Describing Partially Unfolded States of Proteins from Sparse NMR Ddata

Proteins involved in signal transduction can usually be present in two states: an inactive and an active (signaling) state. In the case of photoreceptors such as PYP, it has been shown that the signaling state has a large degree of structural and dynamic disorder. Conventional structural NMR approaches present difficulties in describing such partially unfolded states. Owing to the disordered dynamical and transient nature of such states classical NOE-based information, when present, is sparse. Chemical shift changes upon partial unfolding can, however, be easily monitored from HSQC spectra. We show here that such states can be modeled by defining native-like inter-residue contacts for those residues that do not shift significantly upon partial unfolding. The feasibility of this approach is demonstrated using lysozyme as a test case and applied to model the partially unfolded signaling state (pB) of a truncated form of the photoactive yellow protein for which a “classical” NOE-based structure is available for validation. This approach should be generally applicable to systems in which part of the structure remains in a well-defined native-like conformation.     

Capturing Transition Paths and Transition States for Conformational Rearrangements in the Ribosome

To reveal the molecular determinants of biological function, one seeks to characterize the interactions that are formed in conformational and chemical transition states. In other words, what interactions govern the molecule’s energy landscape? To accomplish this, it is necessary to determine which degrees of freedom can unambiguously identify each transition state. Here, we perform simulations of large-scale aminoacyl-transfer RNA (aa-tRNA) rearrangements during accommodation on the ribosome and project the dynamics along experimentally accessible atomic distances. From this analysis, we obtain evidence for which coordinates capture the correct number of barrier-crossing events and accurately indicate when the aa-tRNA is on a transition path. Although a commonly used coordinate in single-molecule experiments performs poorly, this study implicates alternative coordinates along which rearrangements are accurately described as diffusive movements across a one-dimensional free-energy profile. From this, we provide the theoretical foundation required for single-molecule techniques to uncover the energy landscape governing aa-tRNA selection by the ribosome.     

Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a “sample and select” method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls (¹H, ¹⁵N, and ¹³C′). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.     

Subcellular Localization of Gram-Negative Bacterial Proteins Using Sparse Learning

One of the main challenges faced by biological applications is to predict protein subcellular localization in an automatic fashion accurately. To achieve this in these applications, a wide variety of machine learning methods have been proposed in recent years. Most of them focus on finding the optimal classification scheme and less of them take the simplifying the complexity of biological system into account. Traditionally such bio-data are analyzed by first performing a feature selection before classification. Motivated by CS (Compressive Sensing), we propose a method which performs locality preserving projection with a sparseness criterion such that the feature selection and dimension reduction are merged into one analysis. The proposed sparse method decreases the complexity of biological system, while increases protein subcellular localization accuracy. Experimental results are quite encouraging, indicating that the aforementioned sparse method is quite promising in dealing with complicated biological problems, such as predicting the subcellular localization of Gram-negative bacterial proteins.     

Conformational Studies of Tachykinin Peptides Using NMR Spectroscopy

A conformational analysis in water and DMSO of two tachykinin family peptides (scyliorhinin I (ScyI) and scyliorhinin II (ScyII)) was carried out by 1D and 2D NMR (DQF-COSY, TOCSY, HMQC, HMBC, NOESY and ROESY) and molecular dynamics calculation methods. In DMSO, two groups of conformations (major and minor) were obtained for both peptides based on the experimental data. The conformations proposed for ScyI represent a folded structure, which shows certain similarities to the structures reported for other NK-1 and NK-2 tachykinin agonists. In water ScyII displays a flexible, extended structure, whereas in DMSO the structure is more compact and, in the fragment from the centre to the C-terminus, several -turns may be present.     

Conformational Studies of Tachykinin Peptides Using NMR Spectroscopy

Summary A conformational analysis in water and DMSO of two tachykinin family peptides (scyliorhinin I (ScyI) and scyliorhinin II (ScyII)) was carried out by 1D and 2D NMR (DQF-COSY, TOCSY, HMQC, HMBC, NOESY and ROESY) and molecular dynamics calculation methods. In DMSO, two groups of conformations (major and minor) were obtained for both peptides based on the experimental data. The conformations proposed for ScyI represent a folded structure, which shows certain similarities to the structures reported for other NK-1 and NK-2 tachykinin agonists. In water ScyII displays a flexible, extended structure, whereas in DMSO the structure is more compact and, in the fragment from the centre to the C-terminus, several β-turns may be present.     

Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints

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Surface Fractality of Proteins From Theory and NMR Data

Abstract

Different approaches to study protein surface fractality are considered. An approach based on analysis of surface versus molecular weight dependence is shown to be an informative tool for investigation of protein surface behaviour. An evidence for protein surface fractality, obtained with the use of this analysis from the data of both NMR measurements in protein solutions and computer analysis of protein structures, is presented. Obtained value of fractal dimension of protein surface (d _s ? 2.2) is in a good agreement with the results of conventional approach (with variation of yardstick length) to protein surface fractality. A conclusion is made that surface enlargement due to the rise of protein molecular weight is accompanied by the increase of maximum scale of irregularities on protein surface. Possible effect of surface fractality on hydrodynamic characteristics of protein molecules in solution is discussed.     

The Conformational Analysis of Substance P Analogs Using High-Field NMR Techniques

Abstract

High-field nuclear magnetic resonance measurements were carried out on substance P fragments SP_4–11 [pGlu⁵]-SP_5–11 and [pGlu⁶]SP_6–11 both at 400 and at 500 MHz. A spectral simulation was carried out on two of these peptides and the coupling constants were interpreted in terms of the conformations. The J_NH-CHa coupling constants are all ～8 Hz, with the exception of glycine, indicating no preferred conformation for the backbone. For the amino acids other than p-Glu, a comparison of the coupling constant data suggests the same relative rotamer populations for the side chains. Proton longitudinal relaxation time data were measured for all three peptides and support the above conclusions.     

Structural Dynamics and Conformational Equilibria of SERCA Regulatory Proteins in Membranes by Solid-State NMR Restrained Simulations

Solid-state NMR spectroscopy is emerging as a powerful approach to determine structure, topology, and conformational dynamics of membrane proteins at the atomic level. Conformational dynamics are often inferred and quantified from the motional averaging of the NMR parameters. However, the nature of these motions is difficult to envision based only on spectroscopic data. Here, we utilized restrained molecular dynamics simulations to probe the structural dynamics, topology and conformational transitions of regulatory membrane proteins of the calcium ATPase SERCA, namely sarcolipin and phospholamban, in explicit lipid bilayers. Specifically, we employed oriented solid-state NMR data, such as dipolar couplings and chemical shift anisotropy measured in lipid bicelles, to refine the conformational ensemble of these proteins in lipid membranes. The samplings accurately reproduced the orientations of transmembrane helices and showed a significant degree of convergence with all of the NMR parameters. Unlike the unrestrained simulations, the resulting sarcolipin structures are in agreement with distances and angles for hydrogen bonds in ideal helices. In the case of phospholamban, the restrained ensemble sampled the conformational interconversion between T (helical) and R (unfolded) states for the cytoplasmic region that could not be observed using standard structural refinements with the same experimental data set. This study underscores the importance of implementing NMR data in molecular dynamics protocols to better describe the conformational landscapes of membrane proteins embedded in realistic lipid membranes.     

Structural Dynamics and Conformational Equilibria of SERCA Regulatory Proteins in Membranes by Solid-State NMR Restrained Simulations

Solid-state NMR spectroscopy is emerging as a powerful approach to determine structure, topology, and conformational dynamics of membrane proteins at the atomic level. Conformational dynamics are often inferred and quantified from the motional averaging of the NMR parameters. However, the nature of these motions is difficult to envision based only on spectroscopic data. Here, we utilized restrained molecular dynamics simulations to probe the structural dynamics, topology and conformational transitions of regulatory membrane proteins of the calcium ATPase SERCA, namely sarcolipin and phospholamban, in explicit lipid bilayers. Specifically, we employed oriented solid-state NMR data, such as dipolar couplings and chemical shift anisotropy measured in lipid bicelles, to refine the conformational ensemble of these proteins in lipid membranes. The samplings accurately reproduced the orientations of transmembrane helices and showed a significant degree of convergence with all of the NMR parameters. Unlike the unrestrained simulations, the resulting sarcolipin structures are in agreement with distances and angles for hydrogen bonds in ideal helices. In the case of phospholamban, the restrained ensemble sampled the conformational interconversion between T (helical) and R (unfolded) states for the cytoplasmic region that could not be observed using standard structural refinements with the same experimental data set. This study underscores the importance of implementing NMR data in molecular dynamics protocols to better describe the conformational landscapes of membrane proteins embedded in realistic lipid membranes.     

On Hydrophobicity and Conformational Specificity in Proteins

In this study we examine the distribution of hydrophobic residues in a nonredundant set of monomeric globular single-domain proteins. We find that the total fraction of hydrophobic residues is roughly constant and has no discernible dependence on protein size. This results in a decrease of the hydrophobicity of the core as the size of proteins increases. Using a normalized measure, and by comparing with sets of randomly reshuffled sequences, we show that this change in the composition of the core is statistically significant and robust with respect to which amino acids are considered hydrophobic and to how buried residues are defined. Comparison with model sequences optimized for stability, while still required to retain their native state as a unique minimum energy conformation, suggests that the size-independence of the total fraction of hydrophobic residues could be a result of requiring proteins to be conformationally specific.     

Computation of Conformational Coupling in Allosteric Proteins

In allosteric regulation, an effector molecule binding a protein at one site induces conformational changes, which alter structure and function at a distant active site. Two key challenges in the computational modeling of allostery are the prediction of the structure of one allosteric state starting from the structure of the other, and elucidating the mechanisms underlying the conformational coupling of the effector and active sites. Here we approach these two challenges using the Rosetta high-resolution structure prediction methodology. We find that the method can recapitulate the relaxation of effector-bound forms of single domain allosteric proteins into the corresponding ligand-free states, particularly when sampling is focused on regions known to change conformation most significantly. Analysis of the coupling between contacting pairs of residues in large ensembles of conformations spread throughout the landscape between and around the two allosteric states suggests that the transitions are built up from blocks of tightly coupled interacting sets of residues that are more loosely coupled to one another.     

Paramagnetic probes in NMR and EPR studies of membrane enzymes

The applications of paramagnetic probes to problems of structure and mechanism are discussed from the point of view of the membrane enzymologist. Problems unique to membrane systems are discussed, and a variety of nuclear and paramagnetic probes are evaluated. Three membrane ATPase (kidney (Na+ + K+)-ATPase, Ca2+-ATPase from sarcoplasmic reticulum and Mg2+-ATPase from kidney) are used to describe the types of experiments which can be done, the information which can be obtained and the limitations involved. Nuclear relaxation studies employing 1H, 7Li+, 31P and 205Tl+ nuclei are described. The advantages and disadvantages of Mn2+, Gd3+ and Cr3+ as paramagnetic probes are discussed in terms of the three ATPases. The theory and interpretation of Mn2+ and Gd3+ EPR spectra are evaluated in studies with the (Na+ + K+)-ATPase and Ca2+-ATPase, respectively.