BCL::Fold—Protein topology determination from limited NMR restraints

When experimental protein NMR data are too sparse to apply traditional structure determination techniques, de novo protein structure prediction methods can be leveraged. Here, we describe the incorporation of NMR restraints into the protein structure prediction algorithm BCL::Fold. The method assembles discreet secondary structure elements using a Monte Carlo sampling algorithm with a consensus knowledge‐based energy function. New components were introduced into the energy function to accommodate chemical shift, nuclear Overhauser effect, and residual dipolar coupling data. In particular, since side chains are not explicitly modeled during the minimization process, a knowledge based potential was created to relate experimental side chain proton–proton distances to C_β–C_β distances. In a benchmark test of 67 proteins of known structure with the incorporation of sparse NMR restraints, the correct topology was sampled in 65 cases, with an average best model RMSD100 of 3.4 ± 1.3 Å versus 6.0 ± 2.0 Å produced with the de novo method. Additionally, the correct topology is present in the best scoring 1% of models in 61 cases. The benchmark set includes both soluble and membrane proteins with up to 565 residues, indicating the method is robust and applicable to large and membrane proteins that are less likely to produce rich NMR datasets. Proteins 2014; 82:587–595. © 2013 Wiley Periodicals, Inc.     

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1–2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug‐specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans‐membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α‐helical MPs as well as β‐barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge‐based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. Proteins 2015; 83:1–24. © 2014 Wiley Periodicals, Inc.     

Identification and removal of nitroxide spin label contaminant: impact on PRE studies of α-helical membrane proteins in detergent

NMR paramagnetic relaxation enhancement (PRE) provides long‐range distance constraints (～15–25 Å) that can be critical to determining overall protein topology, especially where long‐range NOE information is unavailable such as in the case of larger proteins that require deuteration. However, several challenges currently limit the use of NMR PRE for α‐helical membrane proteins. One challenge is the nonspecific association of the nitroxide spin label to the protein‐detergent complex that can result in spurious PRE derived distance restraints. The effect of the nitroxide spin label contaminant is evaluated and quantified and a robust method for the removal of the contaminant is provided to advance the application of PRE restraints to membrane protein NMR structure determination.     

BCL::SAXS: GPU accelerated Debye method for computation of small angle X‐ray scattering profiles

Small angle X‐ray scattering (SAXS) is an experimental technique used for structural characterization of macromolecules in solution. Here, we introduce BCL::SAXS—an algorithm designed to replicate SAXS profiles from rigid protein models at different levels of detail. We first show our derivation of BCL::SAXS and compare our results with the experimental scattering profile of hen egg white lysozyme. Using this protein we show how to generate SAXS profiles representing: (1) complete models, (2) models with approximated side chain coordinates, and (3) models with approximated side chain and loop region coordinates. We evaluated the ability of SAXS profiles to identify a correct protein topology from a non‐redundant benchmark set of proteins. We find that complete SAXS profiles can be used to identify the correct protein by receiver operating characteristic (ROC) analysis with an area under the curve (AUC) > 99%. We show how our approximation of loop coordinates between secondary structure elements improves protein recognition by SAχS for protein models without loop regions and side chains. Agreement with SAXS data is a necessary but not sufficient condition for structure determination. We conclude that experimental SAXS data can be used as a filter to exclude protein models with large structural differences from the native. Proteins 2015; 83:1500–1512. © 2015 Wiley Periodicals, Inc.     

Human α‐amino‐β‐carboxymuconate‐ε‐semialdehyde decarboxylase (ACMSD): A structural and mechanistic unveiling

Human α‐amino‐β‐carboxymuconate‐ε‐semialdehyde decarboxylase determines the fate of tryptophan metabolites in the kynurenine pathway by controlling the quinolinate levels for de novo nicotinamide adenine dinucleotide biosynthesis. The unstable nature of its substrate has made gaining insight into its reaction mechanism difficult. Our electron paramagnetic resonance (EPR) spectroscopic study on the Cu‐substituted human enzyme suggests that the native substrate does not directly ligate to the metal ion. Substrate binding did not result in a change of either the hyperfine structure or the super‐hyperfine structure of the EPR spectrum. We also determined the crystal structure of the human enzyme in its native catalytically active state (at 1.99 Å resolution), a substrate analogue‐bound form (2.50 Å resolution), and a selected active site mutant form with one of the putative substrate binding residues altered (2.32 Å resolution). These structures illustrate that each asymmetric unit contains three pairs of dimers. Consistent with the EPR findings, the ligand‐bound complex structure shows that the substrate analogue does not directly coordinate to the metal ion but is bound to the active site by two arginine residues through noncovalent interactions. Proteins 2015; 83:178–187. © 2014 Wiley Periodicals, Inc.     

Backbone structure of a small helical integral membrane protein: A unique structural characterization

The structural characterization of small integral membrane proteins pose a significant challenge for structural biology because of the multitude of molecular interactions between the protein and its heterogeneous environment. Here, the three‐dimensional backbone structure of Rv1761c from Mycobacterium tuberculosis has been characterized using solution NMR spectroscopy and dodecylphosphocholine (DPC) micelles as a membrane mimetic environment. This 127 residue single transmembrane helix protein has a significant (10 kDa) C‐terminal extramembranous domain. Five hundred and ninety distance, backbone dihedral, and orientational restraints were employed resulting in a 1.16 Å rmsd backbone structure with a transmembrane domain defined at 0.40 Å. The structure determination approach utilized residual dipolar coupling orientation data from partially aligned samples, long‐range paramagnetic relaxation enhancement derived distances, and dihedral restraints from chemical shift indices to determine the global fold. This structural model of Rv1761c displays some influences by the membrane mimetic illustrating that the structure of these membrane proteins is dictated by a combination of the amino acid sequence and the protein's environment. These results demonstrate both the efficacy of the structural approach and the necessity to consider the biophysical properties of membrane mimetics when interpreting structural data of integral membrane proteins and, in particular, small integral membrane proteins.     

Protein Topology Prediction Algorithms Systematically Investigated in the Yeast Saccharomyces cerevisiae

Membrane proteins perform a variety of functions, all crucially dependent on their orientation in the membrane. However, neither the exact number of transmembrane domains (TMDs) nor the topology of most proteins have been experimentally determined. Due to this, most scientists rely primarily on prediction algorithms to determine topology and TMD assignments. Since these can give contradictory results, single‐algorithm‐based predictions are unreliable. To map the extent of potential misanalysis, the predictions of nine algorithms on the yeast proteome are compared and it is found that they have little agreement when predicting TMD number and termini orientation. To view all predictions in parallel, a webpage called TopologYeast: http://www.weizmann.ac.il/molgen/TopologYeast was created. Each algorithm is compared with experimental data and a poor agreement is found. The analysis suggests that more systematic data on protein topology are required to increase the training sets for prediction algorithms and to have accurate knowledge of membrane protein topology.     

Determination of structural topology of a membrane protein in lipid bilayers using polarization optimized experiments (POE) for static and MAS solid state NMR spectroscopy

The low sensitivity inherent to both the static and magic angle spinning techniques of solid-state NMR (ssNMR) spectroscopy has thus far limited the routine application of multidimensional experiments to determine the structure of membrane proteins in lipid bilayers. Here, we demonstrate the advantage of using a recently developed class of experiments, polarization optimized experiments, for both static and MAS spectroscopy to achieve higher sensitivity and substantial time-savings for 2D and 3D experiments. We used sarcolipin, a single pass membrane protein, reconstituted in oriented bicelles (for oriented ssNMR) and multilamellar vesicles (for MAS ssNMR) as a benchmark. The restraints derived by these experiments are then combined into a hybrid energy function to allow simultaneous determination of structure and topology. The resulting structural ensemble converged to a helical conformation with a backbone RMSD ~0.44 Å, a tilt angle of 24° ± 1°, and an azimuthal angle of 55° ± 6°. This work represents a crucial first step toward obtaining high-resolution structures of large membrane proteins using combined multidimensional oriented solid-state NMR and magic angle spinning solid-state NMR.     

Ensemble models of proteins and protein domains based on distance distribution restraints

Conformational ensembles of intrinsically disordered peptide chains are not fully determined by experimental observations. Uncertainty due to lack of experimental restraints and due to intrinsic disorder can be distinguished if distance distributions restraints are available. Such restraints can be obtained from pulsed dipolar electron paramagnetic resonance (EPR) spectroscopy applied to pairs of spin labels. Here, we introduce a Monte Carlo approach for generating conformational ensembles that are consistent with a set of distance distribution restraints, backbone dihedral angle statistics in known protein structures, and optionally, secondary structure propensities or membrane immersion depths. The approach is tested with simulated restraints for a terminal and an internal loop and for a protein with 69 residues by using sets of sparse restraints for underlying well‐defined conformations and for published ensembles of a premolten globule‐like and a coil‐like intrinsically disordered protein. Proteins 2016; 84:544–560. © 2016 Wiley Periodicals, Inc.     

Use of random forest in FTIR analysis of LDL cholesterol and tri‐glycerides for hyperlipidemia

A quantitative determination method for the diagnosis of hyperlipidemia was developed using Fourier transform infrared (FTIR) spectroscopy. Random forest (RF) was demonstrated as a potential multivariate algorithm for the FTIR analysis of low‐density lipoprotein cholesterol (LDL‐C) and tri‐glycerides (TG) in human serum samples. The informative wavebands for LDL‐C and TG were selected based on the Gini importance. The selected wavebands were mainly within the fingerprint region. The RF modeling results were better than those derived using PLS in validation process, because the chance for over‐fitting was possibly eliminated in RF algorithm. ARF also demonstrated favorable results in the test process. The prospective model exhibited a higher than 90% true prediction in negative/positive properties for male and female samples. These clinical statistical results indicated the optimization of RF algorithm performed accurately in the FTIR determination of LDL‐C and TG. RF is evaluated as a promising tool for diagnosing and controlling hyperlipidemia in populations. The parameter optimization methodology is useful in the improving model accuracy using FTIR spectroscopic technology. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1693–1702, 2015     

Toward the fourth dimension of membrane protein structure: insight into dynamics from spin-labeling EPR spectroscopy

Trapping membrane proteins in the confines of a crystal lattice obscures dynamic modes essential for interconversion between multiple conformations in the functional cycle. Moreover, lattice forces could conspire with detergent solubilization to stabilize a minor conformer in an ensemble thus confounding mechanistic interpretation. Spin labeling in conjunction with electron paramagnetic resonance (EPR) spectroscopy offers an exquisite window into membrane protein dynamics in the native-like environment of a lipid bilayer. Systematic application of spin labeling and EPR identifies sequence-specific secondary structures, defines their topology and their packing in the tertiary fold. Long range distance measurements (60 ?-80 ?) between pairs of spin labels enable quantitative analysis of equilibrium dynamics and triggered conformational changes. This review highlights the contribution of spin labeling to bridging structure and mechanism. Efforts to develop methods for determining structures from EPR restraints and to increase sensitivity and throughput promise to expand spin labeling applications in membrane protein structural biology.     

Identifying the Tertiary Fold of Small Proteins with Different Topologies from Sequence and Secondary Structure using the Genetic Algorithm and Extended Criteria Specific for Strand Regions

Grid-free protein folding simulations based on sequence and secondary structure knowledge (using mostly experimentally determined secondary structure information but also analysing results from secondary structure predictions) were investigated using the genetic algorithm, a backbone representation, and standard dihedral angular conformations. Optimal structures are selected according to basic protein building principles. Having previously applied this approach to proteins with helical topology, we have now developed additional criteria and weights for β-strand- containing proteins, validated them on four small β-strand-rich proteins with different topologies, and tested the general performance of the method on many further examples from known protein structures with mixed secondary structural type and less than 100 amino acid residues.Topology predictions close to the observed experimental structures were obtained in four test cases together with fitness values that correlated with the similarity of the predicted topology to the observed structures. Root-mean-square deviation values of C^αatoms in the superposed predicted and observed structures, the latter of which had different topologies, were between 4.5 and 5.5 Å (2.9 to 5.1 Å without loops). Including 15 further protein examples with unique folds, root-mean-square deviation values ranged between 1.8 and 6.9 Å with loop regions and averaged 5.3 Å and 4.3 Å, including and excluding loop regions, respectively.     

The membrane-dipped neuronal SNARE complex: a site-directed spin labeling electron paramagnetic resonance study

The formation of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex is an essential process for membrane fusion and the neurotransmitter release in neurons. As an initial step toward the determination of the membrane topology of the SNARE complex, residues at the membrane-water interface were investigated with site-specific spin labeling electron paramagnetic resonance. EPR analysis revealed that the basic amino acid-rich interfacial region, which is universal for all transmembrane SNARE proteins, inserts into the membrane, eliminating the gap between the core complex and the membrane. The result raises the possibility that core complex formation directly leads to the apposition of two membranes, which could facilitate membrane fusion.     

Membrane protein shaving with thermolysin can be used to evaluate topology predictors

Topology analysis of membrane proteins can be obtained by enzymatic shaving in combination with MS identification of peptides. Ideally, such analysis could provide quite detailed information about the membrane spanning regions. Here, we examine the ability of some shaving enzymes to provide large‐scale analysis of membrane proteome topologies. To compare different shaving enzymes, we first analyzed the detected peptides from two over‐expressed proteins. Second, we analyzed the peptides from non‐over‐expressed Escherichia coli membrane proteins with known structure to evaluate the shaving methods. Finally, the identified peptides were used to test the accuracy of a number of topology predictors. At the end we suggest that the usage of thermolysin, an enzyme working at the natural pH of the cell for membrane shaving, is superior because: (i) we detect a similar number of peptides and proteins using thermolysin and trypsin; (ii) thermolysin shaving can be run at a natural pH and (iii) the incubation time is quite short. (iv) Fewer detected peptides from thermolysin shaving originate from the transmembrane regions. Using thermolysin shaving we can also provide a clear separation between the best and the less accurate topology predictors, indicating that using data from shaving can provide valuable information when developing new topology predictors.     

电子顺磁共振技术在细胞膜研究中的应用

电子顺磁共振(EPR)技术具有高灵敏度、高分辨率的特性,通过自旋标记方法,可以用来研究膜蛋白质拓扑学、膜蛋白间相互作用、膜蛋白与磷脂膜相互作用过程中膜蛋白的结构变化以及细胞膜的流动性。在膜脂和膜蛋白的细胞生物学研究中具有广阔的应用前景。现对EPR技术在细胞膜研究中的应用进展做一综述。     

Disruption of LptA oligomerization and affinity of the LptA–LptC interaction

The lipopolysaccharide (LPS)‐rich outer membrane (OM) is a unique feature of Gram‐negative bacteria, and LPS transport across the inner membrane (IM) and through the periplasm is essential to the biogenesis and maintenance of the OM. LPS is transported across the periplasm to the outer leaflet of the OM by the LPS transport (Lpt) system, which in Escherichia coli is comprised of seven recently identified proteins, including LptA, LptC, LptDE, and LptFGB₂. Structures of the periplasmic protein LptA and the soluble portion of the membrane‐associated protein LptC have been solved and show these two proteins to be highly structurally homologous with unique folds. LptA has been shown to form concentration dependent oligomers that stack end‐to‐end. LptA and LptC have been shown to associate in vivo and are expected to form a similar protein–protein interface to that found in the LptA dimer. In these studies, we disrupted LptA oligomerization by introducing two point mutations that removed a lysine and glutamine side chain from the C‐terminal β‐strand of LptA. This loss of oligomerization was characterized using EPR spectroscopy techniques and the affinity of the interaction between the mutant LptA protein and WT LptC was determined using EPR spectroscopy (K_d = 15 µM) and isothermal titration calorimetry (K_d = 14 µM). K_d values were also measured by EPR spectroscopy for the interaction between LptC and WT LptA (4 µM) and for WT LptA oligomerization (29 µM). These data suggest that the affinity between LptA and LptC is stronger than the affinity for LptA oligomerization.     

Recent developments in membrane-protein structural genomics

Recent work has identified the topology of almost all the inner membrane proteins in Escherichia coli, and advances in nuclear magnetic resonance spectroscopy now allow the determination of α-helical membrane protein structures at high resolution. Together these developments will help overcome the current limitations of high-throughput determination of membrane protein structures.     

Protein-lipid interactions with Fusobacterium nucleatum major outer membrane protein FomA: spin-label EPR and polarized infrared spectroscopy

FomA, the major outer membrane protein of Fusobacterium nucleatum, was expressed and purified in Escherichia coli and reconstituted from detergent in bilayer membranes of phosphatidylcholines with chain lengths from C(12:0) to C(17:0). The conformation and orientation of membrane-incorporated FomA were determined from polarized, attenuated total reflection, infrared (IR) spectroscopy, and lipid-protein interactions with FomA were characterized by using electron paramagnetic resonance (EPR) spectroscopy of spin-labeled lipids. Approximately 190 residues of membranous FomA are estimated to be in a beta-sheet configuration from IR band fitting, which is consistent with a 14-strand transmembrane beta-barrel structure. IR dichroism of FomA indicates that the beta-strands are tilted by approximately 45 degrees relative to the sheet/barrel axis and that the order parameter of the latter displays a discontinuity corresponding to hydrophobic matching with fluid C(13:0) lipid chains. The stoichiometry ( N b = 23 lipids/monomer) of lipid-protein interaction from EPR demonstrates that FomA is not trimeric in membranes of diC(14:0) phosphatidylcholine and is consistent with a monomeric beta-barrel of 14-16 strands. The pronounced selectivity of interaction found with anionic spin-labeled lipids places basic residues of the protein in the vicinity of the polar-apolar membrane interfaces, consistent with current topology models. Comparison with similar data from the 8- to 22-stranded E. coli outer membrane proteins, OmpA, OmpG, and FhuA, supports the above conclusions.     

Fragment‐based modeling of membrane protein loops: Successes,failures, and prospects for the future

Membrane proteins (MPs) have become a major focus in structure prediction, due to their medical importance. There is, however, a lack of fast and reliable methods that specialize in the modeling of MP loops. Often methods designed for soluble proteins (SPs) are applied directly to MPs. In this article, we investigate the validity of such an approach in the realm of fragment‐based methods. We also examined the differences in membrane and soluble protein loops that might affect accuracy. We test our ability to predict soluble and MP loops with the previously published method FREAD. We show that it is possible to predict accurately the structure of MP loops using a database of MP fragments (0.5–1 Å median root‐mean‐square deviation). The presence of homologous proteins in the database helps prediction accuracy. However, even when homologues are removed better results are still achieved using fragments of MPs (0.8–1.6 Å) rather than SPs (1–4 Å) to model MP loops. We find that many fragments of SPs have shapes similar to their MP counterparts but have very different sequences; however, they do not appear to differ in their substitution patterns. Our findings may allow further improvements to fragment‐based loop modeling algorithms for MPs. The current version of our proof‐of‐concept loop modeling protocol produces high‐accuracy loop models for MPs and is available as a web server at http://medeller.info/fread . Proteins 2014; 82:175–186. © 2013 Wiley Periodicals, Inc.     

The effects of membrane filters used in biopharmaceutical processes on the concentration and composition of polysorbate 20

Polysorbate 20 (PS‐20) is often included in the formulation for therapeutic proteins to reduce protein aggregation and surface adsorption. During the production process of therapeutic proteins, various membrane filters are used to filter product pools containing PS‐20. The purpose of this study is to quantify the effects of these membrane filtration processes on the concentration and composition of PS‐20. A quantitative understanding of this process provides the knowledge base for better controlling the consistency of formulation excipients in drug products. PS‐20 solutions (without protein) were filtered through either 0.2 µm sterilizing filters or membrane filters with 30 kDa MWCO. The concentration of PS‐20 was measured by a mixed‐mode chromatography method and a nuclear magnetic resonance spectroscopy (NMR) assay. The composition of PS‐20 was characterized by ¹H‐NMR and a reverse‐phase chromatography method. Non‐specific adsorption of PS‐20 on both the sterilizing filter and 30 kDa MWCO membrane filter was quantified. Composition of PS‐20 was altered after 30 kDa MWCO membrane filtration, possibly because the different interactions between heterogeneous PS‐20 components and the 30 kDa MWCO membrane were not uniform. As a result, the retentate after the 30 kDa MWCO membrane filtration step contains no POE sorbitan and increased amount of POE sorbitan di‐esters and tri‐esters. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:1503–1511, 2013