Topology of membrane proteins-predictions, limitations and variations

Transmembrane proteins-Different anchoring systems

Transmembrane proteins are active in amphipathic environments. To stabilize the protein in such surrounding the exposure of hydrophobic residues on the protein surface is required. Transmembrane proteins are responsible for the transport of various molecules. Therefore, they often represent structures in the form of channels. This analysis focused on the stability and local flexibility of transmembrane proteins, particularly those related to their biological activity. Different forms of anchorage were identified using the fuzzy oil-drop model (FOD) and its modified form, FOD-M. The mainly helical as well as β-barrel structural forms are compared with respect to the mechanism of stabilization in the cell membrane. The different anchoring system was found to stabilize protein molecules with possible local fluctuation.

Should I stay or should I go? Trafficking of plant extra-nuclear transcription factors

At the heart of all biological processes lies the control of nuclear gene expression, which is primarily achieved through the action of transcription factors (TFs) that generally contain a nuclear localization signal (NLS) to facilitate their transport into the nucleus. However, some TFs reside in the cytoplasm in a transcriptionally inactive state and only enter the nucleus in response to specific signals, which in plants include biotic or abiotic stresses. These extra-nuclear TFs can be found in the cytosol or associated with various membrane systems, including the endoplasmic reticulum and plasma membrane. They may be integral proteins with transmembrane domains or associate peripherally with the lipid bilayer via acylation or membrane-binding domains. Although over 30 plant TFs, most of them involved in stress responses, have been experimentally shown to reside outside the nucleus, computational predictions suggest that this number is much larger. Understanding how extra-nuclear TFs are trafficked into the nucleus is essential for reconstructing transcriptional regulatory networks that govern major cellular pathways in response to biotic and abiotic signals. Here, we provide a perspective on what is known on plant extranuclear-nuclear TF retention, nuclear trafficking, and the post-translational modifications that ultimately enable them to regulate gene expression upon entering the nucleus.

In Silico Analyses of Vertebrate G-Protein-Coupled Receptor Fusions United With or Without an Additional Transmembrane Sequence Indicate Classification into Three Groups of Linkers

Natural G-protein-coupled receptors (GPCRs) rarely have an additional transmembrane (TM) helix, such as an artificial TM-linker that can unite two class A GPCRs in tandem as a single-polypeptide chain (sc). Here, we report that three groups of TM-linkers exist in the intervening regions of natural GPCR fusions from vertebrates: (1) the original consensus (i.e., consensus 1) and consensus 2~4 (related to GPCR itself or its receptor-interacting proteins); (2) the consensus but GPCR-unrelated ones, 1~7; and (3) the inability to apply 1/2 that show no similarity to any other proteins. In silico analyses indicated that all natural GPCR fusions from Amphibia lack a TM-linker, and reptiles have no GPCR fusions; moreover, in either the GPCR-GPCR fusion or fusion protein of (GPCR monomer) and non-GPCR proteins from vertebrates, excluding tetrapods, i.e., so-called fishes, TM-linkers differ from previously reported mammalian and are avian sequences and are classified as Groups 2 and 3. Thus, previously reported TM-linkers were arranged: Consensus 1 is [T(I/A/P)(A/S)-(L/N)(I/W/L)(I/A/V)GL(L/G)(A/T)(S/L/G)(I/L)] first identified in invertebrate sea anemone Exaiptasia diaphana (LOC110241027) and (330-SPSFLCI-L-SLL-340) identified in a tropical bird Opisthocomus hoazin protein LOC104327099 (XP_009930279.1); GPCR-related consensus 2~4 are, respectively, (371-prlilyavfc fgtatg-386) in the desert woodrat Neotoma lepida A6R68_19462 (OBS78147.1), (363-lsipfcll yiaallgnfi llfvi-385) in Gavia stellate (red-throated loon) LOC104264164 (XP_009819412.1), and (479-ti vvvymivcvi glvgnflvmy viir-504) in a snailfish GPCR (TNN80062.1); In Mammals Neotoma lepida, Aves Erythrura gouldiae, and fishes protein (respectively, OBS83645.1, RLW13346.1 and KPP79779.1), the TM-linkers are Group 2. Here, we categorized, for the first time, natural TM-linkers as rare evolutionary events among all vertebrates.

TMKit: a Python interface for computational analysis of transmembrane proteins

Transmembrane proteins are receptors, enzymes, transporters and ion channels that are instrumental in regulating a variety of cellular activities, such as signal transduction and cell communication. Despite tremendous progress in computational capacities to support protein research, there is still a significant gap in the availability of specialized computational analysis toolkits for transmembrane protein research. Here, we introduce TMKit, an open-source Python programming interface that is modular, scalable and specifically designed for processing transmembrane protein data. TMKit is a one-stop computational analysis tool for transmembrane proteins, enabling users to perform database wrangling, engineer features at the mutational, domain and topological levels, and visualize protein-protein interaction interfaces. In addition, TMKit includes seqNetRR, a high-performance computing library that allows customized construction of a large number of residue connections. This library is particularly well suited for assigning correlation matrix-based features at a fast speed. TMKit should serve as a useful tool for researchers in assisting the study of transmembrane protein sequences and structures. TMKit is publicly available through https://github.com/2003100127/tmkit and https://tmkit-guide.herokuapp.com/doc/overview.

Interaction Network Construction and Functional Analysis of the Plasma Membrane H+-ATPase in Bangia fuscopurpurea (Rhodophyta)

Salinity is a serious threat to most land plants. Although seaweeds adapt to salty environments, intertidal species experience wide fluctuations in external salinities, including hyper- and hypo-saline stress. Bangia fuscopurpurea is an economic intertidal seaweed with a strong tolerance to hypo-salinity. Until now, the salt stress tolerance mechanism has remained elusive. Our previous study showed that the expression of B. fuscopurpurea plasma membrane H⁺-ATPase (BfPMHA) genes were the most upregulated under hypo-salinity. In this study, we obtained the complete sequence of BfPMHA, traced the relative expression of this BfPMHA gene in B. fuscopurpurea under hypo-salinity, and analyzed the protein structure and properties based on the gene's sequence. The result showed that the expression of BfPMHA in B. fuscopurpurea increased significantly with varying hypo-salinity treatments, and the higher the degree of low salinity stress, the higher the expression level. This BfPMHA had typical PMHA structures with a Cation-N domain, an E1-E2 ATPase domain, a Hydrolase domain, and seven transmembrane domains. In addition, through the membrane system yeast two-hybrid library, three candidate proteins interacting with BfPMHA during hypo-saline stress were screened, fructose-bisphosphate aldolase (BfFBA), glyceraldehyde 3-phosphate dehydrogenase (NADP⁺) (phosphorylating) (BfGAPDH), and manganese superoxide dismutase (BfMnSOD). The three candidates and BfPMHA genes were successfully transferred and overexpressed in a BY4741 yeast strain. All of them significantly enhanced the yeast tolerance to NaCl stress, verifying the function of BfPMHA in salt stress response. This is the first study to report the structure and topological features of PMHA in B. fuscopurpurea and its candidate interaction proteins in response to salt stress.

Exopolysaccharide Biosynthesis in Rhizobium leguminosarum bv. trifolii Requires a Complementary Function of Two Homologous Glycosyltransferases PssG and PssI

The Pss-I region of Rhizobium leguminosarum bv. trifolii TA1 comprises more than 20 genes coding for glycosyltransferases, modifying enzymes, and polymerization/export proteins, altogether determining the biosynthesis of symbiotically relevant exopolysaccharides. In this study, the role of homologous PssG and PssI glycosyltransferases in exopolysaccharide subunit synthesis were analyzed. It was shown that the glycosyltransferase-encoding genes of the Pss-I region were part of a single large transcriptional unit with potential downstream promoters activated in specific conditions. The ΔpssG and ΔpssI mutants produced significantly lower amounts of the exopolysaccharide, while the double deletion mutant ΔpssIΔpssG produced no exopolysaccharide. Complementation of double mutation with individual genes restored exopolysaccharide synthesis, but only to the level similar to that observed for the single ΔpssI or ΔpssG mutants, indicating that PssG and PssI serve complementary functions in the process. PssG and PssI interacted with each other in vivo and in vitro. Moreover, PssI displayed an expanded in vivo interaction network comprising other GTs involved in subunit assembly and polymerization/export proteins. PssG and PssI proteins were shown to interact with the inner membrane through amphipathic helices at their C-termini, and PssG also required other proteins involved in exopolysaccharide synthesis to localize in the membrane protein fraction.

Machine learning in computational modelling of membrane protein sequences and structures: From methodologies to applications

Membrane proteins mediate a wide spectrum of biological processes, such as signal transduction and cell communication. Due to the arduous and costly nature inherent to the experimental process, membrane proteins have long been devoid of well-resolved atomic-level tertiary structures and, consequently, the understanding of their functional roles underlying a multitude of life activities has been hampered. Currently, computational tools dedicated to furthering the structure-function understanding are primarily focused on utilizing intelligent algorithms to address a variety of site-wise prediction problems (e.g., topology and interaction sites), but are scattered across different computing sources. Moreover, the recent advent of deep learning techniques has immensely expedited the development of computational tools for membrane protein-related prediction problems. Given the growing number of applications optimized particularly by manifold deep neural networks, we herein provide a review on the current status of computational strategies mainly in membrane protein type classification, topology identification, interaction site detection, and pathogenic effect prediction. Meanwhile, we provide an overview of how the entire prediction process proceeds, including database collection, data pre-processing, feature extraction, and method selection. This review is expected to be useful for developing more extendable computational tools specific to membrane proteins.

An inducible amphipathic α-helix mediates subcellular targeting and membrane binding of RPE65

RPE65 retinol isomerase is an indispensable player in the visual cycle between the vertebrate retina and RPE. Although membrane association is critical for RPE65 function, its mechanism is not clear. Residues 107-125 are believed to interact with membranes but are unresolved in all RPE65 crystal structures, whereas palmitoylation at C112 also plays a role. We report the mechanism of membrane recognition and binding by RPE65. Binding of aa107-125 synthetic peptide with membrane-mimicking micellar surfaces induces transition from unstructured loop to amphipathic α-helical (AH) structure but this transition is automatic in the C112-palmitoylated peptide. We demonstrate that the AH significantly affects palmitoylation level, membrane association, and isomerization activity of RPE65. Furthermore, aa107-125 functions as a membrane sensor and the AH as a membrane-targeting motif. Molecular dynamic simulations clearly show AH-membrane insertion, supporting our experimental findings. Collectively, these studies allow us to propose a working model for RPE65-membrane binding, and to provide a novel role for cysteine palmitoylation.

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 mc [2]4517. 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.

DOCKGROUND membrane protein-protein set

Membrane proteins are significantly underrepresented in Protein Data Bank despite their essential role in cellular mechanisms and the major progress in experimental protein structure determination. Thus, computational approaches are especially valuable in the case of membrane proteins and their assemblies. The main focus in developing structure prediction techniques has been on soluble proteins, in part due to much greater availability of the structural data. Currently, structure prediction of protein complexes (protein docking) is a well-developed field of study. However, the generic protein docking approaches are not optimal for the membrane proteins because of the differences in physicochemical environment and the spatial constraints imposed by the membranes. Thus, docking of the membrane proteins requires specialized computational methods. Development and benchmarking of the membrane protein docking approaches has to be based on high-quality sets of membrane protein complexes. In this study we present a new dataset of 456 non-redundant alpha helical binary interfaces. The set is significantly larger and more representative than the previously developed sets. In the future, it will become the basis for the development of docking and scoring benchmarks, similar to the ones for soluble proteins in the Dockground resource http://dockground.compbio.ku.edu.

Identification of Oocyst-Driven Toxoplasma gondii Infections in Humans and Animals through Stage-Specific Serology-Current Status and Future Perspectives

The apicomplexan zoonotic parasite Toxoplasma gondii has three infective stages: sporozoites in sporulated oocysts, which are shed in unsporulated form into the environment by infected felids; tissue cysts containing bradyzoites, and fast replicating tachyzoites that are responsible for acute toxoplasmosis. The contribution of oocysts to infections in both humans and animals is understudied despite being highly relevant. Only a few diagnostic antigens have been described to be capable of discriminating which parasite stage has caused an infection. Here we provide an extensive overview of the antigens and serological assays used to detect oocyst-driven infections in humans and animals according to the literature. In addition, we critically discuss the possibility to exploit the increasing knowledge of the T. gondii genome and the various 'omics datasets available, by applying predictive algorithms, for the identification of new oocyst-specific proteins for diagnostic purposes. Finally, we propose a workflow for how such antigens and assays based on them should be evaluated to ensure reproducible and robust results.

Topological analyses of the L-lysine exporter LysO reveal a critical role for a conserved pair of intramembrane solvent-exposed acidic residues

LysO, a prototypical member of the LysO family, mediates export of L-lysine (Lys) and resistance to the toxic Lys antimetabolite, L-thialysine (Thl) in Escherichia coli. Here, we have addressed unknown aspects of LysO function pertaining to its membrane topology and the mechanism by which it mediates Lys/Thl export. Using substituted cysteine (Cys) accessibility, here we delineated the membrane topology of LysO. Our studies support a model in which both the N- and C-termini of LysO are present at the periplasmic face of the membrane with a transmembrane (TM) domain comprising eight TM segments (TMSs) between them. In addition, a feature of intramembrane solvent exposure in LysO is inferred with the identification of membrane-located solvent-exposed Cys residues. Isosteric substitutions of a pair of conserved acidic residues, one E233, located in the solvent-exposed TMS7 and the other D261, in a solvent-exposed intramembrane segment located between TMS7 and TMS8, abolished LysO function in vivo. Thl, but not Lys, elicited proton release in inside-out membrane vesicles, a process requiring the presence of both E233 and D261. We postulate that Thl may be exported in antiport with H+ and that Lys may be a low-affinity export substrate. Our findings are compatible with a physiological scenario wherein in vivo LysO exports the naturally occurring antimetabolite Thl with higher affinity over the essential cellular metabolite Lys, thus affording protection from Thl toxicity and limiting wasteful export of Lys.

Integrative approach for detecting membrane proteins

Background

Membrane proteins are key gates that control various vital cellular functions. Membrane proteins are often detected using transmembrane topology prediction tools. While transmembrane topology prediction tools can detect integral membrane proteins, they do not address surface-bound proteins. In this study, we focused on finding the best techniques for distinguishing all types of membrane proteins.

Results

This research first demonstrates the shortcomings of merely using transmembrane topology prediction tools to detect all types of membrane proteins. Then, the performance of various feature extraction techniques in combination with different machine learning algorithms was explored. The experimental results obtained by cross-validation and independent testing suggest that applying an integrative approach that combines the results of transmembrane topology prediction and position-specific scoring matrix (Pse-PSSM) optimized evidence-theoretic k nearest neighbor (OET-KNN) predictors yields the best performance.

Conclusion

The integrative approach outperforms the state-of-the-art methods in terms of accuracy and MCC, where the accuracy reached a 92.51% in independent testing, compared to the 89.53% and 79.42% accuracies achieved by the state-of-the-art methods.

Dynamics of Co-translational Membrane Protein Integration and Translocation via the Sec Translocon

An important aspect of cellular function is the correct targeting and delivery of newly synthesized proteins. Central to this task is the machinery of the Sec translocon, a transmembrane channel that is involved in both the translocation of nascent proteins across cell membranes and the integration of proteins into the membrane. Considerable experimental and computational effort has focused on the Sec translocon and its role in nascent protein biosynthesis, including the correct folding and expression of integral membrane proteins. However, the use of molecular simulation methods to explore Sec-facilitated protein biosynthesis is hindered by the large system sizes and long (i.e., minute) time scales involved. In this work, we describe the development and application of a coarse-grained simulation approach that addresses these challenges and allows for direct comparison with both in vivo and in vitro experiments. The method reproduces a wide range of experimental observations, providing new insights into the underlying molecular mechanisms, predictions for new experiments, and a strategy for the rational enhancement of membrane protein expression levels.

Intestinal OCTN2- and MCT1-targeted drug delivery to improve oral bioavailability

Various drug transporters are widely expressed throughout the intestine and play important roles in absorbing nutrients and drugs, thus providing high quality targets for the design of prodrugs or nanoparticles to facilitate oral drug delivery. In particular, intestinal carnitine/organic cation transporter 2 (OCTN2) and mono-carboxylate transporter protein 1 (MCT1) possess high transport capacities and complementary distributions. Therefore, we outline recent developments in transporter-targeted oral drug delivery with regard to the OCTN2 and MCT1 proteins in this review. First, basic information of the two transporters is reviewed, including their topological structures, characteristics and functions, expression and key features of their substrates. Furthermore, progress in transporter-targeting prodrugs and nanoparticles to increase oral drug delivery is discussed, including improvements in the oral absorption of anti-inflammatory drugs, antiepileptic drugs and anticancer drugs. Finally, the potential of a dual transporter-targeting strategy is discussed.

Verification of the Saccharina japonica Translocon Tic20 and its Localization in the Chloroplast Membrane in Diatoms

Tic20 is an important translocon protein that plays a role in protein transport in the chloroplast. The sequence of Tic20 was determined in the lower brown alga Saccharina japonica. Structural analysis of SjTic20 revealed a noncanonical structure consisting of an N-terminal non-cyanobacterium-originated EF-hand domain (a helix-loop-helix structural domain) and a C-terminal cyanobacterium-originated Tic20 domain. Subcellular localization and transmembrane analysis indicated that SjTic20 featured an "M"-type Nin-Cin-terminal orientation, with four transmembrane domains in the innermost membrane of the chloroplast in the microalga Phaeodactylum tricornutum, and the EF-hand domain was entirely extruded into the chloroplast stroma. Our study provides information on the structure, localization, and topological features of SjTic20, and further functional analysis of SjTic20 in S. japonica is needed.

Inter-residue interactions in alpha-helical transmembrane proteins

MOTIVATION

The number of available membrane protein structures has markedly increased in the last years and, in parallel, the reliability of the methods to detect transmembrane (TM) segments. In the present report, we characterized inter-residue interactions in α-helical membrane proteins using a dataset of 3462 TM helices from 430 proteins. This is by far the largest analysis published to date.

RESULTS

Our analysis of residue-residue interactions in TM segments of membrane proteins shows that almost all interactions involve aliphatic residues and Phe. There is lack of polar-polar, polar-charged and charged-charged interactions except for those between Thr or Ser sidechains and the backbone carbonyl of aliphatic and Phe residues. The results are discussed in the context of the preferences of amino acids to be in the protein core or exposed to the lipid bilayer and to occupy specific positions along the TM segment. Comparison to datasets of β-barrel membrane proteins and of α-helical globular proteins unveils the specific patterns of interactions and residue composition characteristic of α-helical membrane proteins that are the clue to understanding their structure.

AVAILABILITY AND IMPLEMENTATION

Results data and datasets used are available at http://lmc.uab.cat/TMalphaDB/interactions.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MPLs-Pred: Predicting Membrane Protein-Ligand Binding Sites Using Hybrid Sequence-Based Features and Ligand-Specific Models

Membrane proteins (MPs) are involved in many essential biomolecule mechanisms as a pivotal factor in enabling the small molecule and signal transport between the two sides of the biological membrane; this is the reason that a large portion of modern medicinal drugs target MPs. Therefore, accurately identifying the membrane protein-ligand binding sites (MPLs) will significantly improve drug discovery. In this paper, we propose a sequence-based MPLs predictor called MPLs-Pred, where evolutionary profiles, topology structure, physicochemical properties, and primary sequence segment descriptors are combined as features applied to a random forest classifier, and an under-sampling scheme is used to enhance the classification capability with imbalanced samples. Additional ligand-specific models were taken into consideration in refining the prediction. The corresponding experimental results based on our method achieved an appreciable performance, with 0.63 MCC (Matthews correlation coefficient) as the overall prediction precision, and those values were 0.604, 0.7, and 0.692, respectively, for the three main types of ligands: drugs, metal ions, and biomacromolecules. MPLs-Pred is freely accessible at http://icdtools.nenu.edu.cn/.

A Brief History of Protein Sorting Prediction

Ever since the signal hypothesis was proposed in 1971, the exact nature of signal peptides has been a focus point of research. The prediction of signal peptides and protein subcellular location from amino acid sequences has been an important problem in bioinformatics since the dawn of this research field, involving many statistical and machine learning technologies. In this review, we provide a historical account of how position-weight matrices, artificial neural networks, hidden Markov models, support vector machines and, lately, deep learning techniques have been used in the attempts to predict where proteins go. Because the secretory pathway was the first one to be studied both experimentally and through bioinformatics, our main focus is on the historical development of prediction methods for signal peptides that target proteins for secretion; prediction methods to identify targeting signals for other cellular compartments are treated in less detail.

Efflux Pumps Represent Possible Evolutionary Convergence onto the β-Barrel Fold

There are around 100 varieties of outer membrane proteins in each Gram-negative bacteria. All of these proteins have the same fold-an up-down β-barrel. It has been suggested that all membrane β-barrels excluding lysins are homologous. Here we suggest that β-barrels of efflux pumps have converged on this fold as well. By grouping structurally solved outer membrane β-barrels (OMBBs) by sequence we find that the membrane environment may have led to convergent evolution of the barrel fold. Specifically, the lack of sequence linkage to other barrels coupled with distinctive structural differences, such as differences in strand tilt and barrel radius, suggest that the outer membrane factor of efflux pumps evolutionarily converged on the barrel. Rather than being related to other OMBBs, sequence and structural similarity in the periplasmic region of the outer membrane factor of efflux pumps suggests an evolutionary link to the periplasmic subunit of the same pump complex.