Membrane protein structural bioinformatics

TMH Stab-pred: Predicting the stability of α-helical membrane proteins using sequence and structural features

The folding and stability of transmembrane proteins (TMPs) are governed by the insertion of secondary structural elements into the cell membrane followed by their assembly. Understanding the important features that dictate the stability of TMPs is important for elucidating their functions. In this work, we related sequence and structure-based parameters with free energy (ΔG0) of α-helical membrane proteins. Our results showed that the free energy transfer of hydrophobic peptides, relative contact order, total interaction energy, number of hydrogen bonds and lipid accessibility of transmembrane regions are important for stability. Further, we have developed multiple-regression models to predict the stability of α-helical membrane proteins using these features and our method can predict the stability with a correlation and mean absolute error (MAE) of 0.89 and 1.21 kcal/mol, respectively, on jack-knife test. The method was validated with a blind test set of three recently reported experimental ΔG0, which could predict the stability within an average MAE of 0.51 kcal/mol. Further, we developed a webserver for predicting the stability and it is freely available at (https://web.iitm.ac.in/bioinfo2/TMHS/). The importance of selected parameters and limitations are discussed.

The ABCT31 Transporter Regulates the Export System of Phenylacetic Acid as a Side-Chain Precursor of Penicillin G in Monascus ruber M7

The biosynthesis of penicillin G (PG) is compartmentalized, and the transportation of the end and intermediate products, and substrates (precursors) such as L-cysteine (L-Cys), L-valine (L-Val) and phenylacetic acid (PAA) requires traversing membrane barriers. However, the transportation system of PAA as a side chain of PG are unclear yet. To discover ABC transporters (ABCTs) involved in the transportation of PAA, the expression levels of 38 ABCT genes in the genome of Monascus ruber M7, culturing with and without PAA, were examined, and found that one abct gene, namely abct31, was considerably up-regulated with PAA, indicating that abct31 may be relative with PAA transportation. Furthermore the disruption of abct31 was carried out, and the effects of two PG substrate's amino acids (L-Cys and L-Val), PAA and some other weak acids on the morphologies and production of secondary metabolites (SMs) of Δabct31 and M. ruber M7, were performed through feeding experiments. The results revealed that L-Cys, L-Val and PAA substantially impacted the morphologies and SMs production of Δabct31 and M. ruber M7. The UPLC-MS/MS analysis findings demonstrated that Δabct31 did not interrupt the synthesis of PG in M. ruber M7. According to the results, it suggests that abct31 is involved in the resistance and detoxification of the weak acids, including the PAA in M. ruber M7.

Principal component analysis of alpha-helix deformations in transmembrane proteins

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.

Fungal Ice2p is in the same superfamily as 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 it is required for Inheritance of Cortical ER. Ice2p has also been reported to be involved in an ER metabolic branch-point that regulates the flux of lipid either to be stored in lipid droplets or to be used as membrane components. Alternately, Ice2p has been proposed to act as a tether that physically bridges the ER at contact sites with both lipid droplets and the plasma membrane via a long loop on the protein's cytoplasmic face that contains multiple predicted amphipathic helices. Here we carried out a bioinformatic analysis to increase understanding of Ice2p. First, regarding topology, we found that diverse members of the fungal Ice2 family have 10 transmembrane helices (TMHs), which places the long loop on the exofacial face of Ice2p, where it cannot form inter-organelle bridges. Second, we identified Ice2p as a full-length homolog of SERINC (serine incorporator), a family of proteins with 10 TMHs found universally in eukaryotes. Since SERINCs are potent restriction factors for HIV and other viruses, study of Ice2p may reveal functions or mechanisms that shed light on viral restriction by SERINCs.

The voltage-gated T-type Ca2+ channel is key to the sperm motility of Atlantic salmon (Salmo salar)

Ca²⁺ is a key element in the sperm activation process of Salmo salar. However, the molecular mechanisms by which this ion enters the sperm cell have been poorly studied. In this study, we examined, for the first time, the role of the voltage-gated T-type Ca²⁺ channel in the activation of sperm motility of Salmo salar. Using an in vitro inhibition assay, a significant decrease in total and progressive motility (P < 0.0001) was observed in Salmo salar sperm when they were treated with NNC-55-0396, a highly selective blocker. The in silico analysis showed that this blocker is docked with a strong affinity for the pore of the voltage-gated T-type calcium channel suggesting the blocking of Ca²⁺ ions. The results show that the T-type voltage-gated Ca²⁺ channel is key to sperm motility in Salmo salar.

MPTherm-pred: Analysis and Prediction of Thermal Stability Changes upon Mutations in Transmembrane Proteins

The stability of membrane proteins differs from globular proteins due to the presence of nonpolar membrane-spanning regions. Using a dataset of 929 membrane protein mutations whose effects on thermal stability (ΔT_m) were experimentally determined, we found that the average ΔT_m due to 190 stabilizing and 232 destabilizing mutations occurring in membrane-spanning regions are 2.43(3.1) °C and -5.48(5.5) °C, respectively. The ΔT_m values for mutations occurring in solvent-exposed regions are 2.56(2.82) and - 6.8(7.2) °C. We have systematically analyzed the factors influencing the stability of mutants and observed that changes in hydrophobicity, number of contacts between Cα atoms and frequency of aliphatic residues are important determinants of the stability change induced by mutations occurring in membrane-spanning regions. We have developed structure- and sequence-based machine learning predictors of ΔT_m due to mutations specifically for membrane proteins. They showed a correlation and mean absolute error (MAE) of 0.72 and 2.85 °C, respectively, between experimental and predicted ΔT_m for mutations in membrane-spanning regions on 10-fold group-wise cross-validation. The average correlation and MAE for mutations in aqueous regions are 0.73 and 3.7 °C, respectively. These MAE values are about 50% lower than standard deviations from the mean ΔT_m values. The reliability of the method was affirmed on a test set of mutations occurring in evolutionary independent protein sequences. The developed MPTherm-pred server for predicting thermal stability changes upon mutations in membrane proteins is available at https://web.iitm.ac.in/bioinfo2/mpthermpred/. Our results provide insights into factors influencing the stability of membrane proteins and can aid in designing mutants that are more resistant to thermal stress.

Structural Analysis and Dynamic Processes of the Transmembrane Segment Inside Different Micellar Environments-Implications for the TM4 Fragment of the Bilitranslocase Protein

The transmembrane (TM) proteins are gateways for molecular transport across the cell membrane that are often selected as potential targets for drug design. The bilitranslocase (BTL) protein facilitates the uptake of various anions, such as bilirubin, from the blood into the liver cells. As previously established, there are four hydrophobic transmembrane segments (TM1-TM4), which constitute the structure of the transmembrane channel of the BTL protein. In our previous studies, the 3D high-resolution structure of the TM2 and TM3 transmembrane fragments of the BTL in sodium dodecyl sulfate (SDS) micellar media were solved using Nuclear Magnetic Resonance (NMR) spectroscopy and molecular dynamics simulations (MD). The high-resolution 3D structure of the fourth transmembrane region (TM4) of the BTL was evaluated using NMR spectroscopy in two different micellar media, anionic SDS and zwitterionic DPC (dodecylphosphocholine). The presented experimental data revealed the existence of an α -helical conformation in the central part of the TM4 in both micellar media. In the case of SDS surfactant, the α -helical conformation is observed for the Pro258-Asn269 region. The use of the zwitterionic DPC micelle leads to the formation of an amphipathic α -helix, which is characterized by the extension of the central α -helix in the TM4 fragment to Phe257-Thr271. The complex character of the dynamic processes in the TM4 peptide within both surfactants was analyzed based on the relaxation data acquired on 15 N and 31 P isotopes. Contrary to previously published and present observations in the SDS micelle, the zwitterionic DPC environment leads to intensive low-frequency molecular dynamic processes in the TM4 fragment.

Molecular Evolution Bioinformatics Toward Structural Biology of TRPV1-4 Channels

Bioinformatics is a very resourceful tool to understand evolution of membrane proteins, such as transient receptor potential channels. Expert bioinformatics users rely on specialized scripting and programming skills. Several web servers and standalone tools are available for nonadvanced users willing to develop projects to understand their system of choice. In this case, we present a desktop-based protocol to develop evostructural hypotheses based on basic bioinformatics skills and resources, specifically for a small subgroup of TRPV channels, which can be further implemented for larger datasets.

Review of computational methods for virus-host protein interaction prediction: a case study on novel Ebola-human interactions

Identification of potential virus-host interactions is useful and vital to control the highly infectious virus-caused diseases. This may contribute toward development of new drugs to treat the viral infections. Recently, database records of clinically and experimentally validated interactions between a small set of human proteins and Ebola virus (EBOV) have been published. Using the information of the known human interaction partners of EBOV, our main objective is to identify a set of proteins that may interact with EBOV proteins. Here, we first review the state-of-the-art, computational methods used for prediction of novel virus-host interactions for infectious diseases followed by a case study on EBOV-human interactions. The assessment result shows that the predicted human host proteins are highly similar with known human interaction partners of EBOV in the context of structure and semantics and are responsible for similar biochemical activities, pathways and host-pathogen relationships.

The application of Hadoop in structural bioinformatics

The paper reviews the use of the Hadoop platform in structural bioinformatics applications. For structural bioinformatics, Hadoop provides a new framework to analyse large fractions of the Protein Data Bank that is key for high-throughput studies of, for example, protein-ligand docking, clustering of protein-ligand complexes and structural alignment. Specifically we review in the literature a number of implementations using Hadoop of high-throughput analyses and their scalability. We find that these deployments for the most part use known executables called from MapReduce rather than rewriting the algorithms. The scalability exhibits a variable behaviour in comparison with other batch schedulers, particularly as direct comparisons on the same platform are generally not available. Direct comparisons of Hadoop with batch schedulers are absent in the literature but we note there is some evidence that Message Passing Interface implementations scale better than Hadoop. A significant barrier to the use of the Hadoop ecosystem is the difficulty of the interface and configuration of a resource to use Hadoop. This will improve over time as interfaces to Hadoop, e.g. Spark improve, usage of cloud platforms (e.g. Azure and Amazon Web Services (AWS)) increases and standardised approaches such as Workflow Languages (i.e. Workflow Definition Language, Common Workflow Language and Nextflow) are taken up.

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.

Directed Evolution of Membrane Transport Using Synthetic Selections

Understanding and engineering solute transporters is important for metabolic engineering and the development of therapeutics. However, limited available experimental data on membrane transporters makes sequence-function relationships complex to predict. Here we apply ligand-responsive biosensor systems that enable selective growth of E. coli cells only if they functionally express an importer that is specific to the biosensor ligand. Using this system in a directed evolution framework, we successfully engineer the specificity of nicotinamide riboside transporters, PnuC, to accept thiamine as a substrate. Our results provide insight into the molecular determinants of substrate recognition of the PnuC transporter family and demonstrate how synthetic biology can be deployed to engineer the substrate spectrum of small molecule transporters.

Computational Approaches for Revealing the Structure of Membrane Transporters: Case Study on Bilitranslocase

The structural and functional details of transmembrane proteins are vastly underexplored, mostly due to experimental difficulties regarding their solubility and stability. Currently, the majority of transmembrane protein structures are still unknown and this present a huge experimental and computational challenge. Nowadays, thanks to X-ray crystallography or NMR spectroscopy over 3000 structures of membrane proteins have been solved, among them only a few hundred unique ones. Due to the vast biological and pharmaceutical interest in the elucidation of the structure and the functional mechanisms of transmembrane proteins, several computational methods have been developed to overcome the experimental gap. If combined with experimental data the computational information enables rapid, low cost and successful predictions of the molecular structure of unsolved proteins. The reliability of the predictions depends on the availability and accuracy of experimental data associated with structural information. In this review, the following methods are proposed for in silico structure elucidation: sequence-dependent predictions of transmembrane regions, predictions of transmembrane helix–helix interactions, helix arrangements in membrane models, and testing their stability with molecular dynamics simulations. We also demonstrate the usage of the computational methods listed above by proposing a model for the molecular structure of the transmembrane protein bilitranslocase. Bilitranslocase is bilirubin membrane transporter, which shares similar tissue distribution and functional properties with some of the members of the Organic Anion Transporter family and is the only member classified in the Bilirubin Transporter Family. Regarding its unique properties, bilitranslocase is a potentially interesting drug target.

Properties of an inward-facing state of LeuT: conformational stability and substrate release

The leucine transporter (LeuT) is a bacterial homolog of the human monoamine transporters, which are important pharmaceutical targets. There are no high-resolution structures of the human transporters available; however, LeuT has been crystallized in several different conformational states. Recently, an inward-facing conformation of LeuT was solved revealing an unexpectedly large movement of transmembrane helix 1a (TM1a). We have performed molecular dynamics simulations of the mutated and wild-type transporter, with and without the cocrystallized Fab antibody fragment, to investigate the properties of this inward-facing conformation in relation to transport by LeuT within the membrane environment. In all of the simulations, local conformational changes with respect to the crystal structure are consistently observed, especially in TM1a. Umbrella sampling revealed a soft potential for TM1a tilting. Furthermore, simulations of inward-facing LeuT with Na(+) ions and substrate bound suggest that one of the Na(+) ion binding sites is fully disrupted. Release of alanine and the second Na(+) ion is also observed, giving insight into the final stage of the translocation process in atomistic detail.

Structural Model of the Bilitranslocase Transmembrane Domain Supported by NMR and FRET Data

We present a 3D model of the four transmembrane (TM) helical regions of bilitranslocase (BTL), a structurally uncharacterized protein that transports organic anions across the cell membrane. The model was computed by considering helix-helix interactions as primary constraints, using Monte Carlo simulations. The interactions between the TM2 and TM3 segments have been confirmed by Förster resonance energy transfer (FRET) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy, increasing our confidence in the model. Several insights into the BTL transport mechanism were obtained by analyzing the model. For example, the observed cis-trans Leu-Pro peptide bond isomerization in the TM3 fragment may indicate a key conformational change during anion transport by BTL. Our structural model of BTL may facilitate further studies, including drug discovery.

Sequence-structure relationship study in all-α transmembrane proteins using an unsupervised learning approach

Transmembrane proteins (TMPs) are major drug targets, but the knowledge of their precise topology structure remains highly limited compared with globular proteins. In spite of the difficulties in obtaining their structures, an important effort has been made these last years to increase their number from an experimental and computational point of view. In view of this emerging challenge, the development of computational methods to extract knowledge from these data is crucial for the better understanding of their functions and in improving the quality of structural models. Here, we revisit an efficient unsupervised learning procedure, called Hybrid Protein Model (HPM), which is applied to the analysis of transmembrane proteins belonging to the all-α structural class. HPM method is an original classification procedure that efficiently combines sequence and structure learning. The procedure was initially applied to the analysis of globular proteins. In the present case, HPM classifies a set of overlapping protein fragments, extracted from a non-redundant databank of TMP 3D structure. After fine-tuning of the learning parameters, the optimal classification results in 65 clusters. They represent at best similar relationships between sequence and local structure properties of TMPs. Interestingly, HPM distinguishes among the resulting clusters two helical regions with distinct hydrophobic patterns. This underlines the complexity of the topology of these proteins. The HPM classification enlightens unusual relationship between amino acids in TMP fragments, which can be useful to elaborate new amino acids substitution matrices. Finally, two challenging applications are described: the first one aims at annotating protein functions (channel or not), the second one intends to assess the quality of the structures (X-ray or models) via a new scoring function deduced from the HPM classification.

The membrane- and soluble-protein helix-helix interactome: similar geometry via different interactions

α Helices are a basic unit of protein secondary structure and therefore the interaction between helices is crucial to understanding tertiary and higher-order folds. Comparing subtle variations in the structural and sequence motifs between membrane and soluble proteins sheds light on the different constraints faced by each environment and elucidates the complex puzzle of membrane protein folding. Here, we demonstrate that membrane and water-soluble helix pairs share a small number of similar folds with various interhelical distances. The composition of the residues that pack at the interface between corresponding motifs shows that hydrophobic residues tend to be more enriched in the water-soluble class of structures and small residues in the transmembrane class. The latter group facilitates packing via sidechain- and backbone-mediated hydrogen bonds within the low-dielectric membrane milieu. The helix-helix interactome space, with its associated sequence preferences and accompanying hydrogen-bonding patterns, should be useful for engineering, prediction, and design of protein structure.

Recent progress on structural bioinformatics research of cytochrome P450 and its impact on drug discovery

Cytochrome P450 is predominantly responsible for human drug metabolism, which is of critical importance for drug discovery and development. Structural bioinformatics focuses on analysis and prediction of three-dimentional structure of biological macromolecules and elucidation of structure-function relationship as well as identification of important binding interactions. Rapid advancement of structural bioinformatics has been made over the last decade. With more information available for CYP structures, the methods of structural bioinformatics may be used in the CYP field. In this review, we demonstrate three previous studies on CYP using the methods of structural bioinformatics, including the investigation of reasons for decrease of enzymatic activity of CYP1A2 caused by a peripheral mutation, the construction of a pharmacophore model specific to active site of CYP1A2 and the prediction of the functional consequences of single residue mutation in CYP. By illustrating these studies we attempt to show the potential role of structural bioinformatics in CYP research and help better understanding the importance of structural bioinformatics in drug designing.

Molecular modeling and ligand docking for solute carrier (SLC) transporters

Solute Carrier (SLC) transporters are membrane proteins that transport solutes, such as ions, metabolites, peptides, and drugs, across biological membranes, using diverse energy coupling mechanisms. In human, there are 386 SLC transporters, many of which contribute to the absorption, distribution, metabolism, and excretion of drugs and/or can be targeted directly by therapeutics. Recent atomic structures of SLC transporters determined by X-ray crystallography and NMR spectroscopy have significantly expanded the applicability of structure-based prediction of SLC transporter ligands, by enabling both comparative modeling of additional SLC transporters and virtual screening of small molecules libraries against experimental structures as well as comparative models. In this review, we begin by describing computational tools, including sequence analysis, comparative modeling, and virtual screening, that are used to predict the structures and functions of membrane proteins such as SLC transporters. We then illustrate the applications of these tools to predicting ligand specificities of select SLC transporters, followed by experimental validation using uptake kinetic measurements and other assays. We conclude by discussing future directions in the discovery of the SLC transporter ligands.

Helix kinks are equally prevalent in soluble and membrane proteins

Helix kinks are a common feature of α-helical membrane proteins, but are thought to be rare in soluble proteins. In this study we find that kinks are a feature of long α-helices in both soluble and membrane proteins, rather than just transmembrane α-helices. The apparent rarity of kinks in soluble proteins is due to the relative infrequency of long helices (≥20 residues) in these proteins. We compare length-matched sets of soluble and membrane helices, and find that the frequency of kinks, the role of Proline, the patterns of other amino acid around kinks (allowing for the expected differences in amino acid distributions between the two types of protein), and the effects of hydrogen bonds are the same for the two types of helices. In both types of protein, helices that contain Proline in the second and subsequent turns are very frequently kinked. However, there are a sizeable proportion of kinked helices that do not contain a Proline in either their sequence or sequence homolog. Moreover, we observe that in soluble proteins, kinked helices have a structural preference in that they typically point into the solvent.

Functional cooperation of metabotropic adenosine and glutamate receptors regulates postsynaptic plasticity in the cerebellum

G-protein-coupled receptors (GPCRs) may form heteromeric complexes and cooperatively mediate cellular responses. Although heteromeric GPCR complexes are suggested to occur in many neurons, their contribution to neuronal function remains unclear. We address this question using two GPCRs expressed in cerebellar Purkinje cells: adenosine A1 receptor (A1R), which regulates neurotransmitter release and neuronal excitability in central neurons, and type-1 metabotropic glutamate receptor (mGluR1), which mediates cerebellar long-term depression, a form of synaptic plasticity crucial for cerebellar motor learning. We examined interaction between these GPCRs by immunocytochemical, biochemical, and Förster resonance energy transfer analyses in cultured mouse Purkinje cells and heterologous expression cells. These analyses revealed that the GPCRs closely colocalized and formed heteromeric complexes on the cell surfaces. Furthermore, our electrophysiological analysis showed that CSF levels (40-400 nm) of adenosine or synthetic A1R agonists with comparable potencies blocked mGluR1-mediated long-term depression of the postsynaptic glutamate-responsiveness (glu-LTD) of cultured Purkinje cells. A similar dose of the A1R agonist decreased the ligand affinity of mGluR1 and did not affect depolarization-induced Ca(2+) influx, which is an essential factor in inducing glu-LTD. The A1R agonist did not affect glu-LTD mimicked by direct activation of protein kinase C. These results suggest that A1R blocked glu-LTD by decreasing the ligand sensitivity of mGluR1, but not the coupling efficacy from mGluR1 to the intracellular signaling cascades. These findings provide a new insight into neuronal GPCR signaling and demonstrate a novel regulatory mechanism of synaptic plasticity.

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

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.

Plant High-Affinity Potassium (HKT) Transporters involved in salinity tolerance: structural insights to probe differences in ion selectivity

High-affinity Potassium Transporters (HKTs) belong to an important class of integral membrane proteins (IMPs) that facilitate cation transport across the plasma membranes of plant cells. Some members of the HKT protein family have been shown to be critical for salinity tolerance in commercially important crop species, particularly in grains, through exclusion of Na⁺ ions from sensitive shoot tissues in plants. However, given the number of different HKT proteins expressed in plants, it is likely that different members of this protein family perform in a range of functions. Plant breeders and biotechnologists have attempted to manipulate HKT gene expression through genetic engineering and more conventional plant breeding methods to improve the salinity tolerance of commercially important crop plants. Successful manipulation of a biological trait is more likely to be effective after a thorough understanding of how the trait, genes and proteins are interconnected at the whole plant level. This article examines the current structural and functional knowledge relating to plant HKTs and how their structural features may explain their transport selectivity. We also highlight specific areas where new knowledge of plant HKT transporters is needed. Our goal is to present how knowledge of the structure of HKT proteins is helpful in understanding their function and how this understanding can be an invaluable experimental tool. As such, we assert that accurate structural information of plant IMPs will greatly inform functional studies and will lead to a deeper understanding of plant nutrition, signalling and stress tolerance, all of which represent factors that can be manipulated to improve agricultural productivity.

PDBTM: Protein Data Bank of transmembrane proteins after 8 years

The PDBTM database (available at http://pdbtm.enzim.hu), the first comprehensive and up-to-date transmembrane protein selection of the Protein Data Bank, was launched in 2004. The database was created and has been continuously updated by the TMDET algorithm that is able to distinguish between transmembrane and non-transmembrane proteins using their 3D atomic coordinates only. The TMDET algorithm can locate the spatial positions of transmembrane proteins in lipid bilayer as well. During the last 8 years not only the size of the PDBTM database has been steadily growing from ∼400 to 1700 entries but also new structural elements have been identified, in addition to the well-known α-helical bundle and β-barrel structures. Numerous ‘exotic’ transmembrane protein structures have been solved since the first release, which has made it necessary to define these new structural elements, such as membrane loops or interfacial helices in the database. This article reports the new features of the PDBTM database that have been added since its first release, and our current efforts to keep the database up-to-date and easy to use so that it may continue to serve as a fundamental resource for the scientific community.