Transmembrane Helical Proteins Research Articles

Scaling Protein-Water Interactions in the Martini 3 Coarse-Grained Force Field to Simulate Transmembrane Helix Dimers in Different Lipid Environments.

Martini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with the experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the nonbonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or the bilayer structure.

High-throughput strategy for identification of Mycobacterium tuberculosis membrane protein expression conditions using folding reporter GFP

Mycobacterium tuberculosis membrane protein biochemistry and structural biology studies are often hampered by challenges in protein expression and selection for well-expressing protein candidates, suitable for further investigation. Here we present a folding reporter GFP (frGFP) assay, adapted for M. tuberculosis membrane protein screening in Escherichia coli Rosetta 2 (DE3) and Mycobacterium smegmatis mc24517. This method allows protein expression condition screening for multiple protein targets simultaneously by monitoring frGFP fluorescence in growing cells. We discuss the impact of common protein expression conditions on 42 essential M. tuberculosis H37Rv helical transmembrane proteins and establish the grounds for their further analysis. We have found that the basal expression of the lac operon in the T7-promoter expression system generally leads to high recombinant protein yield in M. smegmatis, and we suggest that a screening condition without the inducer is included in routine protein expression tests. In addition to the general observations, we describe conditions allowing high-level expression of more than 25 essential M. tuberculosis membrane proteins, containing 2 to 13 transmembrane helices. We hope that these findings will stimulate M. tuberculosis membrane protein research and aid the efforts in drug development against tuberculosis.

Rhodopsin activation involves an ensemble of conformational substates

G-protein-coupled receptors (GPCRs) are seven transmembrane-helix proteins that participate in transmitting signals across cell membranes to regulate multiple functions of the human body. Rhodopsin is an important prototype for studying class A GPCRs. Here we address aspects of the GPCR activation not available for X-ray crystallography due to cryogenic temperatures and the absence of the membrane environment [1,2]. Our hypothesis was that the activation process involves an allosteric mechanism where a dynamical ensemble of states is affected by protein-membrane interactions [1].

Quantitative trait loci and candidate genes associated with freezing tolerance of winter triticale (\xd7\u2009Triticosecale Wittmack)

Freezing tolerance of triticale is a major trait contributing to its winter hardiness. The identification of genomic regions — quantitative trait loci (QTL) and molecular markers associated with freezing tolerance in winter hexaploid triticale — was the aim of this study. For that purpose, a new genetic linkage map was developed for the population of 92 doubled haploid lines derived from ‘Hewo’ × ‘Magnat’ F1 hybrid. Those lines, together with parents were subjected to freezing tolerance test three times during two winter seasons. Plants were grown and cold-hardened under natural fall/winter conditions and then subjected to freezing in controlled conditions. Freezing tolerance was assessed as the plants recovery (REC), the electrolyte leakage (EL) from leaves and chlorophyll fluorescence parameters (JIP) after freezing. Three consistent QTL for several fluorescence parameters, electrolyte leakage, and the percentage of the survived plants were identified with composite interval mapping (CIM) and single marker analysis (SMA). The first locus Qfr.hm-7A.1 explained 9% of variation of both electrolyte leakage and plants recovery after freezing. Two QTL explaining up to 12% of variation in plants recovery and shared by selected chlorophyll fluorescence parameters were found on 4R and 5R chromosomes. Finally, main locus Qchl.hm-5A.1 was detected for chlorophyll fluorescence parameters that explained up to 19.6% of phenotypic variation. The co-located QTL on chromosomes 7A.1, 4R and 5R, clearly indicated physiological and genetic relationship of the plant survival after freezing with the ability to maintain optimal photochemical activity of the photosystem II and preservation of the cell membranes integrity. The genes located in silico within the identified QTL include those encoding BTR1-like protein, transmembrane helix proteins like potassium channel, and phosphoric ester hydrolase involved in response to osmotic stress as well as proteins involved in the regulation of the gene expression, chloroplast RNA processing, and pyrimidine salvage pathway. Additionally, our results confirm that the JIP test is a valuable tool to evaluate freezing tolerance of triticale under unstable winter environments.

Biphasic Proton Transport Mechanism for Uncoupling Proteins.

It has been suggested that uncoupling proteins (UCPs) transport protons via interconversion between two conformational states: one in the "cytoplasmic state" and the other in the "matrix state". Matrix and cytoplasmic salt-bridge networks are key controllers of these states. This study proposes a mechanism for proton transport in tetrameric UCP2, with focus on the role of the matrix network. Eleven mutants were prepared to disrupt (K → Q or D → N mutations) or alter (K → D and D → K mutations) the salt-bridges in the matrix network. Proteins were recombinantly expressed in Escherichia coli membrane, reconstituted in model lipid membranes, and their structures and functions were analyzed by gel electrophoresis, circular dichroism spectroscopy, fluorescence assays, as well as molecular dynamics simulations. It is shown that the UCP2 matrix network contains five salt-bridges (rather than the previously reported three), and the matrix network can regulate the proton transport by holding the protein's transmembrane helices in close proximity, limiting the movement of the activator fatty acid(s). A biphasic two-state molecular model is proposed for proton transport in tetrameric (a dimer of stable dimers) UCP2, in which all the monomers are functional, and monomers in each dimer are in the same transport mode. Purine nucleotide (e.g., ATP) can occlude the internal pore of the monomeric units of UCP tetramers via interacting with positive residues at or in the proximity of the matrix network (K38, K141, K239, R88, R185, and R279) and prevent switching between cytoplasmic and matrix states, thus inhibiting the proton transport. This study provides new insights into the mechanism of proton transport and regulation in UCPs.

DEER Analysis of GPCR Conformational Heterogeneity.

G protein-coupled receptors (GPCRs) represent a large class of transmembrane helical proteins which are involved in numerous physiological signaling pathways and therefore represent crucial pharmacological targets. GPCR function and the action of therapeutic molecules are defined by only a few parameters, including receptor basal activity, ligand affinity, intrinsic efficacy and signal bias. These parameters are encoded in characteristic receptor conformations existing in equilibrium and their populations, which are thus of paramount interest for the understanding of receptor (mal-)functions and rational design of improved therapeutics. To this end, the combination of site-directed spin labeling and EPR spectroscopy, in particular double electron–electron resonance (DEER), is exceedingly valuable as it has access to sub-Angstrom spatial resolution and provides a detailed picture of the number and populations of conformations in equilibrium. This review gives an overview of existing DEER studies on GPCRs with a focus on the delineation of structure/function frameworks, highlighting recent developments in data analysis and visualization. We introduce “conformational efficacy” as a parameter to describe ligand-specific shifts in the conformational equilibrium, taking into account the loose coupling between receptor segments observed for different GPCRs using DEER.

Fungal Ice2p Has Remote Homology to SERINCs, Restriction Factors for HIV and Other Viruses

Ice2p is an integral endoplasmic reticulum (ER) membrane protein in budding yeast S. cerevisiae named “ICE” because its deletion reduces inheritance of cortical ER. Ice2p has also been reported to be involved in mobilising neutral lipids from lipid droplets to the ER for phospholipid metabolism. In addition, it has been proposed that Ice2 acts as a tether that links the ER both to lipid droplets and to the plasma membrane, via a long cytoplasmic loop that contains multiple predicted amphipathic helices. We used bioinformatics to study Ice2p. First, regarding its topology, we found that members of the Ice2 family in diverse fungi are predominantly predicted to have ten transmembrane helices, casting doubt on the prediction of eight transmembrane helices for the yeast protein. Applying the dominant topology to Ice2p puts the loop with amphipathic helices is in the lumen of the ER, not the cytoplasm, so unable to tether. Secondly, we looked for homologues of Ice2p using the profile-profile search tool HHpred and supporting results with bespoke PSI-BLAST searches. This identified a strong homology to SERINCs (serine incorporators), ten transmembrane helix proteins found universally in eukaryotes. Since SERINCs are potent restriction factors for HIV and other viruses, study of Ice2p may reveal functions shared with SERINCs, including antiviral (including anti-HIV) restriction mechanisms.

Thermodynamic and kinetic stabilities of transmembrane helix bundles as revealed by single-pair FRET analysis: Effects of the number of membrane-spanning segments and cholesterol

The tertiary structures and conformational dynamics of transmembrane (TM) helical proteins are maintained by the interhelical interaction network in membranes, although it is complicated to analyze the underlying driving forces because the amino acid sequences can involve multiple and various types of interactions. To obtain insights into basal and common effects of the number of membrane-spanning segments and membrane cholesterol, we measured stabilities of helix bundles composed of simple TM helices (AALALAA)3 (1TM) and (AALALAA)3-G5-(AALALAA)3 (2TM). Association–dissociation dynamics for 1TM–1TM, 1TM–2TM, and 2TM–2TM pairs were monitored to compare stabilities of 2-, 3-, and 4-helical bundles, respectively, with single-pair fluorescence resonance energy transfer (sp-FRET) in liposome membranes. Both thermodynamic and kinetic stabilities of the helix bundles increased with a greater number of membrane-spanning segments in POPC. The presence of 30 mol% cholesterol strongly enhanced the formation of 1TM–1TM and 1TM–2TM bundles (~ − 9 kJ mol−1), whereas it only weakly stabilized the 2TM–2TM bundle (~ − 3 kJ mol−1). Fourier transform infrared-polarized attenuated total reflection (ATR-FTIR) spectroscopy revealed an ~30° tilt of the helix axis relative to bilayer normal for the 1TM–2TM pair in the presence of cholesterol, suggesting the formation of a tilted helix bundle to release high lateral pressure at the center of cholesterol-containing membranes. These results demonstrate that the number of membrane-spanning segments affects the stability and structure of the helix bundle, and their cholesterol-dependences. Such information is useful to understand the basics of folding and assembly of multispanning TM proteins.

Peripheral myelin protein 22 preferentially partitions into ordered phase membrane domains

The ordered environment of cholesterol-rich membrane nanodomains is thought to exclude many transmembrane (TM) proteins. Nevertheless, some multispan helical transmembrane proteins have been proposed to partition into these environments. Here, giant plasma membrane vesicles (GPMVs) were employed to quantitatively show that the helical tetraspan peripheral myelin protein 22 (PMP22) exhibits a pronounced preference for, promotes the formation of, and stabilizes ordered membrane domains. Neither S-palmitoylation of PMP22 nor its putative cholesterol binding motifs are required for this preference. In contrast, Charcot-Marie-Tooth disease-causing mutations that disrupt the stability of PMP22 tertiary structure reduce or eliminate this preference in favor of the disordered phase. These studies demonstrate that the ordered phase preference of PMP22 derives from global structural features associated with the folded form of this protein, providing a glimpse at the structural factors that promote raft partitioning for multispan helical membrane proteins.

Membrane Interactions of Cy3 and Cy5 Fluorophores and Their Effects on Membrane-Protein Dynamics

Organic fluorophores, such as Cy3 and Cy5, have been widely used as chemical labels to probe the structure and dynamics of membrane proteins. Although a number of previous studies have reported on the possibility of some of the water-soluble fluorophores to interact with lipid bilayers, detailed fluorophore-lipid interactions and, more importantly, the potential effect of such interactions on the natural dynamics of the labeled membrane proteins have not been well studied. We have performed a large set of all-atom molecular dynamics simulations employing the highly mobile membrane mimetic model to describe spontaneous partitioning of the fluorophores into lipid bilayers with different lipid compositions. Spontaneous membrane partitioning of Cy3 and Cy5 fluorophores captured in these simulations proceeds in two steps. Electrostatic interaction between the fluorophores and the lipid headgroups facilitates the initial, fast membrane association of the fluorophores, followed by slow insertion of hydrophobic moieties into the lipid bilayer core. After the conversion of the resulting membrane-bound systems to full-membrane representations, biased-exchange umbrella sampling simulations are performed for free energy calculations, revealing a higher energy barrier for partitioning into negatively charged (phosphatidylserine or phosphatidylcholine) membranes than purely zwitterionic (phosphatidylcholine or phosphatidylethanolamine) ones. Furthermore, the potential effect of fluorophore-lipid interactions on membrane proteins has been examined by covalently linking Cy5 to single- and multipass transmembrane helical proteins. Equilibrium simulations show strong position-dependent effects of Cy5-tagging on the structure and natural dynamics of membrane proteins. Interactions between the tagged protein and Cy5 were also observed. Our results suggest that fluorophore-lipid interactions can affect the structure and dynamics of membrane proteins to various extents, especially in systems with higher structural flexibility.

TM-ZC: A Deep Learning-Based Predictor for the Z-Coordinate of Residues in α-Helical Transmembrane Proteins

Z-coordinate is an important structural feature of $\alpha $ -helical transmembrane proteins ( $\alpha $ -TMPs), which is defined as the distance from a residue to the center of the biological membrane. Since the $\alpha $ -TMP structures from both experimental solved and computational predicted approaches still cannot cover the requirements in relevant research fields, z-coordinate prediction provides an opportunity to partly descript $\alpha $ -TMP structures based on their sequences, further contributes to function annotation and drug target discovery. For the purpose of improving the prediction accuracy and providing a convenient tool, we proposed a deep learning-based predictor (TM-ZC) for the z-coordinate of residues in $\alpha $ -TMPs. TM-ZC used the one-hot code and the PSSM as input features for a convolutional neural network (CNN) regression model. The experimental results demonstrated that TM-ZC was a powerful predictor, which is simple and fast, and achieved a considerable performance: the average error was 1.958, the percent of prediction error within 3A was 77.461%, and the correlation coefficient (CC) was 0.922. We further discussed the usefulness of TM-ZC predicted z-coordinate and found its high consistency with topology structure and the enhancement of the surface accessibility prediction.

CombLabel: rational design of optimized sequence-specific combinatorial labeling schemes. Application to backbone assignment of membrane proteins with low stability.

Assignment of backbone resonances is a necessary initial step in every protein NMR investigation. Standard assignment procedure is based on the set of 3D triple-resonance (1H-13C-15N) spectra and requires at least several days of experimental measurements. This limits its application to the proteins with low stability. To speed up the assignment procedure, combinatorial selective labeling (CSL) can be used. In this case, sequence-specific information is extracted from 2D spectra measured for several selectively 13C,15N-labeled samples, produced in accordance with a special CSL scheme. Here we review previous applications of the CSL approach and present novel deterministic 'CombLabel' algorithm, which generates CSL schemes minimizing the number of labeled samples and their price and maximizing assignment information that can be obtained for a given protein sequence. Theoretical calculations revealed that CombLabel software outperformed previously proposed stochastic algorithms. Current implementation of CombLabel robustly calculates CSL schemes containing up to six samples, which is sufficient for moderately sized (up to 200 residues) proteins. As a proof of concept, we calculated CSL scheme for the first voltage-sensing domain of human Nav1.4 channel, a 134 residue four helical transmembrane protein having extremely low stability in micellar solution (half-life ~ 24h at 45°C). Application of CSL doubled the extent of backbone resonance assignment, initially obtained by conventional approach. The obtained assignment coverage (~ 50%) is sufficient for ligand screening and mapping of binding interfaces.

A Membrane Burial Potential with H-Bonds and Applications to Curved Membranes and Fast Simulations

We use the statistics of a large and curated training set of transmembrane helical proteins to develop a knowledge-based potential that accounts for the dependence on both the depth of burial of the protein in the membrane and the degree of side-chain exposure. Additionally, the statistical potential includes depth-dependent energies for unsatisfied backbone hydrogen bond donors and acceptors, which are found to be relatively small, ∼2 RT. Our potential accurately places known proteins within the bilayer. The potential is applied to the mechanosensing MscL channel in membranes of varying thickness and curvature, as well as to the prediction of protein structure. The potential is incorporated into our new Upside molecular dynamics algorithm. Notably, we account for the exchange of protein-lipid interactions for protein-protein interactions as helices contact each other, thereby avoiding overestimating the energetics of helix association within the membrane. Simulations of most multimeric complexes find that isolated monomers and the oligomers retain the same orientation in the membrane, suggesting that the assembly of prepositioned monomers presents a viable mechanism of oligomerization.

Corrigendum to "Topography Prediction of Helical Transmembrane Proteins by a New Modification of the Sliding Window Method".

[This corrects the article DOI: 10.1155/2014/921218.].

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

Enhanced synaptotagmin plasticity derived from pairing intrinsic disorder with synaptic vesicle lipids

ABSTRACTSynaptotagmin 1 (Syt 1) is an integral membrane protein responsible for sensing the calcium ion (Ca2+) influx in neurons that triggers synaptic vesicle exocytosis. How Syt 1's intrinsically disordered region (IDR), a ∼60 residue sequence located between the protein's transmembrane helix and two Ca2+-sensing C2 domains, contributes to protein function is not well understood. The same is true of analogous IDRs located in the other synaptotagmin isoforms. Recently, we found that the Syt 1 IDR is structurally responsive to vesicles whose lipid composition mimics that of a synaptic vesicle organelle and that this sensitivity allosterically influences binding and folding behavior of the adjacent C2 domain. We believe these observations may be applicable to the study of other synaptotagmin isoforms and discuss generally how an IDR-membrane interaction could contribute to modulation of C2 domain function.

The Impact of the ‘Austrian’ Mutation of the Amyloid Precursor Protein Transmembrane Helix is Communicated to the Hinge Region

AbstractThe transmembrane helix of the amyloid precursor protein is subject to proteolytic cleavages by γ‐secretase at different sites resulting in Aβ peptides of different length and toxicity. A number of point mutations within this transmembrane helix alter the cleavage pattern thus enhancing production of toxic Aβ peptide species that are at the root of familial Alzheimer's disease. Here, we investigated how one of the most devastating mutations, the ‘Austrian’ mutation T43I, affects this transmembrane helix. Site‐resolved deuterium/hydrogen amide exchange experiments reveal that the mutation destabilizes amide hydrogen bonds in the hinge which connects dimerization and cleavage regions. Weaker intrahelical hydrogen bonds at the hinge may enhance helix bending and thereby affect recognition of the transmembrane substrate by the enzyme and/or presentation of its cleavage sites to the catalytic cleft.

Unconventional molecular replacement approaches for ab initio phasing of transmembrane helical protein targets

Unconventional molecular replacement approaches for ab initio phasing of transmembrane helical protein targets

Mapping the Energy Landscape for Second Stage Folding of a Single Membrane Protein

Membrane proteins are designed to fold and function in a lipid membrane, yet folding experiments within a native membrane environment are challenging to design. Here we show that single molecule forced unfolding experiments can be adapted to study helical membrane protein folding under native-like bicelle conditions. Applying force using magnetic tweezers, we find that a transmembrane helix protein, E. coli rhomboid protease GlpG, unfolds in a highly cooperative manner, largely unraveling as one physical unit in response to mechanical tension above 25 pN. Considerable hysteresis is observed, with refolding occurring only at forces below 5 pN. Characterizing the energy landscape reveals only modest thermodynamic stability (delta G = 6.5 kT) but a large unfolding barrier (21.3 kT) that can maintain the protein in a folded state for long periods of time (t1/2 ∼ 3.5 hrs). The observed energy landscape may have evolved to limit the existence of troublesome partially unfolded states and impart rigidity to the structure.

Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors.

The α-helical transmembrane proteins constitute 25% of the entire human proteome space and are difficult targets in high-resolution wet-lab structural studies, calling for accurate computational predictors. We present a novel sequence-based method called MemBrain-Rasa to predict relative solvent accessibility surface area (rASA) from primary sequences. MemBrain-Rasa features by an ensemble prediction protocol composed of a statistical machine-learning engine, which is trained in the sequential feature space, and a segment template similarity-based engine, which is constructed with solved structures and sequence alignment. We locally constructed a comprehensive database of residue relative solvent accessibility surface area from the solved protein 3D structures in the PDB database. It is searched against for segment templates that are expected to be structurally similar to the query sequence's segments. The segment template-based prediction is then fused with the support vector regression outputs using knowledge rules. Our experiments show that pure machine learning output cannot cover the entire rASA solution space and will have a serious prediction preference problem due to the relatively small size of membrane protein structures that can be used as the training samples. The template-based engine solves this problem very well, resulting in significant improvement of the prediction performance. MemBrain-Rasa achieves a Pearson correlation coefficient of 0.733 and mean absolute error of 13.593 on the benchmark dataset, which are 26.4% and 26.1% better than existing predictors. MemBrain-Rasa represents a new progress in structure modeling of α-helical transmembrane proteins. MemBrain-Rasa is available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/.