Scrutinizing molecular mechanics force fields on the submicrosecond timescale with NMR data

Influence of Na+ and Mg2+ ions on RNA structures studied with molecular dynamics simulations

The structure of ribonucleic acid (RNA) polymers is strongly dependent on the presence of, in particular Mg2+ cations to stabilize structural features. Only in high-resolution X-ray crystallography structures can ions be identified reliably. Here, we perform molecular dynamics simulations of 24 RNA structures with varying ion concentrations. Twelve of the structures were helical and the others complex folded. The aim of the study is to predict ion positions but also to evaluate the impact of different types of ions (Na+ or Mg2+) and the ionic strength on structural stability and variations of RNA. As a general conclusion Mg2+ is found to conserve the experimental structure better than Na+ and, where experimental ion positions are available, they can be reproduced with reasonable accuracy. If a large surplus of ions is present the added electrostatic screening makes prediction of binding-sites less reproducible. Distinct differences in ion-binding between helical and complex folded structures are found. The strength of binding (ΔG‡ for breaking RNA atom-ion interactions) is found to differ between roughly 10 and 26 kJ/mol for the different RNA atoms. Differences in stability between helical and complex folded structures and of the influence of metal ions on either are discussed.

Structural insights on the efficient catalysis of hydroperoxide reduction by Ohr: Crystallographic and molecular dynamics approaches

Organic hydroperoxide resistance (Ohr) enzymes are highly efficient Cys-based peroxidases that play central roles in bacterial response to fatty acid hydroperoxides and peroxynitrite, two oxidants that are generated during host-pathogen interactions. In the active site of Ohr proteins, the conserved Arg (Arg19 in Ohr from Xylella fastidiosa) and Glu (Glu51 in Ohr from Xylella fastidiosa) residues, among other factors, are involved in the extremely high reactivity of the peroxidatic Cys (C_p) toward hydroperoxides. In the closed state, the thiolate of C_p is in close proximity to the guanidinium group of Arg19. Ohr enzymes can also assume an open state, where the loop containing the catalytic Arg is far away from C_p and Glu51. Here, we aimed to gain insights into the putative structural switches of the Ohr catalytic cycle. First, we describe the crystal structure of Ohr from Xylella fastidiosa (XfOhr) in the open state that, together with the previously described XfOhr structure in the closed state, may represent two snapshots along the coordinate of the enzyme-catalyzed reaction. These two structures were used for the experimental validation of molecular dynamics (MD) simulations. MD simulations employing distinct protonation states and in silico mutagenesis indicated that the polar interactions of Arg19 with Glu51 and C_p contributed to the stabilization of XfOhr in the closed state. Indeed, C_p oxidation to the disulfide state facilitated the switching of the Arg19 loop from the closed to the open state. In addition to the Arg19 loop, other portions of XfOhr displayed high mobility, such as a loop rich in Gly residues. In summary, we obtained a high correlation between crystallographic data, MD simulations and biochemical/enzymatic assays. The dynamics of the Ohr enzymes are unique among the Cys-based peroxidases, in which the active site Arg undergoes structural switches throughout the catalytic cycle, while C_p remains relatively static.

Developing a molecular dynamics force field for both folded and disordered protein states

Many proteins that perform important biological functions are completely or partially disordered under physiological conditions. Molecular dynamics simulations could be a powerful tool for the structural characterization of such proteins, but it has been unclear whether the physical models (force fields) used in simulations are sufficiently accurate. Here, we systematically compare the accuracy of a number of different force fields in simulations of both ordered and disordered proteins, finding that each force field has strengths and limitations. We then describe a force field that substantially improves on the state-of-the-art accuracy for simulations of disordered proteins without sacrificing accuracy for folded proteins, thus broadening the range of biological systems amenable to molecular dynamics simulations.

Molecular dynamics (MD) simulation is a valuable tool for characterizing the structural dynamics of folded proteins and should be similarly applicable to disordered proteins and proteins with both folded and disordered regions. It has been unclear, however, whether any physical model (force field) used in MD simulations accurately describes both folded and disordered proteins. Here, we select a benchmark set of 21 systems, including folded and disordered proteins, simulate these systems with six state-of-the-art force fields, and compare the results to over 9,000 available experimental data points. We find that none of the tested force fields simultaneously provided accurate descriptions of folded proteins, of the dimensions of disordered proteins, and of the secondary structure propensities of disordered proteins. Guided by simulation results on a subset of our benchmark, however, we modified parameters of one force field, achieving excellent agreement with experiment for disordered proteins, while maintaining state-of-the-art accuracy for folded proteins. The resulting force field, a99SB-disp, should thus greatly expand the range of biological systems amenable to MD simulation. A similar approach could be taken to improve other force fields.

Previously Hidden Dynamics at the TCR-Peptide-MHC Interface Revealed

A structural characterization of the interaction between αβ TCRs and cognate peptide-MHC (pMHC) is central to understanding adaptive T cell-mediated immunity. X-ray crystallography, although the source of much structural data, traditionally provides only a static snapshot of the protein. Given the emerging evidence for the important role of conformational dynamics in protein function, we interrogated 309 crystallographic structures of pMHC complexes using ensemble refinement, a technique that can extract dynamic information from the x-ray data. Focusing on a subset of human pMHC class I systems, we found that in many cases, ensemble methods were able to uncover previously hidden evidence of significant conformational plasticity, thereby revealing additional information that can build upon and significantly enhance functional interpretations that are based on a single static structure. Notable examples include the interpretation of differences in the disease association of HLA subtypes, the relationship between peptide prominence and TCR recognition, the role of conformational flexibility in vaccine design, and the discrimination between induced fit and conformational selection models of TCR binding. We show that the currently widespread practice of analyzing pMHC interactions via the study of a single crystallographic structure does not make use of pertinent and easily accessible information from x-ray data concerning alternative protein conformations. This new analysis therefore not only highlights the capacity for ensemble methods to significantly enrich the interpretation of decades of structural data but also provides previously missing information concerning the dynamics of existing characterized TCR-pMHC interactions.

Lipid Configurations from Molecular Dynamics Simulations

The extent to which current force fields faithfully reproduce conformational properties of lipids in bilayer membranes, and whether these reflect the structural principles established for phospholipids in bilayer crystals, are central to biomembrane simulations. We determine the distribution of dihedral angles in palmitoyl-oleoyl phosphatidylcholine from molecular dynamics simulations of hydrated fluid bilayer membranes. We compare results from the widely used lipid force field of Berger et al. with those from the most recent C36 release of the CHARMM force field for lipids. Only the CHARMM force field produces the chain inequivalence with sn-1 as leading chain that is characteristic of glycerolipid packing in fluid bilayers. The exposure and high partial charge of the backbone carbonyls in Berger lipids leads to artifactual binding of Na+ ions reported in the literature. Both force fields predict coupled, near-symmetrical distributions of headgroup dihedral angles, which is compatible with models of interconverting mirror-image conformations used originally to interpret NMR order parameters. The Berger force field produces rotamer populations that correspond to the headgroup conformation found in a phosphatidylcholine lipid bilayer crystal, whereas CHARMM36 rotamer populations are closer to the more relaxed crystal conformations of phosphatidylethanolamine and glycerophosphocholine. CHARMM36 alone predicts the correct relative signs of the time-average headgroup order parameters, and reasonably reproduces the full range of NMR data from the phosphate diester to the choline methyls. There is strong motivation to seek further experimental criteria for verifying predicted conformational distributions in the choline headgroup, including the 31P chemical shift anisotropy and 14N and CD3 NMR quadrupole splittings.

Angiotensin II cyclic analogs as tools to investigate AT1R biased signaling mechanisms

G protein coupled receptors (GPCRs) produce pleiotropic effects by their capacity to engage numerous signaling pathways once activated. Functional selectivity (also called biased signaling), where specific compounds can bring GPCRs to adopt conformations that enable selective receptor coupling to distinct signaling pathways, continues to be significantly investigated. However, an important but often overlooked aspect of functional selectivity is the capability of ligands such as angiotensin II (AngII) to adopt specific conformations that may preferentially bind to selective GPCRs structures. Understanding both receptor and ligand conformation is of the utmost importance for the design of new drugs targeting GPCRs. In this study, we examined the properties of AngII cyclic analogs to impart biased agonism on the angiotensin type 1 receptor (AT₁R). Positions 3 and 5 of AngII were substituted for cysteine and homocysteine residues ([Sar¹Hcy^3,5]AngII, [Sar¹Cys³Hcy⁵]AngII and [Sar¹Cys^3,5]AngII) and the resulting analogs were evaluated for their capacity to activate the Gq/11, G12, Gi2, Gi3, Gz, ERK and β-arrestin (βarr) signaling pathways via AT₁R. Interestingly, [Sar¹Hcy^3,5]AngII exhibited potency and full efficacy on all pathways tested with the exception of the Gq pathway. Molecular dynamic simulations showed that the energy barrier associated with the insertion of residue Phe⁸ of AngII within the hydrophobic core of AT₁R, associated with Gq/11 activation, is increased with [Sar¹Hcy^3,5]AngII. These results suggest that constraining the movements of molecular determinants within a given ligand by introducing cyclic structures may lead to the generation of novel ligands providing more efficient biased agonism.

Ligand-induced action of the W2866.48 rotamer toggle switch in the β2-adrenergic receptor

Studies focused on GPCRs, particularly on the β₂-adrenergic receptor (β₂-AR), have demonstrated the relationship between ligand structure, receptor conformational changes and the corresponding pharmacological outcomes. Herein, we studied the molecular details of the rotameric flip of the W286^6.48 sidechain, i.e. a presumed action switch that has not been reported in native β₂-AR thus far. It is believed that although both the 'active' and 'inactive' conformers of β₂-AR exhibit similar conformations of this switch, it may still play a substantial role in the ligand-induced activation of the receptor. By using both experimental methods (time-resolved fluorescence spectroscopy) and molecular modeling techniques (enhanced-sampling molecular dynamics), we characterized the conformational rearrangements of W286^6.48 in relation to the type of ligand present in the binding cavity and to the conformation of the receptor ('active' vs. 'inactive' β₂-AR). We found that the conformational behaviour of W286^6.48 is correlated with the pharmacological character of the ligand present in the binding cavity but not with the instantaneous conformation of the receptor. Namely, agonists promote the W286^6.48 conformations that facilitate the increase of the solvation within the inner receptor channel. In contrast, antagonists and inverse agonists act toward the decrease of the solvation in the inner channel. This creates an opportunity for using computational methodologies in determining the pharmacological properties of various ligands. The combination of the time-resolved fluorescence spectroscopy technique with the enhanced-sampling molecular dynamics simulations is shown to be a powerful tool for studying the ligand-induced conformational rearrangements in GPCRs.

Observations on AMBER Force Field Performance under the Conditions of Low pH and High Salt Concentrations

Molecular dynamics simulations have become an important tool for the study of structures, dynamics, and functions of biomolecules. Time scales and force field accuracy are key factors for the reliability of these simulations. With the advancement of computational platforms and simulation technologies, all-atom simulations of proteins in explicitly represented aqueous solutions can reach as long as milliseconds. However, there are indications of minor force field flaws in literature. In this work we present our observations on force field accuracy under uncommon conditions. We performed molecular dynamics simulations of BBL refolding in aqueous solutions of acidic pH and high salt concentrations (up to 6 M) with the AMBER99SB-ILDN force field for a microsecond time scale. The reliability of the simulations relies on the accuracy of the physical models of protein, water, and ions. Our simulations show the same trend as experiments: higher salt concentration facilities refolding. However, we have observed the presence of β-sheet in the native helical region as well as α-helix and β-sheet in the native loop region. Some of the nonnative secondary structures are even more stable than native helices. Aside from the secondary structure issue under the uncommon conditions, we have found that the rigidity of glycine dihedral angles in the loop region leads to low root-mean-square deviations but large topological differences from the native structure. Whether this is due to a force field deficiency or not needs further investigations. Recently developed ion parameters exhibit evident liquid features even in the 6 M LiCl solution. However, cation-anion interactions in TIP3P water still seem too strong, leading to high fractions of contact ion pairs. We do not find any specific ion-binding motif, thus we conclude that the effect of salt is a nonspecific electrostatic screening in our simulations. Our observations on the AMBER force field performance under acidic conditions and high salt concentrations show that simulations under extreme conditions can provide informative tests of physical models.

The molecular mechanism behind resistance of the kinase FLT3 to the inhibitor quizartinib

Fms-like tyrosine kinase 3 (FLT3) is a receptor tyrosine kinase that is a drug target for leukemias. Several potent inhibitors of FLT3 exist, and bind to the inactive form of the enzyme. Unfortunately, resistance due to mutations in the kinase domain of FLT3 limits the therapeutic effects of these inhibitors. As in many other cases, it is not straightforward to explain why certain mutations lead to drug resistance. Extensive fully atomistic molecular dynamics (MD) simulations of FLT3 were carried out with an inhibited form (FLT-quizartinib complex), a free (apo) form, and an active conformation. In all cases, both the wild type (wt) proteins and two resistant mutants (D835F and Y842H) were studied. Analysis of the simulations revealed that impairment of protein-drug interactions cannot explain the resistance mutations in question. Rather, it appears that the active state of the mutant forms is perturbed by the mutations. It is therefore likely that perturbation of deactivation of the protein (which is necessary for drug binding) is responsible for the reduced affinity of the drug to the mutants. Importantly, this study suggests that it is possible to explain the source of resistance by mutations in FLT3 by an analysis of unbiased MD simulations.

Investigating Ebola virus pathogenicity using molecular dynamics

BACKGROUND

Ebolaviruses have been known to cause deadly disease in humans for 40 years and have recently been demonstrated in West Africa to be able to cause large outbreaks. Four Ebolavirus species cause severe disease associated with high mortality in humans. Reston viruses are the only Ebolaviruses that do not cause disease in humans. Conserved amino acid changes in the Reston virus protein VP24 compared to VP24 of other Ebolaviruses have been suggested to alter VP24 binding to host cell karyopherins resulting in impaired inhibition of interferon signalling, which may explain the difference in human pathogenicity. Here we used protein structural analysis and molecular dynamics to further elucidate the interaction between VP24 and KPNA5.

RESULTS

As a control experiment, we compared the interaction of wild-type and R137A-mutant (known to affect KPNA5 binding) Ebola virus VP24 with KPNA5. Results confirmed that the R137A mutation weakens direct VP24-KPNA5 binding and enables water molecules to penetrate at the interface. Similarly, Reston virus VP24 displayed a weaker interaction with KPNA5 than Ebola virus VP24, which is likely to reduce the ability of Reston virus VP24 to prevent host cell interferon signalling.

CONCLUSION

Our results provide novel molecular detail on the interaction of Reston virus VP24 and Ebola virus VP24 with human KPNA5. The results indicate a weaker interaction of Reston virus VP24 with KPNA5 than Ebola virus VP24, which is probably associated with a decreased ability to interfere with the host cell interferon response. Hence, our study provides further evidence that VP24 is a key player in determining Ebolavirus pathogenicity.

Molecular modeling and SPRi investigations of interleukin 6 (IL6) protein and DNA aptamers

Interleukin 6 (IL6), an inflammatory response protein has major implications in immune-related inflammatory diseases. Identification of aptamers for the IL6 protein aids in diagnostic, therapeutic, and theranostic applications. Three different DNA aptamers and their interactions with IL6 protein were extensively investigated in a phosphate buffed saline (PBS) solution. Molecular-level modeling through molecular dynamics provided insights of structural, conformational changes and specific binding domains of these protein-aptamer complexes. Multiple simulations reveal consistent binding region for all protein-aptamer complexes. Conformational changes coupled with quantitative analysis of center of mass (COM) distance, radius of gyration (R_g), and number of intermolecular hydrogen bonds in each IL6 protein-aptamer complex was used to determine their binding performance strength and obtain molecular configurations with strong binding. A similarity comparison of the molecular configurations with strong binding from molecular-level modeling concurred with Surface Plasmon Resonance imaging (SPRi) for these three aptamer complexes, thus corroborating molecular modeling analysis findings. Insights from the natural progression of IL6 protein-aptamer binding modeled in this work has identified key features such as the orientation and location of the aptamer in the binding event. These key features are not readily feasible from wet lab experiments and impact the efficacy of the aptamers in diagnostic and theranostic applications.

A charge equilibration formalism for treating charge transfer effects in MD simulations: Application to water clusters

Conventional classical force fields by construction do not explicitly partition intermolecular interactions to include polarization and charge transfer effects, whereas fully quantum mechanical treatments allow a means to effect this dissection (although not uniquely due to the lack of a charge transfer operator). Considering the importance of polarization in a variety of systems, a particular class of classical models, charge equilibration models, have been extensively developed to study those systems; since these types of interaction models are inherently based on movement of charge throughout a system, they are natural platform for including polarization and charge transfer effects within the context of molecular simulations. Here, we present two bond-space charge equilibration models we term as QE2 and mixed QE2 treat charge transfer in classical molecular mechanical calculations those provide practical solutions to two major drawbacks of charge equilibration models: (a) a nonvanishing amount of charge transfer between two heteroatoms at large separations, and (b) superlinear polarizability scaling during bond dissociation due to charge transfer over unphysical, large distances. To control charge transfer during dissociation of a bond in a molecular system, we introduce a distance-dependent scaling function (QE2 model) which, controls and recovers physical behavior of the homonuclear and heteronuclear charge transfer between two atoms at small and large values of internuclear separation; and the mixed QE2 model in which we combine the QE2 model under allow and disallow charge transfer situations that describe both charge transfer and polarizability in a distance-dependent manner. We demonstrate the utility of both models in the case of a water dimer, and compare the results with other existing models, and further, we perform short molecular dynamics simulations for few water clusters with the QE2 model to show the charge transfer and internuclear separation are correlated in dynamics. © 2017 Wiley Periodicals, Inc.

Differentiating the pre-hydrolysis states of wild-type and A59G mutant HRas: An insight through MD simulations

The most representative member of the Ras subfamily is its HRas isoform. Ras proteins being GTPases, possess an intrinsic activity to hydrolyze the GTP molecule to GDP. During the transition phases, between active and inactive states, P-loop and switch regions show maximum variations. Various hot-spot Ras mutants (G12V, A59G, Q61L etc) have been reported, that limit the protein's conformation in the permanent active state. In the present study, we aim to explore the structural dynamics of one such crucial mutant of Ras namely A59G which belongs to the conserved Switch II region of the protein. Approximately ∼15μs of Classical Molecular Dynamics (CMD) simulations have been carried out on the mutant and wild-type complexes. Further, a metadynamics simulation of 500ns was also carried out, which suggests an energy barrier of ∼9.56kcal/mol between wild-type and mutant conformation. We demonstrate the role of water molecule in maintaining the required interaction networks in the pre-hydrolysis state, its impact on A59G mutation, distinct orientation of the Gln61 residue in two conformations, disruption of crucial Gly60 and γ phosphate and the change in the Switch II region. The outcome of our study captures the pre-hydrolysis state of the HRas protein. It also establishes the fact that this mutation makes the movement of Switch II region and the conserved DXXGQ motif highly constrained, which is known to be an important requirement for hydrolysis. This suggests that the A59G mutation may decrease the rate of intrinsic hydrolysis as well as GAP-mediated hydrolysis.

Computer Simulations of Intrinsically Disordered Proteins

The investigation of intrinsically disordered proteins (IDPs) is a new frontier in structural and molecular biology that requires a new paradigm to connect structural disorder to function. Molecular dynamics simulations and statistical thermodynamics potentially offer ideal tools for atomic-level characterizations and thermodynamic descriptions of this fascinating class of proteins that will complement experimental studies. However, IDPs display sensitivity to inaccuracies in the underlying molecular mechanics force fields. Thus, achieving an accurate structural characterization of IDPs via simulations is a challenge. It is also daunting to perform a configuration-space integration over heterogeneous structural ensembles sampled by IDPs to extract, in particular, protein configurational entropy. In this review, we summarize recent efforts devoted to the development of force fields and the critical evaluations of their performance when applied to IDPs. We also survey recent advances in computational methods for protein configurational entropy that aim to provide a thermodynamic link between structural disorder and protein activity.

Insights from molecular dynamics simulations for computational protein design

A grand challenge in the field of structural biology is to design and engineer proteins that exhibit targeted functions. Although much success on this front has been achieved, design success rates remain low, an ever-present reminder of our limited understanding of the relationship between amino acid sequences and the structures they adopt. In addition to experimental techniques and rational design strategies, computational methods have been employed to aid in the design and engineering of proteins. Molecular dynamics (MD) is one such method that simulates the motions of proteins according to classical dynamics. Here, we review how insights into protein dynamics derived from MD simulations have influenced the design of proteins. One of the greatest strengths of MD is its capacity to reveal information beyond what is available in the static structures deposited in the Protein Data Bank. In this regard simulations can be used to directly guide protein design by providing atomistic details of the dynamic molecular interactions contributing to protein stability and function. MD simulations can also be used as a virtual screening tool to rank, select, identify, and assess potential designs. MD is uniquely poised to inform protein design efforts where the application requires realistic models of protein dynamics and atomic level descriptions of the relationship between dynamics and function. Here, we review cases where MD simulations was used to modulate protein stability and protein function by providing information regarding the conformation(s), conformational transitions, interactions, and dynamics that govern stability and function. In addition, we discuss cases where conformations from protein folding/unfolding simulations have been exploited for protein design, yielding novel outcomes that could not be obtained from static structures.

Influence of specific intermolecular interactions on the thermal and dielectric properties of bulk polymers: atomistic molecular dynamics simulations of Nylon 6

Specific intermolecular interactions, in particular H-bonding, have a strong influence on the structural, thermal and relaxation characteristics of polymers. We report here the results of molecular dynamics simulations of Nylon 6 which provides an excellent example for the investigation of such an influence. To demonstrate the effect of proper accounting for H-bonding on bulk polymer properties, the AMBER99sb force field is used with two different parametrization approaches leading to two different sets of partial atomic charges. The simulations allowed the study of the thermal and dielectric properties in a wide range of temperatures and cooling rates. The feasibility of the use of the three methods for the estimation of the glass transition temperature not only from the temperature dependence of structural characteristics such as density, but also by using the electrostatic energy and dielectric constant is demonstrated. The values of glass transition temperatures obtained at different cooling rates are practically the same for the three methods. By proper accounting for partial charges in the simulations, a reasonable agreement between the results of our simulations and experimental data for the density, thermal expansion coefficient, static dielectric constant and activation energy of γ and β relaxations is obtained demonstrating the validity of the modeling approach reported.

Error assessment in molecular dynamics trajectories using computed NMR chemical shifts

Accurate chemical shifts for the atoms in molecular mechanics (MD) trajectories can be obtained from quantum mechanical (QM) calculations that depend solely on the coordinates of the atoms in the localized regions surrounding atoms of interest. If these coordinates are correct and the sample size is adequate, the ensemble average of these chemical shifts should be equal to the chemical shifts obtained from NMR spectroscopy. If this is not the case, the coordinates must be incorrect. We have utilized this fact to quantify the errors associated with the backbone atoms in MD simulations of proteins. A library of regional conformers containing 169,499 members was constructed from 6 model proteins. The chemical shifts associated with the backbone atoms in each of these conformers was obtained from QM calculations using density functional theory at the B3LYP level with a 6-311+G(2d,p) basis set. Chemical shifts were assigned to each backbone atom in each MD simulation frame using a template matching approach. The ensemble average of these chemical shifts was compared to chemical shifts from NMR spectroscopy. A large systematic error was identified that affected the ¹H atoms of the peptide bonds involved in hydrogen bonding with water molecules or peptide backbone atoms. This error was highly sensitive to changes in electrostatic parameters. Smaller errors affecting the ¹³C^a and ¹⁵N atoms were also detected. We believe these errors could be useful as metrics for comparing the force-fields and parameter sets used in MD simulation because they are directly tied to errors in atomic coordinates.

The Mutational Landscape of the Oncogenic MZF1 SCAN Domain in Cancer

SCAN domains in zinc-finger transcription factors are crucial mediators of protein-protein interactions. Up to 240 SCAN-domain encoding genes have been identified throughout the human genome. These include cancer-related genes, such as the myeloid zinc finger 1 (MZF1), an oncogenic transcription factor involved in the progression of many solid cancers. The mechanisms by which SCAN homo- and heterodimers assemble and how they alter the transcriptional activity of zinc-finger transcription factors in cancer and other diseases remain to be investigated. Here, we provide the first description of the conformational ensemble of the MZF1 SCAN domain cross-validated against NMR experimental data, which are probes of structure and dynamics on different timescales. We investigated the protein-protein interaction network of MZF1 and how it is perturbed in different cancer types by the analyses of high-throughput proteomics and RNASeq data. Collectively, we integrated many computational approaches, ranging from simple empirical energy functions to all-atom microsecond molecular dynamics simulations and network analyses to unravel the effects of cancer-related substitutions in relation to MZF1 structure and interactions.

Transferability of different classical force fields for right and left handed α-helices constructed from enantiomeric amino acids

Amino acids can form d and l enantiomers, of which the l enantiomer is abundant in nature. The naturally occurring l enantiomer has a greater preference for a right handed helical conformation, and the d enantiomer for a left handed helical conformation. The other conformations, that is, left handed helical conformations of the l enantiomers and right handed helical conformations of the d enantiomers, are not common. The energetic differences between left and right handed alpha helical peptide chains constructed from enantiomeric amino acids are investigated using quantum chemical calculations (using the M06/6-311g(d,p) level of theory). Further, the performances of commonly used biomolecular force fields (OPLS/AA, CHARMM27/CMAP and AMBER) to represent the different helical conformations (left and right handed) constructed from enantiomeric (D and L) amino acids are evaluated. 5- and 10-mer chains from d and l enantiomers of alanine, leucine, lysine, and glutamic acid, in right and left handed helical conformations, are considered in the study. Thus, in total, 32 α-helical polypeptides (4 amino acids × 4 conformations of 5-mer and 10-mer) are studied. Conclusions, with regards to the performance of the force fields, are derived keeping the quantum optimized geometry as the benchmark, and on the basis of phi and psi angle calculations, hydrogen bond analysis, and different long range helical order parameters.

All-Atom Continuous Constant pH Molecular Dynamics With Particle Mesh Ewald and Titratable Water

Development of a pH stat to properly control solution pH in biomolecular simulations has been a long-standing goal in the community. Toward this goal recent years have witnessed the emergence of the so-called constant pH molecular dynamics methods. However, the accuracy and generality of these methods have been hampered by the use of implicit-solvent models or truncation-based electrostatic schemes. Here we report the implementation of the particle mesh Ewald (PME) scheme into the all-atom continuous constant pH molecular dynamics (CpHMD) method, enabling CpHMD to be performed with a standard MD engine at a fractional added computational cost. We demonstrate the performance using pH replica-exchange CpHMD simulations with titratable water for a stringent test set of proteins, HP36, BBL, HEWL, and SNase. With the sampling time of 10 ns per replica, most pK_a's are converged, yielding the average absolute and root-mean-square deviations of 0.61 and 0.77, respectively, from experiment. Linear regression of the calculated vs experimental pK_a shifts gives a correlation coefficient of 0.79, a slope of 1, and an intercept near 0. Analysis reveals inadequate sampling of structure relaxation accompanying a protonation-state switch as a major source of the remaining errors, which are reduced as simulation prolongs. These data suggest PME-based CpHMD can be used as a general tool for pH-controlled simulations of macromolecular systems in various environments, enabling atomic insights into pH-dependent phenomena involving not only soluble proteins but also transmembrane proteins, nucleic acids, surfactants, and polysaccharides.

Molecular Dynamics Simulations of 441 Two-Residue Peptides in Aqueous Solution: Conformational Preferences and Neighboring Residue Effects with the Amber ff99SB-ildn-NMR Force Field

Understanding the intrinsic conformational preferences of amino acids and the extent to which they are modulated by neighboring residues is a key issue for developing predictive models of protein folding and stability. Here we present the results of 441 independent explicit-solvent MD simulations of all possible two-residue peptides that contain the 20 standard amino acids with histidine modeled in both its neutral and protonated states. (3)J(HNHα) coupling constants and δ(Hα) chemical shifts calculated from the MD simulations correlate quite well with recently published experimental measurements for a corresponding set of two-residue peptides. Neighboring residue effects (NREs) on the average (3)J(HNHα) and δ(Hα) values of adjacent residues are also reasonably well reproduced, with the large NREs exerted experimentally by aromatic residues, in particular, being accurately captured. NREs on the secondary structure preferences of adjacent amino acids have been computed and compared with corresponding effects observed in a coil library and the average β-turn preferences of all amino acid types have been determined. Finally, the intrinsic conformational preferences of histidine, and its NREs on the conformational preferences of adjacent residues, are both shown to be strongly affected by the protonation state of the imidazole ring.

Oligomer Formation of Amyloid-β(29-42) from Its Monomers Using the Hamiltonian Replica-Permutation Molecular Dynamics Simulation

Oligomers of amyloid-β peptides (Aβ) are formed during the early stage of the amyloidogenesis process and exhibit neurotoxicity. The oligomer formation process of Aβ and even that of Aβ fragments are still poorly understood, though understanding of these processes is essential for remedying Alzheimer's disease. In order to better understand the oligomerization process of the C-terminal Aβ fragment Aβ(29-42) at the atomic level, we performed the Hamiltonian replica-permutation molecular dynamics simulation with Aβ(29-42) molecules using the explicit water solvent model. We observed that oligomers increased in size through the sequential addition of monomers to the oligomer, rather than through the assembly of small oligomers. Moreover, solvent effects played an important role in this oligomerization process.

Deciphering solution scattering data with experimentally guided molecular dynamics simulations

Time-resolved X-ray solution scattering is an increasingly popular method to measure conformational changes in proteins. Extracting structural information from the resulting difference X-ray scattering data is a daunting task. We present a method in which the limited but precious information encoded in such scattering curves is combined with the chemical knowledge of molecular force fields. The molecule of interest is then refined toward experimental data using molecular dynamics simulation. Therefore, the energy landscape is biased toward conformations that agree with experimental data. We describe and verify the method, and we provide an implementation in GROMACS.

Water Determines the Structure and Dynamics of Proteins

Water is an essential participant in the stability, structure, dynamics, and function of proteins and other biomolecules. Thermodynamically, changes in the aqueous environment affect the stability of biomolecules. Structurally, water participates chemically in the catalytic function of proteins and nucleic acids and physically in the collapse of the protein chain during folding through hydrophobic collapse and mediates binding through the hydrogen bond in complex formation. Water is a partner that slaves the dynamics of proteins, and water interaction with proteins affect their dynamics. Here we provide a review of the experimental and computational advances over the past decade in understanding the role of water in the dynamics, structure, and function of proteins. We focus on the combination of X-ray and neutron crystallography, NMR, terahertz spectroscopy, mass spectroscopy, thermodynamics, and computer simulations to reveal how water assist proteins in their function. The recent advances in computer simulations and the enhanced sensitivity of experimental tools promise major advances in the understanding of protein dynamics, and water surely will be a protagonist.

Asymmetric dynamics of ion channel forming proteins - Hepatitis C virus (HCV) p7 bundles

Protein p7 of hepatitis C virus (HCV) is a short 63 amino acid membrane protein which homo-oligomerises in the lipid membrane to form ion and proton conducting bundles. Two different genotypes (GTs) of p7, 1a and 5a, are used to simulate hexameric bundles of the protein embedded in a fully hydrated lipid bilayer during 400 ns molecular dynamics (MD) simulations. Whilst the bundle of GT 1a is based on a fully computational derived structure, the bundle of GT 5a is based on NMR spectroscopic data. Results of a full correlation analysis (FCA) reveal that albeit structural differences both bundles screen local minima during the simulation. The collective motion of the protein domains is asymmetric. No 'breathing-mode'-like dynamics is observed. The presence of divalent ions, such as Ca-ions affects the dynamics of especially solvent exposed parts of the protein, but leaves the asymmetric domain motion unaffected.

The effects of organic solvents on the folding pathway and associated thermodynamics of proteins: a microscopic view

Protein folding is subject to the effects of solvation environment. A variety of organic solvents are used as additives for in vitro refolding of denatured proteins. Examination of the solvent effects on protein folding could be of fundamental importance to understand the molecular interactions in determining protein structure. This article investigated the folding of α-helix and β-hairpin structures in water and the solutions of two representative refolding additives (methanol (MeOH) and 1-Ethyl-3-methylimidazolium chloride (EMIM-Cl) ionic liquid) using REMD simulations. For both α-helix and β-hairpin in MeOH/water solution or α-helix in EMIM-Cl/water solution, the transient structures along the folding pathway are consistent with the counterparts in water but the relative statistical weights are changed, leading to the decrease in the overall folding free energy barrier. Accordingly, MeOH promotes the folding of both α-helix and β-hairpin but EMIM-Cl ionic liquid only promotes the folding of α-helix, consistent with experimental observations. The present study reveals for the first time the trivial effects on folding route but significant effects on folding thermodynamics from MeOH and EMIM-Cl, explaining the function of protein refolding additives and testifying the validity of the folding mechanism revealed by in vitro protein folding study using refolding additives.

NMR Order Parameter Determination from Long Molecular Dynamics Trajectories for Objective Comparison with Experiment

Functional protein motions covering a wide range of time scales can be studied, among other techniques, by NMR and by molecular dynamics (MD) computer simulations. MD simulations of proteins now routinely extend into the hundreds of nanoseconds time scale range exceeding the overall tumbling correlation times of proteins in solution by several orders of magnitude. This provides a unique opportunity to rigorously validate these simulations by quantitative comparison with model-free order parameters derived from NMR relaxation experiments. However, presently there is no consensus on how such a comparison is best done. We address here how this can be accomplished in a way that is both efficient and objective. For this purpose, we analyze (15)N R1 and R2 and heteronuclear {(1)H}-(15)N NOE NMR relaxation parameters computed from 500 ns MD trajectories of 10 different protein systems using the model-free analysis. The resulting model-free S(2) order parameters are then used as targets for S(2) values computed directly from the trajectories by the iRED method by either averaging over blocks of variable lengths or by using exponentially weighted snapshots (wiRED). We find that the iRED results are capable of reproducing the target S(2) values with high accuracy provided that the averaging window is chosen 5 times the length of the overall tumbling correlation time. These results provide useful guidelines for the derivation of NMR order parameters from MD for a meaningful comparison with their experimental counterparts.

Protocol To Make Protein NMR Structures Amenable to Stable Long Time Scale Molecular Dynamics Simulations

A robust protocol for the treatment of NMR protein structures is presented that makes them amenable to long time scale molecular dynamics (MD) simulations that are stable. The protocol embeds an NMR structure in a native low energy region of the recently developed ff99SB_φψ(g24;CS) molecular mechanics force field. Extended MD trajectories that start from these structures show good consistency with proton-proton nuclear Overhauser effect data, and they reproduce NMR chemical shift data better than the original NMR structures as is demonstrated for four protein systems. Moreover, for all proteins studied here the simulations spontaneously approach the X-ray crystal structures, thereby improving the effective resolution of the initial structural models.

Investigating protein conformational energy landscapes and atomic resolution dynamics from NMR dipolar couplings: a review

Nuclear magnetic resonance spectroscopy is exquisitely sensitive to protein dynamics. In particular inter-nuclear dipolar couplings, that become measurable in solution when the protein is dissolved in a dilute liquid crystalline solution, report on all conformations sampled up to millisecond timescales. As such they provide the opportunity to describe the Boltzmann distribution present in solution at atomic resolution, and thereby to map the conformational energy landscape in unprecedented detail. The development of analytical methods and approaches based on numerical simulation and their application to numerous biologically important systems is presented.

Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment

Intrinsically disordered proteins (IDPs) are notoriously challenging to study both experimentally and computationally. The structure of IDPs cannot be described by a single conformation but must instead be described as an ensemble of interconverting conformations. Atomistic simulations are increasingly used to obtain such IDP conformational ensembles. Here, we have compared the IDP ensembles generated by eight all-atom empirical force fields against primary small-angle X-ray scattering (SAXS) and NMR data. Ensembles obtained with different force fields exhibit marked differences in chain dimensions, hydrogen bonding, and secondary structure content. These differences are unexpectedly large: changing the force field is found to have a stronger effect on secondary structure content than changing the entire peptide sequence. The CHARMM 22* ensemble performs best in this force field comparison: it has the lowest error in chemical shifts and J-couplings and agrees well with the SAXS data. A high population of left-handed α-helix is present in the CHARMM 36 ensemble, which is inconsistent with measured scalar couplings. To eliminate inadequate sampling as a reason for differences between force fields, extensive simulations were carried out (0.964 ms in total); the remaining small sampling uncertainty is shown to be much smaller than the observed differences. Our findings highlight how IDPs, with their rugged energy landscapes, are highly sensitive test systems that are capable of revealing force field deficiencies and, therefore, contributing to force field development.

Structural insights into the interactions of phorbol ester and bryostatin complexed with protein kinase C: a comparative molecular dynamics simulation study

Protein kinase C (PKC) isozymes are important regulatory enzymes that have been implicated in many diseases, including cancer, Alzheimer's disease, and in the eradication of HIV/AIDS. Given their potential clinical ramifications, PKC modulators, e.g. phorbol esters and bryostatin, are also of great interest in the drug development. However, structural details on the binding between PKC and its modulators, especially bryostatin - the highly potent and non-tumor promoting activator for PKCs, are still lacking. Here, we report the first comparative molecular dynamics study aimed at gaining structural insight into the mechanisms by which the PKC delta cys2 activator domain is used in its binding to phorbol ester and bryostatin-1. As anticipated in the phorbol ester binding, hydrogen bonds are formed through the backbone atoms of Thr242, Leu251, and Gly253 of PKC. However, the opposition of H-bond formation between Thr242 and Gly253 may cause the phorbol ester complex to become less stable when compared with the bryostatin binding. For the PKC delta-bryostatin complex, hydrogen bonds are formed between the Gly253 backbone carbonyl and the C30 carbomethoxy substituent of the ligand. Additionally, the indole Nε1 of the highly homologous Trp252 also forms an H-bond to the C20 ester group on bryostatin. Backbone fluctuations also suggest that this latter H-bond formation may abrogate the transient interaction between Trp252 and His269, thus dampening the fluctuations observed on the nearby Zn(2+)-coordinating residues. This new dynamic fluctuation dampening model can potentially benefit future design of new PKC modulators.

Validating solution ensembles from molecular dynamics simulation by wide-angle X-ray scattering data

Wide-angle x-ray scattering (WAXS) experiments of biomolecules in solution have become increasingly popular because of technical advances in light sources and detectors. However, the structural interpretation of WAXS profiles is problematic, partly because accurate calculations of WAXS profiles from structural models have remained challenging. In this work, we present the calculation of WAXS profiles from explicit-solvent molecular dynamics (MD) simulations of five different proteins. Using only a single fitting parameter that accounts for experimental uncertainties because of the buffer subtraction and dark currents, we find excellent agreement to experimental profiles both at small and wide angles. Because explicit solvation eliminates free parameters associated with the solvation layer or the excluded solvent, which would require fitting to experimental data, we minimize the risk of overfitting. We further find that the influence from water models and protein force fields on calculated profiles are insignificant up to q≈15nm(-1). Using a series of simulations that allow increasing flexibility of the proteins, we show that incorporating thermal fluctuations into the calculations significantly improves agreement with experimental data, demonstrating the importance of protein dynamics in the interpretation of WAXS profiles. In addition, free MD simulations up to one microsecond suggest that the calculated profiles are highly sensitive with respect to minor conformational rearrangements of proteins, such as an increased flexibility of a loop or an increase of the radius of gyration by < 1%. The present study suggests that quantitative comparison between MD simulations and experimental WAXS profiles emerges as an accurate tool to validate solution ensembles of biomolecules.

Secondary Structure of Rat and Human Amylin across Force Fields

The aggregation of human amylin has been strongly implicated in the progression of Type II diabetes. This 37-residue peptide forms a variety of secondary structures, including random coils, α-helices, and β-hairpins. The balance between these structures depends on the chemical environment, making amylin an ideal candidate to examine inherent biases in force fields. Rat amylin differs from human amylin by only 6 residues; however, it does not form fibrils. Therefore it provides a useful complement to human amylin in studies of the key events along the aggregation pathway. In this work, the free energy of rat and human amylin was determined as a function of α-helix and β-hairpin content for the Gromos96 53a6, OPLS-AA/L, CHARMM22/CMAP, CHARMM22*, Amberff99sb*-ILDN, and Amberff03w force fields using advanced sampling techniques, specifically bias exchange metadynamics. This work represents a first systematic attempt to evaluate the conformations and the corresponding free energy of a large, clinically relevant disordered peptide in solution across force fields. The NMR chemical shifts of rIAPP were calculated for each of the force fields using their respective free energy maps, allowing us to quantitatively assess their predictions. We show that the predicted distribution of secondary structures is sensitive to the choice of force-field: Gromos53a6 is biased towards β-hairpins, while CHARMM22/CMAP predicts structures that are overly α-helical. OPLS-AA/L favors disordered structures. Amberff99sb*-ILDN, AmberFF03w and CHARMM22* provide the balance between secondary structures that is most consistent with available experimental data. In contrast to previous reports, our findings suggest that the equilibrium conformations of human and rat amylin are remarkably similar, but that subtle differences arise in transient alpha-helical and beta-strand containing structures that the human peptide can more readily adopt. We hypothesize that these transient states enable dynamic pathways that facilitate the formation of aggregates and, eventually, amyloid fibrils.

ff14SB: Improving the Accuracy of Protein Side Chain and Backbone Parameters from ff99SB

Molecular mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Average errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple small adjustments of φ and ψ parameters were tested against NMR scalar coupling data and secondary structure content for short peptides. The best results were obtained from a physically motivated adjustment to the φ rotational profile that compensates for lack of ff99SB QM training data in the β-ppII transition region. Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reproduction of NMR χ1 scalar coupling measurements for proteins in solution. We also discuss the Amber ff12SB parameter set, a preliminary version of ff14SB that includes most of its improvements.

How amide hydrogens exchange in native proteins

Amide hydrogen exchange (HX) is widely used in protein biophysics even though our ignorance about the HX mechanism makes data interpretation imprecise. Notably, the open exchange-competent conformational state has not been identified. Based on analysis of an ultralong molecular dynamics trajectory of the protein BPTI, we propose that the open (O) states for amides that exchange by subglobal fluctuations are locally distorted conformations with two water molecules directly coordinated to the N-H group. The HX protection factors computed from the relative O-state populations agree well with experiment. The O states of different amides show little or no temporal correlation, even if adjacent residues unfold cooperatively. The mean residence time of the O state is ∼100 ps for all examined amides, so the large variation in measured HX rate must be attributed to the opening frequency. A few amides gain solvent access via tunnels or pores penetrated by water chains including native internal water molecules, but most amides access solvent by more local structural distortions. In either case, we argue that an overcoordinated N-H group is necessary for efficient proton transfer by Grotthuss-type structural diffusion.

Accurately modeling nanosecond protein dynamics requires at least microseconds of simulation

Advances in hardware and algorithms have greatly extended the timescales accessible to molecular simulation. This article assesses whether such long timescale simulations improve our ability to calculate order parameters that describe conformational heterogeneity on ps-ns timescales or if force fields are now a limiting factor. Order parameters from experiment are compared with order parameters calculated in three different ways from simulations ranging from 10 ns to 100 μs in length. Importantly, bootstrapping is employed to assess the variability in results for each simulation length. The results of 10-100 ns timescale simulations are highly variable, possibly explaining the variation in levels of agreement between simulation and experiment in published works examining different proteins. Fortunately, microsecond timescale simulations improve both the accuracy and precision of calculated order parameters, at least so long as the full exponential fit or truncated average approximation is used instead of the common long-time limit approximation. The improved precision of these long timescale simulations allows a statistically sound comparison of a number of modern force fields, such as Amber03, Amber99sb-ILDN, and Charmm27. While there is some variation between these force fields, they generally give very similar results for sufficiently long simulations. The fact that so much simulation is required to precisely capture ps-ns timescale processes suggests that extremely extensive simulations are required for slower processes. Advanced sampling techniques could aid greatly, however, such methods will need to maintain accurate kinetics if they are to be of value for calculating dynamical properties like order parameters. © 2015 Wiley Periodicals, Inc.

Assessing the potential of atomistic molecular dynamics simulations to probe reversible protein-protein recognition and binding

Protein-protein recognition and binding are governed by diffusion, noncovalent forces and conformational flexibility, entangled in a way that only molecular dynamics simulations can dissect at high resolution. Here we exploited ubiquitin's noncovalent dimerization equilibrium to assess the potential of atomistic simulations to reproduce reversible protein-protein binding, by running submicrosecond simulations of systems with multiple copies of the protein at millimolar concentrations. The simulations essentially fail because they lead to aggregates, yet they reproduce some specificity in the binding interfaces as observed in known covalent and noncovalent ubiquitin dimers. Following similar observations in literature we hint at electrostatics and water descriptions as the main liable force field elements, and propose that their optimization should consider observables relevant to multi-protein systems and unfolded proteins. Within limitations, analysis of binding events suggests salient features of protein-protein recognition and binding, to be retested with improved force fields. Among them, that specific configurations of relative direction and orientation seem to trigger fast binding of two molecules, even over 50 Å distances; that conformational selection can take place within surface-to-surface distances of 10 to 40 Å i.e. well before actual intermolecular contact; and that establishment of contacts between molecules further locks their conformations and relative orientations.

Molecular Dynamics Simulation Analysis of Anti-MUC1 Aptamer and Mucin 1 Peptide Binding

Aptasensors utilize aptamers as bioreceptors. Aptamers are highly efficient, have a high specificity and are reusable. Within the biosensor the aptamers are immobilized to maximize their access to target molecules. Knowledge of the orientation and location of the aptamer and peptide during binding could be gained through computational modeling. Experimentally, the aptamer (anti-MUC1 S2.2) has been identified as a bioreceptor for breast cancer biomarker mucin 1 (MUC1) protein. However, within this protein lie several peptide variants with the common sequence APDTRPAP that are targeted by the aptamer. Understanding orientation and location of the binding region for a peptide-aptamer complex is critical in their biosensor applicability. In this study, we investigate through computational modeling how this peptide sequence and its minor variants affect the peptide-aptamer complex binding. We use molecular dynamics simulations to study multiple peptide-aptamer systems consisting of MUC1 (APDTRPAP) and MUC1-G (APDTRPAPG) peptides with the anti-MUC1 aptamer under similar physiological conditions reported experimentally. Multiple simulations of the MUC1 peptide and aptamer reveal that the peptide interacts between 3' and 5' ends of the aptamer but does not fully bind. Multiple simulations of the MUC1-G peptide indicate consistent binding with the thymine loop of the aptamer, initiated by the arginine residue of the peptide. We find that the binding event induces structural changes in the aptamer by altering the number of hydrogen bonds within the aptamer and establishes a stable peptide-aptamer complex. In all MUC1-G cases the occurrence of binding was confirmed by systematically studying the distance distributions between peptide and aptamers. These results are found to corroborate well with experimental study reported in the literature that indicated a strong binding in the case of MUC1-G peptide and anti-MUC1 aptamer. Present MD simulations highlight the role of the arginine residue of MUC1-G peptide in initiating the binding. The addition of the glycine residue to the peptide, as in the case of MUC1-G, is shown to yield a stable binding. Our study clearly demonstrates the ability of MD simulations to obtain molecular insights for peptide-aptamer binding, and to provide details on the orientation and location of binding between the peptide-aptamer that can be instrumental in biosensor development.

Identification of Distinct Conformations of the Angiotensin-II Type 1 Receptor Associated with the Gq/11 Protein Pathway and the β-Arrestin Pathway Using Molecular Dynamics Simulations

Biased signaling represents the ability of G protein-coupled receptors to engage distinct pathways with various efficacies depending on the ligand used or on mutations in the receptor. The angiotensin-II type 1 (AT1) receptor, a prototypical class A G protein-coupled receptor, can activate various effectors upon stimulation with the endogenous ligand angiotensin-II (AngII), including the Gq/11 protein and β-arrestins. It is believed that the activation of those two pathways can be associated with distinct conformations of the AT1 receptor. To verify this hypothesis, microseconds of molecular dynamics simulations were computed to explore the conformational landscape sampled by the WT-AT1 receptor, the N111G-AT1 receptor (constitutively active and biased for the Gq/11 pathway), and the D74N-AT1 receptor (biased for the β-arrestin1 and -2 pathways) in their apo-forms and in complex with AngII. The molecular dynamics simulations of the AngII-WT-AT1, N111G-AT1, and AngII-N111G-AT1 receptors revealed specific structural rearrangements compared with the initial and ground state of the receptor. Simulations of the D74N-AT1 receptor revealed that the mutation stabilizes the receptor in the initial ground state. The presence of AngII further stabilized the ground state of the D74N-AT1 receptor. The biased agonist [Sar(1),Ile(8)]AngII also showed a preference for the ground state of the WT-AT1 receptor compared with AngII. These results suggest that activation of the Gq/11 pathway is associated with a specific conformational transition stabilized by the agonist, whereas the activation of the β-arrestin pathway is linked to the stabilization of the ground state of the receptor.