Computational prediction of atomic structures of helical membrane proteins aided by EM maps

Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.     

Fragment-based phase extension for three-dimensional structure determination of membrane proteins by electron crystallography

In electron crystallography, membrane protein structure is determined from two-dimensional crystals where the protein is embedded in a membrane. Once large and well-ordered 2D crystals are grown, one of the bottlenecks in electron crystallography is the collection of image data to directly provide experimental phases to high resolution. Here, we describe an approach to bypass this bottleneck, eliminating the need for high-resolution imaging. We use the strengths of electron crystallography in rapidly obtaining accurate experimental phase information from low-resolution images and accurate high-resolution amplitude information from electron diffraction. The low-resolution experimental phases were used for the placement of α helix fragments and extended to high resolution using phases from the fragments. Phases were further improved by density modifications followed by fragment expansion and structure refinement against the high-resolution diffraction data. Using this approach, structures of three membrane proteins were determined rapidly and accurately to atomic resolution without high-resolution image data.     

Facile backbone structure determination of human membrane proteins by NMR spectroscopy

Although nearly half of today's major pharmaceutical drugs target human integral membrane proteins (hIMPs), only 30 hIMP structures are currently available in the Protein Data Bank, largely owing to inefficiencies in protein production. Here we describe a strategy for the rapid structure determination of hIMPs, using solution NMR spectroscopy with systematically labeled proteins produced via cell-free expression. We report new backbone structures of six hIMPs, solved in only 18 months from 15 initial targets. Application of our protocols to an additional 135 hIMPs with molecular weight <30 kDa yielded 38 hIMPs suitable for structural characterization by solution NMR spectroscopy without additional optimization.     

Spherical reconstruction: a method for structure determination of membrane proteins from cryo-EM images

We propose a new method for single-particle reconstruction, which should be generally applicable to structure determination for membrane proteins. After reconstitution into a small spherical vesicle, a membrane protein takes a particular orientation relative to the membrane normal, and its position in the projected image of the vesicle directly defines two of its three Euler angles of orientation. The spherical constraint imposed by the vesicle effectively reduces the dimensionality of the alignment search from 5 to 3 and simplifies the detection of the particle. Projection images of particles in vesicles collectively take all possible orientations and therefore cover the whole Fourier space. Analysis of images of vesicles in ice showed that the vesicle density is well described by a simple model for membrane electron scattering density. In fitting this model we found that osmotically swollen vesicles remain nearly spherical through the freezing process. These results satisfy the basic experimental requirements for spherical reconstruction. A computer simulation of particles in vesicles showed that this method provides good estimates of the two Euler angles and thus may improve single-particle reconstruction and extend it to smaller membrane proteins.     

An all-atom force field for tertiary structure prediction of helical proteins

We have developed an all-atom free-energy force field (PFF01) for protein tertiary structure prediction. PFF01 is based on physical interactions and was parameterized using experimental structures of a family of proteins believed to span a wide variety of possible folds. It contains empirical, although sequence-independent terms for hydrogen bonding. Its solvent-accessible surface area solvent model was first fit to transfer energies of small peptides. The parameters of the solvent model were then further optimized to stabilize the native structure of a single protein, the autonomously folding villin headpiece, against competing low-energy decoys. Here we validate the force field for five nonhomologous helical proteins with 20-60 amino acids. For each protein, decoys with 2-3 A backbone root mean-square deviation and correct experimental Cbeta-Cbeta distance constraints emerge as those with the lowest energy.     

Recollections of the electron crystallographic heavy atom derivative search of purple membrane: the quest for EM structure determination.

The use of multiple isomorphous replacement in protein electron crystallography for phase determination has been systematically studied only for purple membrane, even though the use of heavy atoms or heavy atom clusters has been used on many occasions in electron microscopy for locating domains or subunits in protein assemblies. The background behind the structure determination of bacteriorhodopsin, the protein component of purple membranes, is summarized and an evaluation of the strengths and weaknesses of using isomorphous replacement in electron crystallography is discussed.     

Molecular packing and packing defects in helical membrane proteins

The packing of helices spanning lipid bilayers is crucial for the stability and function of alpha-helical membrane proteins. Using a modified Voronoi procedure, we calculated packing densities for helix-helix contacts in membrane spanning domains. Our results show that the transmembrane helices of protein channels and transporters are significantly more loosely packed compared with helices in globular proteins. The observed packing deficiencies of these membrane proteins are also reflected by a higher amount of cavities at functionally important sites. The cavities positioned along the gated pores of membrane channels and transporters are noticeably lined by polar amino acids that should be exposed to the aqueous medium when the protein is in the open state. In contrast, nonpolar amino acids surround the cavities in those protein regions where large rearrangements are supposed to take place, as near the hinge regions of transporters or at restriction sites of protein channels. We presume that the observed deficiencies of helix-helix packing are essential for the helical mobility that sustains the function of many membrane protein channels and transporters.     

Tricks of the trade used to accelerate high-resolution structure determination of membrane proteins

The rate at which X-ray structures of membrane proteins are solved is on a par with that of soluble proteins in the late 1970s. There are still many obstacles facing the membrane protein structural community. Recently, there have been several technical achievements in the field that have started to dramatically accelerate structural studies. Here, we summarize these so-called ‘tricks-of-the-trade’ and include case studies of several mammalian transporters.     

Single-particle reconstruction from EM images of helical filaments

Helical filaments were the first structures to be reconstructed in three dimensions from electron microscopic images, and continue to be extensively studied due to the large number of such helical polymers found in biology. In principle, a single image of a helical polymer provides all of the different projections needed to reconstruct the three-dimensional structure. Unfortunately, many helical filaments have been refractory to the application of traditional (Fourier-Bessel) methods due to variability, heterogeneity, and weak scattering. Over the past several years, many of these problems have been surmounted using single-particle type approaches that can do substantially better than Fourier-Bessel approaches. Applications of these new methods to viruses, actin filaments, pili and many other polymers show the great advantages of the new methods.     

A cost-effective method for simultaneous homo-oligomeric size determination and monodispersity conditions for membrane proteins

The use of blue native polyacrylamide gel electrophoresis (BN-PAGE) has been reported in the literature to retain both water-soluble and membrane protein complexes in their native hetero-oligomeric state and to determine the molecular weight of membrane proteins. However, membrane proteins show abnormal mobility when compared with water-soluble markers. Although one could use membrane proteins as markers or apply a conversion factor to the observed molecular weight to account for the bound Coomassie blue dye, when one just wants to assess homo-oligomeric size, these methods appear to be too time-consuming or might not be generally applicable. Here, during detergent screening studies to identify the best detergent for achieving a monodisperse sample, we observed that under certain conditions membrane proteins tend to form ladders of increasing oligomeric size. Although the ladders themselves contain no indication of which band represents the correct oligomeric size, they provide a scale that can be compared with a single band, representing the native homo-oligomeric size, obtained in other conditions of the screen. We show that this approach works for three membrane proteins: CorA (42 kDa), aquaporin Z (25 kDa), and small hydrophobic (SH) protein from respiratory syncytial virus (8 kDa). In addition, polydispersity results and identification of the most suitable detergent correlate optimally not only with size exclusion chromatography (SEC) but also with results from sedimentation velocity and equilibrium experiments. Because it involves minute quantities of sample and detergent, this method can be used in high-throughput approaches as a low-cost technique.     

Study and prediction of secondary structure for membrane proteins

In this paper we present a novel approach to membrane protein secondary structure prediction based on the statistical stepwise discriminant analysis method. A new aspect of our approach is the possibility to derive physical-chemical properties that may affect the formation of membrane protein secondary structure. The certain physical-chemical properties of protein chains can be used to clarify the formation of the secondary structure types under consideration. Another aspect of our approach is that the results of multiple sequence alignment, or the other kinds of sequence alignment, are not used in the frame of the method. Using our approach, we predicted the formation of three main secondary structure types (alpha-helix, beta-structure and coil) with high accuracy, that is Q(3) = 76%. Predicting the formation of alpha-helix and non-alpha-helix states we reached the accuracy which was measured as Q(2) = 86%. Also we have identified certain protein chain properties that affect the formation of membrane protein secondary structure. These protein properties include hydrophobic properties of amino acid residues, presence of Gly, Ala and Val amino acids, and the location of protein chain end.     

A new strategy for structure determination of large proteins in solution without deuteration

So far high-resolution structure determination by nuclear magnetic resonance (NMR) spectroscopy has been limited to proteins <30 kDa, although global fold determination is possible for substantially larger proteins. Here we present a strategy for assigning backbone and side-chain resonances of large proteins without deuteration, with which one can obtain high-resolution structures from (1)H-(1)H distance restraints. The strategy uses information from through-bond correlation experiments to filter intraresidue and sequential correlations from through-space correlation experiments, and then matches the filtered correlations to obtain sequential assignment. We demonstrate this strategy on three proteins ranging from 24 to 65 kDa for resonance assignment and on maltose binding protein (42 kDa) and hemoglobin (65 kDa) for high-resolution structure determination. The strategy extends the size limit for structure determination by NMR spectroscopy to 42 kDa for monomeric proteins and to 65 kDa for differentially labeled multimeric proteins without the need for deuteration or selective labeling.     

A computer-based protocol for semiautomated assignments and 3D structure determination of proteins

Summary A strategy is presented for the semiautomated assignment and 3D structure determination of proteins from heteronuclear multidimensional Nuclear Magnetic Resonance (NMR) data. This approach involves the computer-based assignment of the NMR signals, identification of distance restraints from nuclear Overhauser effects, and generation of 3D structures by using the NMR-derived restraints. The protocol is described in detail and illustrated on a resonance assignment and structure determination of the FK506 binding protein (FKBP, 107 amino acids) complexed to the immunosuppressant, ascomycin. The 3D structures produced from this automated protocol attained backbone and heavy atom rmsd of 1.17 and 1.69 Å, respectively. Although more highly resolved structures of the complex have been obtained by standard interpretation of NMR data (Meadows et al. (1993) Biochemistry, 32, 754–765), the structures generated with this automated protocol required minimal manual intervention during the spectral assignment and 3D structure calculations stages. Thus, the protocol may yield an approximate order of magnitude reduction in the time required for the generation of 3D structures of proteins from NMR data.     

Prediction of the burial status of transmembrane residues of helical membrane proteins

Background  

Helical membrane proteins (HMPs) play a crucial role in diverse cellular processes, yet it still remains extremely difficult to determine their structures by experimental techniques. Given this situation, it is highly desirable to develop sequence-based computational methods for predicting structural characteristics of HMPs.     

On the derivation of propensity scales for predicting exposed transmembrane residues of helical membrane proteins

Helical membrane proteins (HMPs) play a crucial role in diverse physiological processes. Given the difficulty in determining their structures by experimental techniques, it is desired to develop computational methods for predicting the burial status of transmembrane residues. Deriving a propensity scale for the 20 amino acids to be exposed to the lipid bilayer from known structures is central to developing such methods. A fundamental problem in this regard is what would be the optimal way of deriving propensity scales. Here, we show that this problem can be reformulated such that an optimal scale is straightforwardly obtained in an analytical fashion. The derived scale favorably compares with others in terms of both algorithmic optimality and practical prediction accuracy. It also allows interesting insights into the structural organization of HMPs. Furthermore, the presented approach can be applied to other bioinformatics problems of HMPs, too. All the data sets and programs used in the study and detailed primary results are available upon request.     

Comprehensive evaluation of solution nuclear magnetic resonance spectroscopy sample preparation for helical integral membrane proteins

The preparation of high quality samples is a critical challenge for the structural characterization of helical integral membrane proteins. Solving the structures of this diverse class of proteins by solution nuclear magnetic resonance spectroscopy (NMR) requires that well-resolved 2D ¹H/¹⁵N chemical shift correlation spectra be obtained. Acquiring these spectra demands the production of samples with high levels of purity and excellent homogeneity throughout the sample. In addition, high yields of isotopically enriched protein and efficient purification protocols are required. We describe two robust sample preparation methods for preparing high quality, homogeneous samples of helical integral membrane proteins. These sample preparation protocols have been combined with screens for detergents and sample conditions leading to the efficient production of samples suitable for solution NMR spectroscopy. We have examined 18 helical integral membrane proteins, ranging in size from approximately 9 kDa to 29 kDa with 1–4 transmembrane helices, originating from a number of bacterial and viral genomes. 2D ¹H/¹⁵N chemical shift correlation spectra acquired for each protein demonstrate well-resolved resonances, and >90% detection of the predicted resonances. These results indicate that with proper sample preparation, high quality solution NMR spectra of helical integral membrane proteins can be obtained greatly enhancing the probability for structural characterization of these important proteins.     

Automation of NMR structure determination of proteins

The automation of protein structure determination using NMR is coming of age. The tedious processes of resonance assignment, followed by assignment of NOE (nuclear Overhauser enhancement) interactions (now intertwined with structure calculation), assembly of input files for structure calculation, intermediate analyses of incorrect assignments and bad input data, and finally structure validation are all being automated with sophisticated software tools. The robustness of the different approaches continues to deal with problems of completeness and uniqueness; nevertheless, the future is very bright for automation of NMR structure generation to approach the levels found in X-ray crystallography. Currently, near completely automated structure determination is possible for small proteins, and the prospect for medium-sized and large proteins is good.