMR of membrane proteins solubilized in detergent micelles are combined with backbone orientational restraints (chemical shift anisotropy and dipolar couplings) derived from solid-state NMR in aligned lipid bilayers. In addition, a supplementary knowledge-based potential, E (z) (insertion depth potential), is used to ensure the correct positioning of secondary structural elements with respect to a virtual membrane. The hybrid objective function is minimized using a simulated annealing protocol implemented into XPLOR-NIH software for general use.

CHARMM: the biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Conformational heterogeneity of the M2 proton channel and a structural model for channel activation

The M2 protein of influenza virus A is a proton-selective ion channel activated by pH. Structure determination by solid-state and solution NMR and X-ray crystallography has contributed significantly to our understanding, but channel activation may involve conformations not captured by these studies. Indeed, solid-state NMR data demonstrate that the M2 protein possesses significant conformational heterogeneity. Here, we report molecular dynamics (MD) simulations of the M2 transmembrane domain (TMD) in the absence and presence of the antiviral drug amantadine. The ensembles of MD conformations for both apo and bound forms reproduced the NMR data well. The TMD helix was found to kink around Gly-34, where water molecules penetrated deeply into the backbone. The amantadine-bound form exhibited a single peak approximately 10 degrees in the distribution of helix-kink angle, but the apo form exhibited 2 peaks, approximately 0 degrees and 40 degrees . Conformations of the apo form with small and large kink angles had narrow and wide pores, respectively, around the primary gate formed by His-37 and Trp-41. We propose a structural model for channel activation, in which the small-kink conformations dominate before proton uptake by His-37 from the exterior, and proton uptake makes the large-kink conformations more favorable, thereby priming His-37 for proton release to the interior.

Tilt and azimuthal angles of a transmembrane peptide: a comparison between molecular dynamics calculations and solid-state NMR data of sarcolipin in lipid membranes

We report molecular dynamics simulations in the explicit membrane environment of a small membrane-embedded protein, sarcolipin, which regulates the sarcoplasmic reticulum Ca-ATPase activity in both cardiac and skeletal muscle. In its monomeric form, we found that sarcolipin adopts a helical conformation, with a computed average tilt angle of 28 +/- 6 degrees and azymuthal angles of 66 +/- 22 degrees, in reasonable accord with angles determined experimentally (23 +/- 2 degrees and 50 +/- 4 degrees, respectively) using solid-state NMR with separated-local-field experiments. The effects of time and spatial averaging on both (15)N chemical shift anisotropy and (1)H/(15)N dipolar couplings have been analyzed using short-time averages of fast amide out-of-plane motions and following principal component dynamic trajectories. We found that it is possible to reproduce the regular oscillatory patterns observed for the anisotropic NMR parameters (i.e., PISA wheels) employing average amide vectors. This work highlights the role of molecular dynamics simulations as a tool for the analysis and interpretation of solid-state NMR data.

Calculation of protein heat capacity from replica-exchange molecular dynamics simulations with different implicit solvent models

The heat capacity has played a major role in relating microscopic and macroscopic properties of proteins and their disorder-order phase transition of folding. Its calculation by atomistic simulation methods remains a significant challenge due to the complex and dynamic nature of protein structures, their solvent environment, and configurational averaging. To better understand these factors on calculating a protein heat capacity, we provide a comparative analysis of simulation models that differ in their implicit solvent description and force-field resolution. Our model protein system is the src Homology 3 (SH3) domain of alpha-spectrin, and we report a series of 10 ns replica-exchange molecular dynamics simulations performed at temperatures ranging from 298 to 550 K, starting from the SH3 native structure. We apply the all-atom CHARMM22 force field with different modified analytical generalized Born solvent models (GBSW and GBMV2) and compare these simulation models with the distance-dependent dielectric screening of charge-charge interactions. A further comparison is provided with the united-atom CHARMM19 plus a pairwise GB model. Unfolding-folding transition temperatures of SH3 were estimated from the temperature-dependent profiles of the heat capacity, root-mean-square distance from the native structure, and the fraction of native contacts, each calculated from the density of states by using the weighted histogram analysis method. We observed that, for CHARMM22, the unfolding transition and energy probability density were quite sensitive to the implicit solvent description, in particular, the treatment of the protein-solvent dielectric boundary in GB models and their surface-area-based hydrophobic term. Among the solvent models tested, the calculated melting temperature varied in the range 353-438 K and was higher than the experimental value near 340 K. A reformulated GBMV2 model of employing a smoother molecular-volume dielectric interface was the most accurate in reproducing the native conformation and a two-state folding landscape, although the melting transition temperature did not show the smallest deviation from experiment. For the lower-resolution CHARMM19/GB model, the simulations failed to yield a bimodal energy distribution, yet the melting temperature was observed to be a good estimate of higher-resolution simulation models. We also demonstrate that a careful analysis of a relatively long simulation is necessary to avoid trapping in local minima and to find a true thermodynamic transition temperature.

Effects of tryptophan microenvironment, soluble domain, and vesicle size on the thermodynamics of membrane protein folding: lessons from the transmembrane protein OmpA

Refolding curves of the integral membrane protein outer membrane protein A (OmpA) were measured to determine the conformational stabilities of this model system for membrane protein folding. Wild-type OmpA exhibits a free energy of unfolding (DeltaG degrees H2O) of 10.5 kcal/mol. Mutants, containing a single tryptophan residue at the native positions 7, 15, 57, 102, or 143, are less stable than wild-type OmpA, with DeltaG degrees H2O values of 6.7, 4.8, 2.4, 4.7, and 2.8 kcal/mol, respectively. The trend observed here is discussed in terms of noncovalent interactions, including aromatic interactions and hydrogen bonding. The effect of the soluble tail on the conformational stability of the transmembrane domain of OmpA was also investigated via truncated single-Trp mutants; DeltaG degrees H2O values for four of the five truncated mutants are greater by >2.7 kcal/mol relative to the full-length versions, suggesting that the absence of the soluble domain may destabilize the unfolded transmembrane domain. Finally, dynamic light scattering experiments were performed to measure the effects of urea and protein on vesicle size and stability. Urea concentrations greater than 1 M cause an increase in vesicle size, and these diameters are unaltered in the presence of protein. These dynamic light scattering results complement the fluorescence studies and illustrate the important effects of vesicle size on protein conformational stability.

Ultraviolet resonance Raman spectroscopy of folded and unfolded states of an integral membrane protein

The vibrational structure of native anchoring tryptophan (Trp) and tyrosine residues in an integral membrane protein, bacterial outer membrane protein A (OmpA), have been investigated using UV resonance Raman (UVRR) spectroscopy for the first time. Spectra of native OmpA, a single-Trp mutant, and a Trp-less mutant were recorded in folded and unfolded states, and reveal significant changes in tryptophan structure and local environment. Salient alterations upon folding include loss of hydrogen-bonding character of indole N1H, evidenced by a shift in W17 frequency from 874 and 878 cm(-1), and growth in hydrophobicity of the local tryptophan environment, supported by increase in the ratio I1361/I1340. In addition to these site-specific changes in a single tryptophan residue, modification of the vibrational structure of the remaining native tryptophan and tyrosine amino acids is also evident. Finally, the UVRR data presented here indicate that the structures of OmpA folded in vesicle and folded in detergent may differ, and provide important foundations for ongoing studies of membrane protein folding.

De novo prediction of the structures of M. tuberculosis membrane proteins

The structures of four integral membrane proteins from the Mycobacterium tuberculosis (TB) gene, Rv2433c, Rv1861, Rv1616, and Rv3069, have been de novo predicted by combining a generalized Born implicit solvent/membrane model with replica exchange molecular dynamics simulations to sample the conformational space of each protein.

Implicit membrane models for membrane protein simulation

Implicit models of membrane environments offer computational advantages in simulations of membrane-interacting proteins and peptides. Such methods are especially useful for studies of long time scale processes, such as folding and aggregation, or very large complexes that are otherwise intractable with explicit lipid environments. Implicit models replace explicit solute-solvent interactions with a mean-field approach. In the most physical models, continuum dielectric electrostatics is combined with empirical formulations for the nonpolar components of the free energy of solvation. The practical use of a number of implicit membrane models ranging from the empirical IMM1 method to generalized Born-based methods with two-dielectric and multidielectric representations of biological membrane characteristics is presented.

Acoustic Wave (TSM) Biosensors: Weighing Bacteria

This chapter is focused on the development and use of acoustic wave biosensor platforms for the detection of bacteria, specifically those based on the thickness shear mode (TSM) resonator. We demonstrated the mechanical and electrical implications of bacterial positioning at the solid-liquid interface of a TSM biosensor and presented a model of the TSM with bacteria attached operating as coupled oscillators. The experiments and model provide an understanding of the nature of the signals produced by acoustic wave devices when they are used for testing bacteria. The paradox of “negative mass” could be a real threat to the interpretation of experimental results related to the detection of bacteria. The knowledge of the true nature of “negative mass” linked to the strength of bacteria attachment will contribute significantly to our understanding of the results of “weighing bacteria.” The results of this work can be used for bacterial detection and control of processes of bacterial settlement, bacterial colonization, biofilm formation, and bacterial infection in which bacterial attachment plays a role.

Monte carlo folding of trans-membrane helical peptides in an implicit generalized Born membrane

An efficient Monte Carlo (MC) algorithm using concerted backbone rotations is combined with a recently developed implicit membrane model to simulate the folding of the hydrophobic transmembrane domain M2TM of the M2 protein from influenza A virus and Sarcolipin at atomic resolution. The implicit membrane environment is based on generalized Born theory and has been calibrated against experimental data. The MC sampling has previously been used to fold several small polypeptides and been shown to be equivalent to molecular dynamics (MD). In combination with a replica exchange algorithm, M2TM is found to form continuous membrane spanning helical conformations for low temperature replicas. Sarcolipin is only partially helical, in agreement with the experimental NMR structures in lipid bilayers and detergent micelles. Higher temperature replicas exhibit a rapidly decreasing helicity, in agreement with expected thermodynamic behavior. To exclude the possibility of an erroneous helical bias in the simulations, the model is tested by sampling a synthetic Alanine-rich polypeptide of known helicity. The results demonstrate there is no overstabilization of helical conformations, indicating that the implicit model captures the essential components of the native membrane environment for M2TM and Sarcolipin.

Toward high-resolution prediction and design of transmembrane helical protein structures

The prediction and design at the atomic level of membrane protein structures and interactions is a critical but unsolved challenge. To address this problem, we have developed an all-atom physical model that describes intraprotein and protein-solvent interactions in the membrane environment. We evaluated the ability of the model to recapitulate the energetics and structural specificities of polytopic membrane proteins by using a battery of in silico prediction and design tests. First, in side-chain packing and design tests, the model successfully predicts the side-chain conformations at 73% of nonexposed positions and the native amino acid identities at 34% of positions in naturally occurring membrane proteins. Second, the model predicts significant energy gaps between native and nonnative structures of transmembrane helical interfaces and polytopic membrane proteins. Third, distortions in transmembrane helices are successfully recapitulated in docking experiments by using fragments of ideal helices judiciously defined around helical kinks. Finally, de novo structure prediction reaches near-atomic accuracy (<2.5 A) for several small membrane protein domains (<150 residues). The success of the model highlights the critical role of van der Waals and hydrogen-bonding interactions in the stability and structural specificity of membrane protein structures and sets the stage for the high-resolution prediction and design of complex membrane protein architectures.

Solid-state NMR characterization of conformational plasticity within the transmembrane domain of the influenza A M2 proton channel

Membrane protein function within the membrane interstices is achieved by mechanisms that are not typically available to water-soluble proteins. The whole balance of molecular interactions that stabilize three-dimensional structure in the membrane environment is different from that in an aqueous environment. As a result interhelical interactions are often dominated by non-specific van der Waals interactions permitting dynamics and conformational heterogeneity in these interfaces. Here, solid-state NMR data of the transmembrane domain of the M2 protein from influenza A virus are used to exemplify such conformational plasticity in a tetrameric helical bundle. Such data lead to very high resolution structural restraints that can identify both subtle and substantial structural differences associated with various states of the protein. Spectra from samples using two different preparation protocols, samples prepared in the presence and absence of amantadine, and spectra as a function of pH are used to illustrate conformational plasticity.

Coarse-grained molecular dynamics simulations of membrane proteins and peptides

Molecular dynamics (MD) simulations provide a valuable approach to the dynamics, structure, and stability of membrane-protein systems. Coarse-grained (CG) models, in which small groups of atoms are treated as single particles, enable extended (>100 ns) timescales to be addressed. In this study, we explore how CG-MD methods that have been developed for detergents and lipids may be extended to membrane proteins. In particular, CG-MD simulations of a number of membrane peptides and proteins are used to characterize their interactions with lipid bilayers. CG-MD is used to simulate the insertion of synthetic model membrane peptides (WALPs and LS3) into a lipid (PC) bilayer. WALP peptides insert in a transmembrane orientation, whilst the LS3 peptide adopts an interfacial location, both in agreement with experimental biophysical data. This approach is extended to a transmembrane fragment of the Vpu protein from HIV-1, and to the coat protein from fd phage. Again, simulated protein/membrane interactions are in good agreement with solid state NMR data for these proteins. CG-MD has also been applied to an M3-M4 fragment from the CFTR protein. Simulations of CFTR M3-M4 in a detergent micelle reveal formation of an alpha-helical hairpin, consistent with a variety of biophysical data. In an I231D mutant, the M3-M4 hairpin is additionally stabilized via an inter-helix Q207/D231 interaction. Finally, CG-MD simulations are extended to a more complex membrane protein, the bacterial sugar transporter LacY. Comparison of a 200 ns CG-MD simulation of LacY in a DPPC bilayer with a 50 ns atomistic simulation of the same protein in a DMPC bilayer shows that the two methods yield comparable predictions of lipid-protein interactions. Taken together, these results demonstrate the utility of CG-MD simulations for studies of membrane/protein interactions.

A generalized born implicit-membrane representation compared to experimental insertion free energies

An implicit-membrane representation based on the generalized Born theory of solvation has been developed. The method was parameterized against the water-to-cyclohexane insertion free energies of hydrophobic side-chain analogs. Subsequently, the membrane was compared with experimental data from translocon inserted polypeptides and validated by comparison with an independent dataset of six membrane-associated peptides and eight integral membrane proteins of known structure and orientation. Comparison of the insertion energy of alpha-helical model peptides with the experimental values from the biological hydrophobicity scale of Hessa et al. gave a correlation of 93% with a mean unsigned error of 0.64 kcal/mol, when charged residues were ignored. The membrane insertion energy was found to be dependent on residue position. This effect is particularly pronounced for charged and polar residues, which strongly prefer interfacial locations. All integral membrane proteins investigated orient and insert correctly into the implicit-membrane model. Remarkably, the membrane model correctly predicts a partially inserted configuration for the monotopic membrane protein cyclooxygenase, matching experimental and theoretical predictions. To test the applicability and usefulness of the implicit-membrane method, molecular simulations of influenza A M2 as well as the glycophorin A dimer were performed. Both systems remain structurally stable and integrated into the membrane.

Molecular dynamics simulations of large integral membrane proteins with an implicit membrane model

The heterogeneous dielectric generalized Born (HDGB) methodology is an the extension of the GBMV model for the simulation of integral membrane proteins with an implicit membrane environment. Three large integral membrane proteins, the bacteriorhodopsin monomer and trimer and the BtuCD protein, were simulated with the HDGB model in order to evaluate how well thermodynamic and dynamic properties are reproduced. Effects of the truncation of electrostatic interactions were examined. For all proteins, the HDGB model was able to generate stable trajectories that remained close to the starting experimental structures, in excellent agreement with explicit membrane simulations. Dynamic properties evaluated through a comparison of B-factors are also in good agreement with experiment and explicit membrane simulations. However, overall flexibility was slightly underestimated with the HDGB model unless a very large electrostatic cutoff is employed. Results with the HDGB model are further compared with equivalent simulations in implicit aqueous solvent, demonstrating that the membrane environment leads to more realistic simulations.

Positioning of proteins in membranes: a computational approach

A new computational approach has been developed to determine the spatial arrangement of proteins in membranes by minimizing their transfer energies from water to the lipid bilayer. The membrane hydrocarbon core was approximated as a planar slab of adjustable thickness with decadiene-like interior and interfacial polarity profiles derived from published EPR studies. Applicability and accuracy of the method was verified for a set of 24 transmembrane proteins whose orientations in membranes have been studied by spin-labeling, chemical modification, fluorescence, ATR FTIR, NMR, cryo-microscopy, and neutron diffraction. Subsequently, the optimal rotational and translational positions were calculated for 109 transmembrane, five integral monotopic and 27 peripheral protein complexes with known 3D structures. This method can reliably distinguish transmembrane and integral monotopic proteins from water-soluble proteins based on their transfer energies and membrane penetration depths. The accuracies of calculated hydrophobic thicknesses and tilt angles were approximately 1 A and 2 degrees, respectively, judging from their deviations in different crystal forms of the same proteins. The hydrophobic thicknesses of transmembrane proteins ranged from 21.1 to 43.8 A depending on the type of biological membrane, while their tilt angles with respect to the bilayer normal varied from zero in symmetric complexes to 26 degrees in asymmetric structures. Calculated hydrophobic boundaries of proteins are located approximately 5 A lower than lipid phosphates and correspond to the zero membrane depth parameter of spin-labeled residues. Coordinates of all studied proteins with their membrane boundaries can be found in the Orientations of Proteins in Membranes (OPM) database:http://opm.phar.umich.edu/.

A generalized Born formalism for heterogeneous dielectric environments: application to the implicit modeling of biological membranes

Reliable computer simulations of complex biological environments such as integral membrane proteins with explicit water and lipid molecules remain a challenging task. We propose a modification of the standard generalized Born theory of homogeneous solvent for modeling the heterogeneous dielectric environments such as lipid/water interfaces. Our model allows the representation of biological membranes in the form of multiple layered dielectric regions with dielectric constants that are different from the solute cavity. The proposed new formalism is shown to predict the electrostatic component of solvation free energy with a relative error of 0.17% compared to exact finite-difference solutions of the Poisson equation for a transmembrane helix test system. Molecular dynamics simulations of melittin and bacteriorhodopsin are carried out and performed over 10 ns and 7 ns of simulation time, respectively. The center of melittin along the membrane normal in these stable simulations is in excellent agreement with the relevant experimental data. Simulations of bacteriorhodopsin started from the experimental structure remained stable and in close agreement with experiment. We also examined the free energy profiles of water and amino acid side chain analogs upon membrane insertion. The results with our implicit membrane model agree well with the experimental transfer free energy data from cyclohexane to water as well as explicit solvent simulations of water and selected side chain analogs.

Balancing solvation and intramolecular interactions: toward a consistent generalized Born force field

The efficient and accurate characterization of solvent effects is a key element in the theoretical and computational study of biological problems. Implicit solvent models, particularly generalized Born (GB) continuum electrostatics, have emerged as an attractive tool to study the structure and dynamics of biomolecules in various environments. Despite recent advances in this methodology, there remain limitations in the parametrization of many of these models. In the present work, we demonstrate that it is possible to achieve a balanced implicit solvent force field by further optimizing the input atomic radii in combination with adjusting the protein backbone torsional energetics. This parameter optimization is guided by the potentials of mean force (PMFs) between amino acid polar groups, calculated from explicit solvent free energy simulations, and by conformational equilibria of short peptides, obtained from extensive folding and unfolding replica exchange molecular dynamics (REX-MD) simulations. Through the application of this protocol, the delicate balance between the competing solvation forces and intramolecular forces appears to be better captured, and correct conformational equilibria for a range of both helical and beta-hairpin peptides are obtained. The same optimized force field also successfully folds both beta-hairpin trpzip2 and mini-protein Trp-Cage, indicating that it is quite robust. Such a balanced, physics-based force field will be highly applicable to a range of biological problems including protein folding and protein structural dynamics.

Insertion and assembly of membrane proteins via simulation

Interactions of lipids are central to the folding and stability of membrane proteins. Coarse-grained molecular dynamics simulations have been used to reveal the mechanisms of self-assembly of protein/membrane and protein/detergent complexes for representatives of two classes of membrane protein, namely, glycophorin (a simple alpha-helical bundle) and OmpA (a beta-barrel). The accuracy of the coarse-grained simulations is established via comparison with the equivalent atomistic simulations of self-assembly of protein/detergent micelles. The simulation of OmpA/bilayer self-assembly reveals how a folded outer membrane protein can be inserted in a bilayer. The glycophorin/bilayer simulation supports the two-state model of membrane folding, in which transmembrane helix insertion precedes dimer self-assembly within a bilayer. The simulations also suggest that a dynamic equilibrium exists between the glycophorin helix monomer and dimer within a bilayer. The simulated glycophorin helix dimer is remarkably close in structure to that revealed by NMR. Thus, coarse-grained methods may help to define mechanisms of membrane protein (re)folding and will prove suitable for simulation of larger scale dynamic rearrangements of biological membranes.

Application of torsion angle molecular dynamics for efficient sampling of protein conformations

We investigate the application of torsion angle molecular dynamics (TAMD) to augment conformational sampling of peptides and proteins. Interesting conformational changes in proteins mainly involve torsional degrees of freedom. Carrying out molecular dynamics in torsion space does not only explicitly sample the most relevant degrees of freedom, but also allows larger integration time steps with elimination of the bond and angle degrees of freedom. However, the covalent geometry needs to be fixed during internal coordinate dynamics, which can introduce severe distortions to the underlying potential surface in the extensively parameterized modern Cartesian-based protein force fields. A "projection" approach (Katritch et al. J Comput Chem 2003, 24, 254-265) is extended to construct an accurate internal coordinate force field (ICFF) from a source Cartesian force field. Torsion crossterm corrections constructed from local molecular fragments, together with softened van der Waals and electrostatic interactions, are used to recover the potential surface and incorporate implicit bond and angle flexibility. MD simulations of dipeptide models demonstrate that full flexibility in both the backbone phi/psi and side chain chi1 angles are virtually restored. The efficacy of TAMD in enhancing conformational sampling is then further examined by folding simulations of small peptides and refinement experiments of protein NMR structures. The results show that an increase of several fold in conformational sampling efficiency can be reliably achieved. The current study also reveals some complicated intrinsic properties of internal coordinate dynamics, beyond energy conservation, that can limit the maximum size of the integration time step and thus the achievable gain in sampling efficiency.

Evaluating tilt angles of membrane-associated helices: comparison of computational and NMR techniques

A computational method to calculate the orientation of membrane-associated alpha-helices with respect to a lipid bilayer has been developed. It is based on a previously derived implicit membrane representation, which was parameterized using the structures of 46 alpha-helical membrane proteins. The method is validated by comparison with an independent data set of six transmembrane and nine antimicrobial peptides of known structure and orientation. The minimum energy orientations of the transmembrane helices were found to be in good agreement with tilt and rotation angles known from solid-state NMR experiments. Analysis of the free-energy landscape found two types of minima for transmembrane peptides: i), Surface-bound configurations with the helix long axis parallel to the membrane, and ii), inserted configurations with the helix spanning the membrane in a perpendicular orientation. In all cases the inserted configuration also contained the global energy minimum. Repeating the calculations with a set of solution NMR structures showed that the membrane model correctly distinguishes native transmembrane from nonnative conformers. All antimicrobial peptides investigated were found to orient parallel and bind to the membrane surface, in agreement with experimental data. In all cases insertion into the membrane entailed a significant free-energy penalty. An analysis of the contributions of the individual residue types confirmed that hydrophobic residues are the main driving force behind membrane protein insertion, whereas polar, charged, and aromatic residues were found to be important for the correct orientation of the helix inside the membrane.

Transmembrane helix prediction: a comparative evaluation and analysis

The prediction of transmembrane (TM) helices plays an important role in the study of membrane proteins, given the relatively small number (approximately 0.5% of the PDB) of high-resolution structures for such proteins. We used two datasets (one redundant and one non-redundant) of high-resolution structures of membrane proteins to evaluate and analyse TM helix prediction. The redundant (non-redundant) dataset contains structure of 434 (268) TM helices, from 112 (73) polypeptide chains. Of the 434 helices in the dataset, 20 may be classified as 'half-TM' as they are too short to span a lipid bilayer. We compared 13 TM helix prediction methods, evaluating each method using per segment, per residue and termini scores. Four methods consistently performed well: SPLIT4, TMHMM2, HMMTOP2 and TMAP. However, even the best methods were in error by, on average, about two turns of helix at the TM helix termini. The best and worst case predictions for individual proteins were analysed. In particular, the performance of the various methods and of a consensus prediction method, were compared for a number of proteins (e.g. SecY, ClC, KvAP) containing half-TM helices. The difficulties of predicting half-TM helices suggests that current prediction methods successfully embody the two-state model of membrane protein folding, but do not accommodate a third stage in which, e.g., short helices and re-entrant loops fold within a bundle of stable TM helices.

Interfacial folding and membrane insertion of designed peptides studied by molecular dynamics simulations

The mechanism of interfacial folding and membrane insertion of designed peptides is explored by using an implicit membrane generalized Born model and replica-exchange molecular dynamics. Folding/insertion simulations initiated from fully extended peptide conformations in the aqueous phase, at least 28 A away from the membrane interface, demonstrate a general mechanism for structure formation and insertion (when it occurs). The predominately hydrophobic peptides from the synthetic WALP and TMX series first become localized at the membrane-solvent interface where they form significant helical secondary structure via a helix-turn-helix motif that inserts the central hydrophobic residues into the membrane interior, and then fluctuations occur that provide a persistent helical structure throughout the peptide and it inserts with its N-terminal end moving across the membrane. More specifically, we observed that: (i) the WALP peptides (WALP16, WALP19, and WALP23) spontaneously insert in the membrane as just noted; (ii) TMX-1 also inserts spontaneously after a similar mechanism and forms a transmembrane helix with a population of approximately 50% at 300 K; and (iii) TMX-3 does not insert, but exists in a fluctuating membrane interface-bound form. These findings are in excellent agreement with available experimental data and demonstrate the potential for new implicit solvent/membrane models together with advanced simulation protocols to guide experimental programs in exploring the nature and mechanism of membrane-associated folding and insertion of biologically important peptides.