Certification of Molecular Dynamics Trajectories with NMR Chemical Shifts

Molecular dynamics ensembles of proteins generated by different force fields (AMBER ff99, ff99SB, ff03) have been quantitatively assessed based on their back-calculated Cα, Cβ, and C′ chemical shifts in comparison with NMR experiments. For the latest generation of force fields, a substantial improvement is found for ensemble-averaged chemical shifts over individual snapshots. Explicit inclusion of protein dynamics provides the largest improvement for Cβ chemical shifts, which are dominated by φ, ψ, and χ₁ dihedral angle distributions. Since NMR chemical shifts are available for a vast number of proteins, this novel strategy opens up the possibility to quantitatively certify molecular dynamics simulations on an unprecedented scale

Dynamic and Thermodynamic Signatures of Native and Non-Native Protein States with Application to the Improvement of Protein Structures

Accurate knowledge of the 3D structural ensemble of proteins is important for understanding of their biological function. We report here the application of microsecond all-atom molecular dynamics (MD) simulations in explicit solvent for the improvement of the quality of low-resolution structures obtained by protein structure prediction (decoys). Seventy MD simulations of ∼1 μs average duration were performed on 13 different protein systems starting from X-ray crystal structures and decoys. Their behavior can be divided into three groups: 22 trajectories converged toward the native state, 27 trajectories displayed a quasi-equilibrium by populating mainly a single non-native free energy basin, and 21 trajectories drifted away from their initial decoy structure transiently visiting multiple free energy minima. To determine whether the native structure can be identified among non-native ensembles, the free energy was determined for each basin by the MM/GBSA method together with the von Mises entropy estimator in dihedral angle space. For the proteins studied here, it is found that the ensembles belonging to free energy basins with the lowest free energies and the longest residence times are most native-like. The results demonstrate that explicit solvent microsecond MD simulations using the latest generation of protein force fields and free energy metrics are sufficiently accurate to permit positive identification of native state ensembles against low-resolution structural models and decoys. The approach can be applied to the direct refinement of predicted or experimental low-resolution protein structures

Decoding the Mobility and Time Scales of Protein Loops

The flexible nature of protein loops and the time scales of their dynamics are critical for many biologically important events at the molecular level, such as protein interaction and recognition processes. In order to obtain a predictive understanding of the dynamic properties of loops, 500 ns molecular dynamics (MD) computer simulations of 38 different proteins were performed and validated using NMR chemical shifts. A total of 169 loops were analyzed and classified into three types, namely fast loops with correlation times <10 ns, slow loops with correlation times between 10 and 500 ns, and loops that are static over the course of the whole trajectory. Chemical and biophysical loop descriptors, such as amino-acid sequence, average 3D structure, charge distribution, hydrophobicity, and local contacts were used to develop and parametrize the ToeLoop algorithm for the prediction of the flexibility and motional time scale of every protein loop, which is also implemented as a public Web server (http://spin.ccic.ohio-state.edu/index.php/loop). The results demonstrate that loop dynamics with their time scales can be predicted rapidly with reasonable accuracy, which will allow the screening of average protein structures to help better understand the various roles loops can play in the context of protein–protein interactions and binding

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 ¹⁵N <i>R</i>₁ and <i>R</i>₂ and heteronuclear {¹H}–¹⁵N NOE NMR relaxation parameters computed from 500 ns MD trajectories of 10 different protein systems using the model-free analysis. The resulting model-free <i>S</i>² order parameters are then used as targets for <i>S</i>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 <i>S</i>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

Customized Metabolomics Database for the Analysis of NMR ¹H–¹H TOCSY and ¹³C–¹H HSQC-TOCSY Spectra of Complex Mixtures

A customized metabolomics NMR database, termed ¹H­(¹³C)-TOCCATA, is introduced, which contains complete ¹H and ¹³C chemical shift information on individual spin systems and isomeric states of common metabolites. Since this information directly corresponds to cross sections of 2D ¹H–¹H TOCSY and 2D ¹³C–¹H HSQC-TOCSY spectra, it allows the straightforward and unambiguous identification of metabolites of complex metabolic mixtures at ¹³C natural abundance from these types of experiments. The ¹H­(¹³C)-TOCCATA database, which is complementary to the previously introduced TOCCATA database for the analysis of uniformly ¹³C-labeled compounds, currently contains 455 metabolites, and it can be used through a publicly accessible web portal. We demonstrate its performance by applying it to 2D ¹H–¹H TOCSY and 2D ¹³C–¹H HSQC-TOCSY spectra of a cell lysate from E. coli, which yields a substantial improvement over other databases, as well as 1D NMR-based approaches, in the number of compounds that can be correctly identified with high confidence

Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server

Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the coanalysis of up to three two-dimensional (2D) NMR spectra, namely, ¹³C–¹H HSQC (heteronuclear single quantum coherence spectroscopy), ¹H–¹H TOCSY (total correlation spectroscopy), and ¹³C–¹H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR

Suppression Subtractive Hybridization Analysis of Genes Regulated by Application of Exogenous Abscisic Acid in Pepper Plant (<i>Capsicum annuum</i> L.) Leaves under Chilling Stress

<div><p>Low temperature is one of the major factors limiting pepper (<i>Capsicum annuum</i> L.) production during winter and early spring in non-tropical regions. Application of exogenous abscisic acid (ABA) effectively alleviates the symptoms of chilling injury, such as wilting and formation of necrotic lesions on pepper leaves; however, the underlying molecular mechanism is not understood. The aim of this study was to identify genes that are differentially up- or downregulated in ABA-pretreated hot pepper seedlings incubated at 6°C for 48 h, using a suppression subtractive hybridization (SSH) method. A total of 235 high-quality ESTs were isolated, clustered and assembled into a collection of 73 unigenes including 18 contigs and 55 singletons. A total of 37 unigenes (50.68%) showed similarities to genes with known functions in the non-redundant database; the other 36 unigenes (49.32%) showed low similarities or unknown functions. Gene ontology analysis revealed that the 37 unigenes could be classified into nine functional categories. The expression profiles of 18 selected genes were analyzed using quantitative RT-PCR; the expression levels of 10 of these genes were at least two-fold higher in the ABA-pretreated seedlings under chilling stress than water-pretreated (control) plants under chilling stress. In contrast, the other eight genes were downregulated in ABA-pretreated seedlings under chilling stress, with expression levels that were one-third or less of the levels observed in control seedlings under chilling stress. These results suggest that ABA can positively and negatively regulate genes in pepper plants under chilling stress.</p></div

Analysis of mRNA expression using qPCR of four genes found downregulated with SSH.

<p>Total RNA was extracted from pepper leaves with ABA spray or water, subsequently 72 h after foliar application exposed for 48 h to 6°C. SE was calculated based on three biological replicates. Closed circle: ABA-pretreated samples under room temperature; open circle: ABA-sprayed samples prior to chilling stress; triangle down: water-sprayed samples prior to chilling stress. The level of ubiquitin was used as an internal reference gene.</p

Analysis of mRNA expression of six genes using qPCR found upregulated with SSH.

<p>Total RNA was extracted from pepper leaves with ABA spray or water, subsequently 72 h after foliar application exposed for 48 h to 6°C. SE was calculated based on three biological replicates. Closed circle: ABA-pretreated samples under room temperature; open circle: ABA-sprayed samples prior to chilling stress; triangle down: water-sprayed samples prior to chilling stress. Reaction conditions for each gene are shown in ‘Materials and methods’. The level of ubiquitin was used as an internal reference gene.</p