Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Model of Environmental Membrane Field for Transmembrane Proteins.

ABSTRACT: The water environment determines the activity of biological processes. The role of such an environment interpreted in the form of an external field expressed by the 3D Gaussian distribution in the fuzzy oil drop model directs the folding process towards the generation of a centrally located hydrophobic core with the simultaneous exposure of polar residues on the surface. In addition to proteins soluble in the water environment, there is a significant group of membrane proteins that act as receptors or channels, including ion channels in particular. The change of the polar (water) environment into a highly hydrophobic (membrane) environment is quite radical, resulting in a different hydrophobicity distribution within the membrane protein. Modification of the notation of the force field expressing the presence of the hydrophobic environment has been proposed in this work. A modified fuzzy oil drop model with its adaptation to membrane proteins was used to interpret the structure of membrane proteins-mechanosensitive channel. The modified model was also used to describe the so-called negative cases-i.e., for water-soluble proteins with a clear distribution consistent with the fuzzy oil drop model.

SUBMITTER: Roterman I

PROVIDER: S-EPMC8036355 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Field model for multistate lateral diffusion of various transmembrane proteins observed in living Dictyostelium cells.

Project description:The lateral diffusion of transmembrane proteins on plasma membranes is a fundamental process for various cellular functions. Diffusion properties specific for individual protein species have been extensively studied, but the common features among protein species are poorly understood. Here, we systematically studied the lateral diffusion of various transmembrane proteins in the lower eukaryote Dictyostelium discoideum cells using a hidden Markov model for single-molecule trajectories obtained experimentally. As common features, all membrane proteins that had from one to ten transmembrane regions adopted three free diffusion states with similar diffusion coefficients regardless of their structural variability. All protein species reduced their mobility similarly upon the inhibition of microtubule or actin cytoskeleton dynamics, or myosin II. The relationship between protein size and the diffusion coefficient was consistent with the Saffman-Delbrück model, meaning that membrane viscosity is a major determinant of lateral diffusion, but protein size is not. These protein species-independent properties of multistate free diffusion were explained simply and quantitatively by free diffusion on the three membrane regions with different viscosities, which is in sharp contrast to the complex diffusion behavior of transmembrane proteins in higher eukaryotes.

| S-EPMC10022678 | biostudies-literature

Transmembrane proteins tetraspanin 4 and CD9 sense membrane curvature.

Project description:Multiple membrane-shaping and remodeling processes are associated with tetraspanin proteins by yet unknown mechanisms. Tetraspanins constitute a family of proteins with four transmembrane domains present in every cell type. Prominent examples are tetraspanin4 and CD9, which are required for the fundamental cellular processes of migrasome formation and fertilization, respectively. These proteins are enriched in curved membrane structures, such as cellular retraction fibers and oocyte microvilli. The factors driving this enrichment are, however, unknown. Here, we revealed that tetraspanin4 and CD9 are curvature sensors with a preference for positive membrane curvature. To this end, we used a biomimetic system emulating membranes of cell retraction fibers and oocyte microvilli by membrane tubes pulled out of giant plasma membrane vesicles with controllable membrane tension and curvature. We developed a simple thermodynamic model for the partitioning of curvature sensors between flat and tubular membranes, which allowed us to estimate the individual intrinsic curvatures of the two proteins. Overall, our findings illuminate the process of migrasome formation and oocyte microvilli shaping and provide insight into the role of tetraspanin proteins in membrane remodeling processes.

| S-EPMC9618112 | biostudies-literature

Prediction of transmembrane helix orientation in polytopic membrane proteins.

Project description:BackgroundMembrane proteins compose up to 30% of coding sequences within genomes. However, their structure determination is lagging behind compared with soluble proteins due to the experimental difficulties. Therefore, it is important to develop reliable computational methods to predict structures of membrane proteins.ResultsWe present a method for prediction of the TM helix orientation, which is an essential step in ab initio modeling of membrane proteins. Our method is based on a canonical model of the heptad repeat originally developed for coiled coils. We identify the helical surface patches that interface with lipid molecules at an accuracy of about 88% from the sequence information alone, using an empirical scoring function LIPS (LIPid-facing Surface), which combines lipophilicity and conservation of residues in the helix. We test and discuss results of prediction of helix-lipid interfaces on 162 transmembrane helices from 18 polytopic membrane proteins and present predicted orientations of TM helices in TRPV1 channel. We also apply our method to two structures of homologous cytochrome b6f complexes and find discrepancy in the assignment of TM helices from subunits PetG, PetN and PetL. The results of LIPS calculations and analysis of packing and H-bonding interactions support the helix assignment found in the cytochrome b6f structure from green alga but not the assignment of TM helices in the cyanobacterium b6f structure.ConclusionLIPS calculations can be used for the prediction of helix orientation in ab initio modeling of polytopic membrane proteins. We also show with the example of two cytochrome b6f structures that our method can identify questionable helix assignments in membrane proteins. The LIPS server is available online at http://gila.bioengr.uic.edu/lab/larisa/lips.html.

| S-EPMC1540425 | biostudies-literature

mCSM-membrane: predicting the effects of mutations on transmembrane proteins.

Project description:Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects of mutations in membrane proteins. To fill this gap, here we report, mCSM-membrane, a user-friendly web server that can be used to analyse the impacts of mutations on membrane protein stability and the likelihood of them being disease associated. mCSM-membrane derives from our well-established mutation modelling approach that uses graph-based signatures to model protein geometry and physicochemical properties for supervised learning. Our stability predictor achieved correlations of up to 0.72 and 0.67 (on cross validation and blind tests, respectively), while our pathogenicity predictor achieved a Matthew's Correlation Coefficient (MCC) of up to 0.77 and 0.73, outperforming previously described methods in both predicting changes in stability and in identifying pathogenic variants. mCSM-membrane will be an invaluable and dedicated resource for investigating the effects of single-point mutations on membrane proteins through a freely available, user friendly web server at http://biosig.unimelb.edu.au/mcsm_membrane.

| S-EPMC7319563 | biostudies-literature

Transmembrane glycine zippers: physiological and pathological roles in membrane proteins.

Project description:We have observed a common sequence motif in membrane proteins, which we call a glycine zipper. Glycine zipper motifs are strongly overrepresented and conserved in membrane protein sequences, and mutations in glycine zipper motifs are deleterious to function in many cases. The glycine zipper has a significant structural impact, engendering a strong driving force for right-handed packing against a neighboring helix. Thus, the presence of a glycine zipper motif leads directly to testable structural hypotheses, particularly for a subclass of glycine zipper proteins that form channels. For example, we suggest that the membrane pores formed by the amyloid-beta peptide in vitro are constructed by glycine zipper packing and find that mutations in the glycine zipper motif block channel formation. Our findings highlight an important structural motif in a wide variety of normal and pathological processes.

| S-EPMC1242278 | biostudies-literature

TMbed: transmembrane proteins predicted through language model embeddings.

Project description:BackgroundDespite the immense importance of transmembrane proteins (TMP) for molecular biology and medicine, experimental 3D structures for TMPs remain about 4-5 times underrepresented compared to non-TMPs. Today's top methods such as AlphaFold2 accurately predict 3D structures for many TMPs, but annotating transmembrane regions remains a limiting step for proteome-wide predictions.ResultsHere, we present TMbed, a novel method inputting embeddings from protein Language Models (pLMs, here ProtT5), to predict for each residue one of four classes: transmembrane helix (TMH), transmembrane strand (TMB), signal peptide, or other. TMbed completes predictions for entire proteomes within hours on a single consumer-grade desktop machine at performance levels similar or better than methods, which are using evolutionary information from multiple sequence alignments (MSAs) of protein families. On the per-protein level, TMbed correctly identified 94 ± 8% of the beta barrel TMPs (53 of 57) and 98 ± 1% of the alpha helical TMPs (557 of 571) in a non-redundant data set, at false positive rates well below 1% (erred on 30 of 5654 non-membrane proteins). On the per-segment level, TMbed correctly placed, on average, 9 of 10 transmembrane segments within five residues of the experimental observation. Our method can handle sequences of up to 4200 residues on standard graphics cards used in desktop PCs (e.g., NVIDIA GeForce RTX 3060).ConclusionsBased on embeddings from pLMs and two novel filters (Gaussian and Viterbi), TMbed predicts alpha helical and beta barrel TMPs at least as accurately as any other method but at lower false positive rates. Given the few false positives and its outstanding speed, TMbed might be ideal to sieve through millions of 3D structures soon to be predicted, e.g., by AlphaFold2.

| S-EPMC9358067 | biostudies-literature

Transmembrane segments of nascent polytopic membrane proteins control cytosol/ER targeting during membrane integration.

Project description:During cotranslational integration of a eukaryotic multispanning polytopic membrane protein (PMP), its hydrophilic loops are alternately directed to opposite sides of the ER membrane. Exposure of fluorescently labeled nascent PMP to the cytosol or ER lumen was detected by collisional quenching of its fluorescence by iodide ions localized in the cytosol or lumen. PMP loop exposure to the cytosol or lumen was controlled by structural rearrangements in the ribosome, translocon, and associated proteins that occurred soon after a nascent chain transmembrane segment (TMS) entered the ribosomal tunnel. Each successive TMS, although varying in length, sequence, hydrophobicity, and orientation, reversed the structural changes elicited by its predecessor, irrespective of loop size. Fluorescence lifetime data revealed that TMSs occupied a more nonpolar environment than secretory proteins inside the aqueous ribosome tunnel, which suggests that TMS recognition by the ribosome involves hydrophobic interactions. Importantly, the TMS-triggered structural rearrangements that cycle nascent chain exposure between cytosolic and lumenal occur without compromising the permeability barrier of the ER membrane.

| S-EPMC3187712 | biostudies-literature

Spontaneous Reconstitution of Functional Transmembrane Proteins During Bioorthogonal Phospholipid Membrane Synthesis.

Project description:Transmembrane proteins are critical for signaling, transport, and metabolism, yet their reconstitution in synthetic membranes is often challenging. Non-enzymatic and chemoselective methods to generate phospholipid membranes in?situ would be powerful tools for the incorporation of membrane proteins. Herein, the spontaneous reconstitution of functional integral membrane proteins during the de?novo synthesis of biomimetic phospholipid bilayers is described. The approach takes advantage of bioorthogonal coupling reactions to generate proteoliposomes from micelle-solubilized proteins. This method was successfully used to reconstitute three different transmembrane proteins into synthetic membranes. This is the first example of the use of non-enzymatic chemical synthesis of phospholipids to prepare proteoliposomes.

| S-EPMC5790194 | biostudies-literature

Transmembrane domain-dependent partitioning of membrane proteins within the endoplasmic reticulum.

Project description:The length and hydrophobicity of the transmembrane domain (TMD) play an important role in the sorting of membrane proteins within the secretory pathway; however, the relative contributions of protein-protein and protein-lipid interactions to this phenomenon are currently not understood. To investigate the mechanism of TMD-dependent sorting, we used the following two C tail-anchored fluorescent proteins (FPs), which differ only in TMD length: FP-17, which is anchored to the endoplasmic reticulum (ER) membrane by 17 uncharged residues, and FP-22, which is driven to the plasma membrane by its 22-residue-long TMD. Before export of FP-22, the two constructs, although freely diffusible, were seen to distribute differently between ER tubules and sheets. Analyses in temperature-blocked cells revealed that FP-17 is excluded from ER exit sites, whereas FP-22 is recruited to them, although it remains freely exchangeable with the surrounding reticulum. Thus, physicochemical features of the TMD influence sorting of membrane proteins both within the ER and at the ER-Golgi boundary by simple receptor-independent mechanisms based on partitioning.

| S-EPMC2287291 | biostudies-literature

BCL::MP-fold: folding membrane proteins through assembly of transmembrane helices.

Project description:Membrane protein structure determination remains a challenging endeavor. Computational methods that predict membrane protein structure from sequence can potentially aid structure determination for such difficult target proteins. The de novo protein structure prediction method BCL::Fold rapidly assembles secondary structure elements into three-dimensional models. Here, we describe modifications to the algorithm, named BCL::MP-Fold, in order to simulate membrane protein folding. Models are built into a static membrane object and are evaluated using a knowledge-based energy potential, which has been modified to account for the membrane environment. Additionally, a symmetry folding mode allows for the prediction of obligate homomultimers, a common property among membrane proteins. In a benchmark test of 40 proteins of known structure, the method sampled the correct topology in 34 cases. This demonstrates that the algorithm can accurately predict protein topology without the need for large multiple sequence alignments, homologous template structures, or experimental restraints.

| S-EPMC3738745 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data