Validation of molecular force field parameters for peptides including isomerized amino acids

Recently, stereoinversions and isomerizations of amino acid residues in the proteins of living beings have been observed. Because isomerized amino acids cause structural changes and denaturation of proteins, isomerizations of amino acid residues are suspected to cause age‐related diseases. In this study, AMBER molecular force field parameters were tested by using computationally generated nonapeptides and tripeptides including stereoinverted and/or isomerized amino acid residues. Energy calculations by using density functional theory were also performed for comparison. Although the force field parameters were developed by parameter fitting for l ‐α‐amino acids, the accuracy of the computational results for d ‐amino acids and β‐amino acids was comparable to those for l ‐α‐amino acids. The conformational energies for tripeptides calculated by using density functional theory were reproduced more accurately than those for nonapeptides calculated by using the molecular mechanical force field. The evaluations were performed for the ff99SB, ff03, ff12SB, and the latest ff14SB force field parameters.     

Improved side‐chain torsion potentials for the Amber ff99SB protein force field

Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations in the accuracy of the force fields used for such simulations and spurring efforts to refine these force fields. Recent modifications to the Amber and CHARMM protein force fields, for example, have improved the backbone torsion potentials, remedying deficiencies in earlier versions. Here, we further advance simulation accuracy by improving the amino acid side‐chain torsion potentials of the Amber ff99SB force field. First, we used simulations of model alpha‐helical systems to identify the four residue types whose rotamer distribution differed the most from expectations based on Protein Data Bank statistics. Second, we optimized the side‐chain torsion potentials of these residues to match new, high‐level quantum‐mechanical calculations. Finally, we used microsecond‐timescale MD simulations in explicit solvent to validate the resulting force field against a large set of experimental NMR measurements that directly probe side‐chain conformations. The new force field, which we have termed Amber ff99SB‐ILDN, exhibits considerably better agreement with the NMR data. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Effects of force fields on the conformational and dynamic properties of amyloid β(1‐40) dimer explored by replica exchange molecular dynamics simulations

The conformational space and structural ensembles of amyloid beta (Aβ) peptides and their oligomers in solution are inherently disordered and proven to be challenging to study. Optimum force field selection for molecular dynamics (MD) simulations and the biophysical relevance of results are still unknown. We compared the conformational space of the Aβ(1‐40) dimers by 300 ns replica exchange MD simulations at physiological temperature (310 K) using: the AMBER‐ff99sb‐ILDN, AMBER‐ff99sb*‐ILDN, AMBER‐ff99sb‐NMR, and CHARMM22* force fields. Statistical comparisons of simulation results to experimental data and previously published simulations utilizing the CHARMM22* and CHARMM36 force fields were performed. All force fields yield sampled ensembles of conformations with collision cross sectional areas for the dimer that are statistically significantly larger than experimental results. All force fields, with the exception of AMBER‐ff99sb‐ILDN (8.8 ± 6.4%) and CHARMM36 (2.7 ± 4.2%), tend to overestimate the α‐helical content compared to experimental CD (5.3 ± 5.2%). Using the AMBER‐ff99sb‐NMR force field resulted in the greatest degree of variance (41.3 ± 12.9%). Except for the AMBER‐ff99sb‐NMR force field, the others tended to under estimate the expected amount of β‐sheet and over estimate the amount of turn/bend/random coil conformations. All force fields, with the exception AMBER‐ff99sb‐NMR, reproduce a theoretically expected β‐sheet‐turn‐β‐sheet conformational motif, however, only the CHARMM22* and CHARMM36 force fields yield results compatible with collapse of the central and C‐terminal hydrophobic cores from residues 17‐21 and 30‐36. Although analyses of essential subspace sampling showed only minor variations between force fields, secondary structures of lowest energy conformers are different.     

Predicting molecular properties of α-synuclein using force fields for intrinsically disordered proteins

Independent force field validation is an essential practice to keep track of developments and for performing meaningful Molecular Dynamics simulations. In this work, atomistic force fields for intrinsically disordered proteins (IDP) are tested by simulating the archetypical IDP α-synuclein in solution for 2.5 μs. Four combinations of protein and water force fields were tested: ff19SB/OPC , ff19SB/TIP4P-D , ff03CMAP/TIP4P-D , and a99SB-disp/TIP4P-disp , with four independent repeat simulations for each combination. We compare our simulations to the results of a 73 μs simulation using the a99SB-disp/TIP4P-disp combination, provided by D. E. Shaw Research. From the trajectories, we predict a range of experimental observations of α-synuclein and compare them to literature data. This includes protein radius of gyration and hydration, intramolecular distances, NMR chemical shifts, and ³J-couplings. Both ff19SB/TIP4P-D and a99SB-disp/TIP4P-disp produce extended conformational ensembles of α-synuclein that agree well with experimental radius of gyration and intramolecular distances while a99SB-disp/TIP4P-disp reproduces a balanced α-synuclein secondary structure content. It was found that ff19SB/OPC and ff03CMAP/TIP4P-D produce overly compact conformational ensembles and show discrepancies in the secondary structure content compared to the experimental data.     

Comparison of multiple Amber force fields and development of improved protein backbone parameters

The ff94 force field that is commonly associated with the Amber simulation package is one of the most widely used parameter sets for biomolecular simulation. After a decade of extensive use and testing, limitations in this force field, such as over-stabilization of alpha-helices, were reported by us and other researchers. This led to a number of attempts to improve these parameters, resulting in a variety of "Amber" force fields and significant difficulty in determining which should be used for a particular application. We show that several of these continue to suffer from inadequate balance between different secondary structure elements. In addition, the approach used in most of these studies neglected to account for the existence in Amber of two sets of backbone phi/psi dihedral terms. This led to parameter sets that provide unreasonable conformational preferences for glycine. We report here an effort to improve the phi/psi dihedral terms in the ff99 energy function. Dihedral term parameters are based on fitting the energies of multiple conformations of glycine and alanine tetrapeptides from high level ab initio quantum mechanical calculations. The new parameters for backbone dihedrals replace those in the existing ff99 force field. This parameter set, which we denote ff99SB, achieves a better balance of secondary structure elements as judged by improved distribution of backbone dihedrals for glycine and alanine with respect to PDB survey data. It also accomplishes improved agreement with published experimental data for conformational preferences of short alanine peptides and better accord with experimental NMR relaxation data of test protein systems.     

PPM: a side-chain and backbone chemical shift predictor for the assessment of protein conformational ensembles

The combination of the wide availability of protein backbone and side-chain NMR chemical shifts with advances in understanding of their relationship to protein structure makes these parameters useful for the assessment of structural-dynamic protein models. A new chemical shift predictor (PPM) is introduced, which is solely based on physical?Cchemical contributions to the chemical shifts for both the protein backbone and methyl-bearing amino-acid side chains. To explicitly account for the effects of protein dynamics on chemical shifts, PPM was directly refined against 100?ns long molecular dynamics (MD) simulations of 35 proteins with known experimental NMR chemical shifts. It is found that the prediction of methyl-proton chemical shifts by PPM from MD ensembles is improved over other methods, while backbone C??, C??, C??, N, and H^N chemical shifts are predicted at an accuracy comparable to the latest generation of chemical shift prediction programs. PPM is particularly suitable for the rapid evaluation of large protein conformational ensembles on their consistency with experimental NMR data and the possible improvement of protein force fields from chemical shifts.     

On the ability of molecular dynamics force fields to recapitulate NMR derived protein side chain order parameters

Molecular dynamics (MD) simulations have become a central tool for investigating various biophysical questions with atomistic detail. While many different proxies are used to qualify MD force fields, most are based on largely structural parameters such as the root mean square deviation from experimental coordinates or nuclear magnetic resonance (NMR) chemical shifts and residual dipolar couplings. NMR derived Lipari–Szabo squared generalized order parameter (O²) values of amide N? H bond vectors of the polypeptide chain were also often employed for refinement and validation. However, with a few exceptions, side chain methyl symmetry axis order parameters have not been incorporated into experimental reference sets. Using a test set of five diverse proteins, the performance of several force fields implemented in the NAMDD simulation package was examined. It was found that simulations employing explicit water implemented using the TIP3 model generally performed significantly better than those using implicit water in reproducing experimental methyl symmetry axis O² values. Overall the CHARMM27 force field performs nominally better than two implementations of the Amber force field. It appeared that recent quantum mechanics modifications to side chain torsional angles of leucine and isoleucine in the Amber force field have significantly hindered proper motional modeling for these residues. There remained significant room for improvement as even the best correlations of experimental and simulated methyl group Lipari–Szabo generalized order parameters fall below an R² of 0.8.     

Circular Dichroism and NMR Studies of Metabolically Stableα-Methylpolyamines: Spectral Comparison with Naturally Occurring Polyamines

Three synthetic polyamine analogs, α-methylspermine, and α,α′-dimethylspermine, were compared with their naturally occurring counterparts, spermidine and spermine, by two different spectral techniques. The interaction of polyamines with oligodeoxynucleotides was measured by circular dichroism in order to monitor the polyamine-induced conversion of right-handed B-DNA to the left-handed Z-form. The methylated analogs were shown to be equally effective as the natural polyamines in inducing the B → Z transition. The pH dependence of the chemical shift of all carbon atoms in each of the five polyamines was measured by ¹³C-NMR spectroscopy. With the exception of expected changes in chemical shift due to the presence of the α-methyl substituents, the chemical shifts and pH dependence of all carbon atoms in the three α-methyl polyamines were similar to the corresponding naturally occurring polyamines. The combined data indicate that α-methyl polyamines have physical properties that are very similar to their natural counterparts. The two metabolically stable polyamine analogs, α-methylspermidine and α,α′-dimethylspermine, are therefore useful surrogates for spermidine and spermine in the study of numerous polyamine-mediated effects in mammalian cell cultures and can be used in such studies without the requirement for coadministration of amine oxidase inhibitors.     

Dual‐tracer‐based isotope turnover rates in a highly invasive mysid Limnomysis benedeni from Lake Constance

Understanding the ecological patterns of invasive species and their habitats require an understanding of the species’ foraging ecology. Stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope values provide useful information into the study of animal ecology and evolution, since the isotope ratios of consumers reflect consumer's dietary patterns. Nevertheless, the lack of species‐ and element‐specific laboratory‐derived turnover rates could limit their application. Using a laboratory‐based dual stable isotope tracer approach (Na¹⁵NO₃ and NaH¹³CO₃), we evaluated the δ¹⁵N and δ¹³C isotope turnover rates in full‐grown adult invasive Limnomysis benedeni from Lake Constance. We provide δ¹⁵N and δ¹³C turnover rates based on nonlinear least‐squares regression and posterior linear regression models. Model precisions and fit were evaluated using Akaike's information criterion. Within a couple of days, the δ¹⁵N and δ¹³C of mysids began to change. Nevertheless, after about 14 days, L. benedeni did not reach equilibrium with their new isotope values. Since the experiment was conducted on adult subjects, it is evident that turnover was mainly influenced by metabolism (in contrast to growth). Unlike traditional dietary shifts, our laboratory‐based dual stable isotope tracer approach does not shift the experimental organisms into a new diet and avoids dietary effects on isotope values. Results confirm the application of isotopic tracers to label mysid subpopulations and could be used to reflect assimilation and turnover from the labeled dietary sources. Field‐based stable isotope studies often use isotopic mixing models commonly assuming diet‐tissue steady state. Unfortunately, in cases where the isotopic composition of the animal is not in equilibrium with its diet, this can lead to highly misleading conclusions. Thus, our laboratory‐based isotopic incorporation rates assist interpretation of the isotopic values from the field and provide a foundation for future research into using isotopic tracers to investigate invasion ecology.     

Hash: a program to accurately predict protein Hα shifts from neighboring backbone shifts

Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H^α chemical shifts suffer from the following limitations. (1) For large proteins, the H^α chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C^α that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H^α chemical shifts. Predicting accurate H^α chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H^α chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H^α chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.     

Motional timescale predictions by molecular dynamics simulations: Case study using proline and hydroxyproline sidechain dynamics

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use ¹³C NMR spin‐lattice relaxation times T₁ of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4‐hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius‐type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force‐field (termed as AMBER99SB‐ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc.     

Molecular dynamics guided study of salt bridge length dependence in both fluorinated and non-fluorinated parallel dimeric coiled-coils

The alpha-helical coiled-coil is one of the most common oligomerization motifs found in both native and engineered proteins. To better understand the stability and dynamics of the coiled-coil motifs, including those modified by fluorination, several fluorinated and nonfluorinated parallel dimeric coiled-coil protein structures were designed and modeled. We also attempt to investigate how changing the length and geometry of the important stabilizing salt bridges influences the coiled-coil protein structure. Molecular dynamics (MD) and free energy simulations with AMBER used a particle mesh Ewald treatment of the electrostatics in explicit TIP3P solvent with balanced force field treatments. Preliminary studies with legacy force fields (ff94, ff96, and ff99) show a profound instability of the coiled-coil structures in short MD simulation. Significantly, better behavior is evident with the more balanced ff99SB and ff03 protein force fields. Overall, the results suggest that the coiled-coil structures can readily accommodate the larger acidic arginine or S-2,7-diaminoheptanedoic acid mutants in the salt bridge, whereas substitution of the smaller L-ornithine residue leads to rapid disruption of the coiled-coil structure on the MD simulation time scale. This structural distortion of the secondary structure allows both the formation of large hydration pockets proximal to the charged groups and within the hydrophobic core. Moreover, the increased structural fluctuations and movement lead to a decrease in the water occupancy lifetimes in the hydration pockets. In contrast, analysis of the hydration in the stable dimeric coiled-coils shows high occupancy water sites along the backbone residues with no water occupancy in the hydrophobic core, although transitory water interactions with the salt bridge residues are evident. The simulations of the fluorinated coiled-coils suggest that in some cases fluorination electrostatically stabilizes the intermolecular coiled-coil salt bridges. Structural analyses also reveal different side chain rotamer preferences for leucine when compared with 5,5,5,5',5',5'-hexafluoroleucine mutants. These observed differences in the side chain rotamer populations suggest differential changes in the side chain conformational entropy upon coiled-coil formation when the protein is fluorinated. The free energy of hydration of the isolated 5,5,5,5',5',5'-hexafluoroleucine amino acid is calculated to be 1.1 kcal/mol less stable than leucine; this hydrophobic penalty in the monomer may provide a driving force for coiled-coil dimer formation. Estimation of the ellipticity at 222 nm from a series of snapshots from the MD simulations with DicroCalc shows distinct increases in the ellipticity when the coiled-coil is fluorinated, which suggests that the helicity in the folded coiled-coils is greater when fluorinated.     

Ab initio-based vibrational analysis of α-poly(L-alanine)

Polarized ir and Raman spectra have been obtained on oriented films of α-helical poly(L -alanine) (α-PLA) and its N-deuterated derivative. These improved spectra permit a more complete assignment of observed bands to A-, E₁-, and E₂-species modes. A new empirical force field has been refined, based on ab initio force fields of N-methylacetamide and L -alanyl-L -alanine, which reproduces observed frequencies above 200 cm⁻¹ to less than 5 cm⁻¹. A new transition dipole coupling treatment avoids the weak coupling and perturbation approximations, and can now account for the newly observed and reassigned amide I (E₂) mode. As a result of this improved force field, several other observed bands have also been reassigned. © 1998 John Wiley & Sons, Inc. Biopoly 46: 283–317, 1998     

Accurate geometries for “Mountain pass” regions of the Ramachandran plot using quantum chemical calculations

Unusual local arrangements of protein in Ramachandran space are not well represented by standard geometry tools used in either protein structure refinement using simple harmonic geometry restraints or in protein simulations using molecular mechanics force fields. In contrast, quantum chemical computations using small poly‐peptide molecular models can predict accurate geometries for any well‐defined backbone Ramachandran orientation. For conformations along transition regions—ϕ from −60 to 60°—a very good agreement with representative high‐resolution experimental X‐ray (≤1.5 Å) protein structures is obtained for both backbone C⁻¹‐N‐C_α angle and the nonbonded O⁻¹…C distance, while “standard geometry” leads to the “clashing” of O…C atoms and Amber FF99SB predicts distances too large by about 0.15 Å. These results confirm that quantum chemistry computations add valuable support for detailed analysis of local structural arrangements in proteins, providing improved or missing data for less understood high‐energy or unusual regions.     

What stabilizes the 314‐helix in β3‐peptides? A conformational analysis using molecular simulation

β‐Peptides are analogs of natural α‐peptides and form a variety of remarkably stable structures. Having an additional carbon atom in the backbone of each residue, their folded conformation is not only influenced by the side‐chain sequence but also and foremost by their substitution pattern. The precise mechanism by which the side chains interact with the backbone is, however, hitherto not completely known. To unravel the various effects by which the side chains influence the backbone conformation, we quantify to which extent the dihedral angles of a β³‐substited peptide with an additional methyl group on the central C_α‐atom can be regarded as independent degrees of freedom and analyze the distributions of these dihedral angles. We also selectively capture the steric effect of substituents on the C_α‐ and C_β‐atoms of the central residue by alchemically changing them into dummy atoms, which have no nonbonded interactions. We find that the folded state of the β³‐peptide is primarily stabilized by a steric exclusion of large parts of the unfolded state (entropic effect) and only subsequently by mutual dependence of the ψ‐dihedral angles (enthalpic effect). The folded state of β‐peptides is stabilized by a different mechanism than that of α‐peptides. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Developing polarized protein-specific charges for protein dynamics: MD free energy calculation of pKa shifts for Asp26/Asp20 in thioredoxin

Ab initio quantum mechanical calculation of protein in solution is carried out to generate polarized protein-specific charge(s) (PPC) for molecular dynamics (MD) stimulation of protein. The quantum calculation of protein is made possible by developing a fragment-based quantum chemistry approach in combination with the implicit continuum solvent model. The computed electron density of protein is utilized to derive PPCs that represent the polarized electrostatic state of protein near the native structure. These PPCs are atom-centered like those in the standard force fields and are thus computationally attractive for molecular dynamics simulation of protein. Extensive MD simulations have been carried out to investigate the effect of electronic polarization on the structure and dynamics of thioredoxin. Our study shows that the dynamics of thioredoxin is stabilized by electronic polarization through explicit comparison between MD results using PPC and AMBER charges. In particular, MD free-energy calculation using PPCs accurately reproduced the experimental value of pK_a shift for ionizable residue Asp²⁶ buried inside thioredoxin, whereas previous calculations using standard force fields overestimated pK_a shift by twice as much. Accurate prediction of pK_a shifts by rigorous MD free energy simulation for ionizable residues buried inside protein has been a significant challenge in computational biology for decades. This study presented strong evidence that electronic polarization of protein plays an important role in protein dynamics.     

Toward a predictive understanding of slow methyl group dynamics in proteins

The development of the most recent generation of molecular mechanics force fields promises an increasingly predictive understanding of the protein dynamics-function relationship. Based on extensive validation against various types of experimental data, the AMBER force field ff99SB was benchmarked in recent years as a favorable force field for protein simulations. Recent improvements of the side chain and backbone potentials, made by different groups, led to the ff99SB-ILDN and ff99SBnmr1 force fields, respectively. The combination of these potentials into a unified force field, termed ff99SBnmr1-ILDN, was used in this study to perform a microsecond time scale molecular dynamics simulation of free ubiquitin in explicit solvent for validation against an extensive set of experimental NMR methyl group residual dipolar couplings. Our results show a high level of consistency between the experimental data and the values predicted from the molecular dynamics trajectory reflecting a systematically improved performance of ff99SBnmr1-ILDN over the original ff99SB force field. Moreover, the unconstrained ff99SBnmr1-ILDN MD ensemble achieves a similar level of agreement as the recently introduced EROS ensemble, which was constructed based on a large body of NMR data as constraints, including the methyl residual dipolar couplings. This suggests that ff99SBnmr1-ILDN provides a high-quality representation of the motions of methyl-bearing protein side chains, which are sensitive probes of protein-protein and protein-ligand interactions.     

Empirical correlation between protein backbone <Superscript>15</Superscript>N and <Superscript>13</Superscript>C secondary chemical shifts and its application to nitrogen chemical shift re-referencing

The linear analysis of chemical shifts (LACS) has provided a robust method for identifying and correcting ¹³C chemical shift referencing problems in data from protein NMR spectroscopy. Unlike other approaches, LACS does not require prior knowledge of the three-dimensional structure or inference of the secondary structure of the protein. It also does not require extensive assignment of the NMR data. We report here a way of extending the LACS approach to ¹⁵N NMR data from proteins, so as to enable the detection and correction of inconsistencies in chemical shift referencing for this nucleus. The approach is based on our finding that the secondary ¹⁵N chemical shift of the backbone nitrogen atom of residue i is strongly correlated with the secondary chemical shift difference (experimental minus random coil) between the alpha and beta carbons of residue i − 1. Thus once alpha and beta ¹³C chemical shifts are available (their difference is referencing error-free), the ¹⁵N referencing can be validated, and an appropriate offset correction can be derived. This approach can be implemented prior to a structure determination and can be used to analyze potential referencing problems in database data not associated with three-dimensional structure. Application of the LACS algorithm to the current BMRB protein chemical shift database, revealed that nearly 35% of the BMRB entries have δ ¹⁵N values mis-referenced by over 0.7 ppm and over 25% of them have δ ¹H^N values mis-referenced by over 0.12 ppm. One implication of the findings reported here is that a backbone ¹⁵N chemical shift provides a better indicator of the conformation of the preceding residue than of the residue itself. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Ensemble MD simulations restrained via crystallographic data: Accurate structure leads to accurate dynamics

Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free‐energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography‐based restraints into the MD protocol. Because these restraints are aimed at the ensemble‐average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native‐like fashion as dictated by the original force field. To validate this approach, we have used the data from solid‐state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well‐established model protein, ubiquitin. The ensemble‐restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid‐state chemical shifts, and backbone order parameters. The predictions for ¹⁵N relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high‐resolution crystallographic data can be viewed as protein‐specific empirical corrections to the standard force fields.     

Synthesis and conformational analysis of aib-containing peptide modelling for N-glycosylation site in N-glycoprotein

A tetrapetide containing an Aib residue, Boc-Asn-Aib-Thr-Aib-OMe, was synthesized as a peptide model for the N-glycosylation site in N-glycoproteins. Backbone conformation of the peptide and possible intramolecular interaction between the Asn and Thr side chains were elucidated by means of n.m.r. spectroscopy. Temperature dependence of NH proton chemical shift and NOE experiments showed that Boc-Asn-Aib-Thr-Aib-OMe has a tendency to form a β-turn structure with a hydrogen bond involving Thr and Aib⁴ NH groups. Incorporation of Aib residues in the peptide model promotes folding of the peptide backbone. With folded backbone conformation, carboxyamide protons of the Asn residue are not involved in hydrogen bond network, while the OH group of the Thr residue is a candidate for a hydrogen bond in DMSO-d₆ solution.