TMM@: a web application for the analysis of transmembrane helix mobility.
ABSTRACT: BACKGROUND: To understand the mechanism by which a protein transmits a signal through the cell membrane, an understanding of the flexibility of its transmembrane (TM) region is essential. Normal Mode Analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. It has been widely used to study transmembrane channels and pumps. It relies on the hypothesis that the vibrational normal modes having the lowest frequencies (also named soft modes) describe the largest movements in a protein and are the ones that are functionally relevant. In particular NMA can be used to study dynamics of TM regions, but no tool making this approach available for non-experts, has been available so far. RESULTS: We developed the web-application TMM@ (TransMembrane alpha-helical Mobility analyzer). It uses NMA to characterize the propensity of transmembrane alpha-helices to be displaced. Starting from a structure file at the PDB format, the server computes the normal modes of the protein and identifies which helices in the bundle are the most mobile. Each analysis is performed independently from the others and results can be visualized using only a web browser. No additional plug-in or software is required. For users who would like to further analyze the output data with their favourite software, raw results can also be downloaded. CONCLUSION: We built a novel and unique tool, TMM@, to study the mobility of transmembrane alpha-helices. The tool can be applied to for example membrane transporters and provides biologists studying transmembrane proteins with an approach to investigate which alpha-helices are likely to undergo the largest displacements, and hence which helices are most likely to be involved in the transportation of molecules in and out of the cell.
Project description:Dimerization of transmembrane (TM) ? helices of membrane receptors plays a key role in signaling. We show that molecular dynamics simulations yield models of integrin TM helix heterodimers, which agree well with available NMR structures. We use a multiscale simulation approach, combining coarse-grained and subsequent atomistic simulation, to model the dimerization of wild-type (WT) and mutated sequences of the ?IIb and ?3 integrin TM helices. The WT helices formed a stable, right-handed dimer with the same helix-helix interface as in the published NMR structure (PDB: 2K9J). In contrast, the presence of disruptive mutations perturbed the interface between the helices, altering the conformational stability of the dimer. The ?IIb/?3 interface was more flexible than that of, e.g., glycophorin A. This is suggestive of a role for alternative packing modes of the TM helices in transbilayer signaling.
Project description:α-helices are deformable secondary structural components regularly observed in protein folds. The overall flexibility of an α-helix can be resolved into constituent physical deformations such as bending in two orthogonal planes and twisting along the principal axis. We used Principal Component Analysis to identify and quantify the contribution of each of these dominant deformation modes in transmembrane α-helices, extramembrane α-helices, and α-helices in soluble proteins. Using three α-helical samples from Protein Data Bank entries spanning these three cellular contexts, we determined that the relative contributions of these modes towards total deformation are independent of the α-helix's surroundings. This conclusion is supported by the observation that the identities of the top three deformation modes, the scaling behaviours of mode eigenvalues as a function of α-helix length, and the percentage contribution of individual modes on total variance were comparable across all three α-helical samples. These findings highlight that α-helical deformations are independent of cellular location and will prove to be valuable in furthering the development of flexible templates in de novo protein design.
Project description:Large-conductance voltage- and calcium-activated potassium (BK) channels contain four pore-forming alpha subunits and four modulatory beta subunits. From the extents of disulfide cross-linking in channels on the cell surface between cysteine (Cys) substituted for residues in the first turns in the membrane of the S0 transmembrane (TM) helix, unique to BK alpha, and of the voltage-sensing domain TM helices S1-S4, we infer that S0 is next to S3 and S4, but not to S1 and S2. Furthermore, of the two beta1 TM helices, TM2 is next to S0, and TM1 is next to TM2. Coexpression of alpha with two substituted Cys's, one in S0 and one in S2, and beta1 also with two substituted Cys's, one in TM1 and one in TM2, resulted in two alphas cross-linked by one beta. Thus, each beta lies between and can interact with the voltage-sensing domains of two adjacent alpha subunits.
Project description:BACKGROUND:Alpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are also prime drug targets, and it has been estimated that more than half of all drugs currently on the market target membrane proteins. However, due to the experimental difficulties involved in obtaining high quality crystals, this class of protein is severely under-represented in structural databases. In the absence of structural data, sequence-based prediction methods allow TM protein topology to be investigated. RESULTS:We present a support vector machine-based (SVM) TM protein topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of 131 sequences with known crystal structures. The method achieves topology prediction accuracy of 89%, while signal peptides and re-entrant helices are predicted with 93% and 44% accuracy respectively. An additional SVM trained to discriminate between globular and TM proteins detected zero false positives, with a low false negative rate of 0.4%. We present the results of applying these tools to a number of complete genomes. Source code, data sets and a web server are freely available from http://bioinf.cs.ucl.ac.uk/psipred/. CONCLUSION:The high accuracy of TM topology prediction which includes detection of both signal peptides and re-entrant helices, combined with the ability to effectively discriminate between TM and globular proteins, make this method ideally suited to whole genome annotation of alpha-helical transmembrane proteins.
Project description:In the past 5 years, RNA-Seq has become a powerful tool in transcriptome analysis even though computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. It is, however, now commonly accepted that the choice of a normalization procedure is an important step in such a process, for example in differential gene expression analysis. The present article highlights the similarities between three normalization methods: TMM from edgeR R package, RLE from DESeq2 R package, and MRN. Both TMM and DESeq2 are widely used for differential gene expression analysis. This paper introduces properties that show when these three methods will give exactly the same results. These properties are proven mathematically and illustrated by performing <i>in silico</i> calculations on a given RNA-Seq data set.
Project description:Large-conductance, voltage- and Ca(2+)-gated potassium (BK) channels control excitability in a number of cell types. BK channels are composed of alpha subunits, which contain the voltage-sensor domains and the Ca(2+)- sensor domains and form the pore, and often one of four types of beta subunits, which modulate the channel in a cell-specific manner. beta 4 is expressed in neurons throughout the brain. Deletion of beta 4 in mice causes temporal lobe epilepsy. Compared with channels composed of alpha alone, channels composed of alpha and beta 4 activate and deactivate more slowly. We inferred the locations of the two beta 4 transmembrane (TM) helices TM1 and TM2 relative to the seven alpha TM helices, S0-S6, from the extent of disulfide bond formation between cysteines substituted in the extracellular flanks of these TM helices. We found that beta 4 TM2 is close to alpha S0 and that beta 4 TM1 is close to both alpha S1 and S2. At least at their extracellular ends, TM1 and TM2 are not close to S3-S6. In six of eight of the most highly crosslinked cysteine pairs, four crosslinks from TM2 to S0 and one each from TM1 to S1 and S2 had small effects on the V(50) and on the rates of activation and deactivation. That disulfide crosslinking caused only small functional perturbations is consistent with the proximity of the extracellular ends of TM2 to S0 and of TM1 to S1 and to S2, in both the open and closed states.
Project description:G-protein-coupled receptors (GPCRs) respond to external stimuli by activating heterotrimeric G proteins inside the cell. There is increasing evidence that many GPCRs exist as dimers or higher oligomers, but the biochemical nature of such dimers and what roles they have, if any, in signal transduction remains unclear. We conducted a comprehensive study of dimerization of the 5HT2c serotonin receptor using disulphide-trapping experiments. We found a dimer interface between transmembrane (TM) helices IV and V that is markedly sensitive to the state of receptor activation. This dimer seems to be quasisymmetrical in interfacial geometry and asymmetrical in its association with its cognate G alpha protein. We also found a second interface at TM I helices, which is insensitive to the state of activation.
Project description:The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of alpha-helices and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained molecular dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helices during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helices. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 x 5 micros) were used to study the tetramerization of inserted M2 helices. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This analysis reveals that the M2 tetramer has 2x rotationally symmetrical packing of the helices. The helices form a left-handed bundle, with a helix tilt angle of approximately 16 degrees. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundle's stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.
Project description:?-helical transmembrane (TM) proteins play an important role in many critical and diverse biological processes, and specific associations between TM helices are important determinants for membrane protein folding, dynamics and function. In order to gain insights into the above phenomena, it is necessary to investigate different types of helix-packing modes and interactions. However, such information is difficult to obtain because of the experimental impediment and a lack of a well-annotated source of helix-packing folds in TM proteins. We have developed the TMPad (TransMembrane Protein Helix-Packing Database) which addresses the above issues by integrating experimentally observed helix-helix interactions and related structural information of membrane proteins. Specifically, the TMPad offers pre-calculated geometric descriptors at the helix-packing interface including residue backbone/side-chain contacts, interhelical distances and crossing angles, helical translational shifts and rotational angles. The TMPad also includes the corresponding sequence, topology, lipid accessibility, ligand-binding information and supports structural classification, schematic diagrams and visualization of the above structural features of TM helix-packing. Through detailed annotations and visualizations of helix-packing, this online resource can serve as an information gateway for deciphering the relationship between helix-helix interactions and higher levels of organization in TM protein structure and function. The website of the TMPad is freely accessible to the public at http://bio-cluster.iis.sinica.edu.tw/TMPad.
Project description:Loops connecting the transmembrane (TM) alpha-helices in membrane proteins are expected to affect the structural organization of the thereby connected helices and the helical bundles as a whole. This effect, which has been largely ignored previously, is studied here by analyzing the x-ray structures of 41 alpha-helical membrane proteins. First we define the loop flexibility ratio, R, and find that 53% of the loops are stretched, where a stretched loop constrains the distance between the two connected helices. The significance of this constraining effect is supported by experiments carried out with bacteriorhodopsin and rhodopsin, in which cutting or eliminating their (predominately stretched) loops has led to a decrease in protein stability, and for rhodopsin, in most cases, also to the destruction of the structure. We show that for nonstretched loops in the extramembranous regions, the fraction of hydrophobic residues is comparable to that for soluble proteins; furthermore (as is also the case for soluble proteins), the hydrophobic residues in these regions are preferentially buried. This is expected to lead to the compact structural organization of the loops, which is transferred to the TM helices, causing them to assemble. We argue that a soluble protein complexed with a membrane protein similarly promotes compactness; other properties of such complexes are also studied. We calculate complementary attractive interactions between helices, including hydrogen bonds and van der Waals interactions of sequential motifs, such as GXXXG. The relative and combined effects of all these factors on the association of the TM helices are discussed and protein structures with only a few of these factors are analyzed. Our study emphasizes the need for classifying membrane proteins into groups according to structural organization. This classification should be considered when procedures for structural analysis or prediction are developed and applied. Detailed analysis of each structure is provided at http://flan.blm.cs.cmu.edu/memloop/