A benchmark server using high resolution protein structure data, and benchmark results for membrane helix predictions

MBOAT7 is anchored to endomembranes by six transmembrane domains

Membrane bound O-acyltransferase domain- containing 7 (MBOAT7, also known as LPIAT1) is a protein involved in the acyl chain remodeling of phospholipids via the Lands' cycle. The MBOAT7 is a susceptibility risk genetic locus for non-alcoholic fatty liver disease (NAFLD) and mental retardation. Although it has been shown that MBOAT7 is associated to membranes, the MBOAT7 topology remains unknown. To solve the topological organization of MBOAT7, we performed: A) solubilization of the total membrane fraction of cells overexpressing the recombinant MBOAT7-V5, which revealed MBOAT7 is an integral protein strongly attached to endomembranes; B) in silico analysis by using 22 computational methods, which predicted the number and localization of transmembrane domains of MBOAT7 with a range between 5 and 12; C) in vitro analysis of living cells transfected with GFP-tagged MBOAT7 full length and truncated forms, using a combination of Western Blotting, co-immunofluorescence and Fluorescence Protease Protection (FPP) assay; D) in vitro analysis of living cells transfected with FLAG-tagged MBOAT7 full length forms, using a combination of Western Blotting, selective membrane permeabilization followed by indirect immunofluorescence. All together, these data revealed that MBOAT7 is a multispanning transmembrane protein with six transmembrane domains. Based on our model, the predicted catalytic dyad of the protein, composed of the conserved asparagine in position 321 (Asn-321) and the preserved histidine in position 356 (His-356), has a lumenal localization. These data are compatible with the role of MBOAT7 in remodeling the acyl chain composition of endomembranes.

TMSEG: Novel prediction of transmembrane helices

Transmembrane proteins (TMPs) are important drug targets because they are essential for signaling, regulation, and transport. Despite important breakthroughs, experimental structure determination remains challenging for TMPs. Various methods have bridged the gap by predicting transmembrane helices (TMHs), but room for improvement remains. Here, we present TMSEG, a novel method identifying TMPs and accurately predicting their TMHs and their topology. The method combines machine learning with empirical filters. Testing it on a non-redundant dataset of 41 TMPs and 285 soluble proteins, and applying strict performance measures, TMSEG outperformed the state-of-the-art in our hands. TMSEG correctly distinguished helical TMPs from other proteins with a sensitivity of 98 ± 2% and a false positive rate as low as 3 ± 1%. Individual TMHs were predicted with a precision of 87 ± 3% and recall of 84 ± 3%. Furthermore, in 63 ± 6% of helical TMPs the placement of all TMHs and their inside/outside topology was correctly predicted. There are two main features that distinguish TMSEG from other methods. First, the errors in finding all helical TMPs in an organism are significantly reduced. For example, in human this leads to 200 and 1600 fewer misclassifications compared to the second and third best method available, and 4400 fewer mistakes than by a simple hydrophobicity-based method. Second, TMSEG provides an add-on improvement for any existing method to benefit from. Proteins 2016; 84:1706-1716. © 2016 Wiley Periodicals, Inc.

Topology based identification and comprehensive classification of four-transmembrane helix containing proteins (4TMs) in the human genome

BACKGROUND

Membrane proteins are key components in a large spectrum of diverse functions and thus account for the major proportion of the drug-targeted portion of the genome. From a structural perspective, the α-helical transmembrane proteins can be categorized into major groups based on the number of transmembrane helices and these groups are often associated with specific functions. When compared to the well-characterized seven-transmembrane containing proteins (7TM), other TM groups are less explored and in particular the 4TM group. In this study, we identify the complete 4TM complement from the latest release of the human genome and assess the 4TM structure group as a whole. We functionally characterize this dataset and evaluate the resulting groups and ubiquitous functions, and furthermore describe disease and drug target involvement.

RESULTS

We classified 373 proteins, which represents ~7 % of the human membrane proteome, and includes 69 more proteins than our previous estimate. We have characterized the 4TM dataset based on functional, structural, and/or evolutionary similarities. Proteins that are involved in transport activity constitute 37 % of the dataset, 23 % are receptor-related, and 13 % have enzymatic functions. Intriguingly, proteins involved in transport are more than double the 15 % of transporters in the entire human membrane proteome, which might suggest that the 4TM topological architecture is more favored for transporting molecules over other functions. Moreover, we found an interesting exception to the ubiquitous intracellular N- and C-termini localization that is found throughout the entire membrane proteome and 4TM dataset in the neurotransmitter gated ion channel families. Overall, we estimate that 58 % of the dataset has a known association to disease conditions with 19 % of the genes possibly involved in different types of cancer.

CONCLUSIONS

We provide here the most robust and updated classification of the 4TM complement of the human genome as a platform to further understand the characteristics of 4TM functions and to explore pharmacological opportunities.

Evaluation of transmembrane helix predictions in 2014

Experimental structure determination continues to be challenging for membrane proteins. Computational prediction methods are therefore needed and widely used to supplement experimental data. Here, we re-examined the state of the art in transmembrane helix prediction based on a nonredundant dataset with 190 high-resolution structures. Analyzing 12 widely-used and well-known methods using a stringent performance measure, we largely confirmed the expected high level of performance. On the other hand, all methods performed worse for proteins that could not have been used for development. A few results stood out: First, all methods predicted proteins in eukaryotes better than those in bacteria. Second, methods worked less well for proteins with many transmembrane helices. Third, most methods correctly discriminated between soluble and transmembrane proteins. However, several older methods often mistook signal peptides for transmembrane helices. Some newer methods have overcome this shortcoming. In our hands, PolyPhobius and MEMSAT-SVM outperformed other methods.

Life at the border: adaptation of proteins to anisotropic membrane environment

This review discusses main features of transmembrane (TM) proteins which distinguish them from water-soluble proteins and allow their adaptation to the anisotropic membrane environment. We overview the structural limitations on membrane protein architecture, spatial arrangement of proteins in membranes and their intrinsic hydrophobic thickness, co-translational and post-translational folding and insertion into lipid bilayers, topogenesis, high propensity to form oligomers, and large-scale conformational transitions during membrane insertion and transport function. Special attention is paid to the polarity of TM protein surfaces described by profiles of dipolarity/polarizability and hydrogen-bonding capacity parameters that match polarity of the lipid environment. Analysis of distributions of Trp resides on surfaces of TM proteins from different biological membranes indicates that interfacial membrane regions with preferential accumulation of Trp indole rings correspond to the outer part of the lipid acyl chain region-between double bonds and carbonyl groups of lipids. These "midpolar" regions are not always symmetric in proteins from natural membranes. We also examined the hydrophobic effect that drives insertion of proteins into lipid bilayer and different free energy contributions to TM protein stability, including attractive van der Waals forces and hydrogen bonds, side-chain conformational entropy, the hydrophobic mismatch, membrane deformations, and specific protein-lipid binding.

In silico evaluation of the influence of the translocon on partitioning of membrane segments

Background

The locations of the TM segments inside the membrane proteins are the consequence of a cascade of several events: the localizing of the nascent chain to the membrane, its insertion through the translocon, and the conformation adopted to reach its stable state inside the lipid bilayer. Even though the hydrophobic h-region of signal peptides and a typical TM segment are both composed of mostly hydrophobic side chains, the translocon has the ability to determine whether a given segment is to be inserted into the membrane. Our goal is to acquire robust biological insights into the influence of the translocon on membrane insertion of helices, obtained from the in silico discrimination between signal peptides and transmembrane segments of bitopic proteins. Therefore, by exploiting this subtle difference, we produce an optimized scale that evaluates the tendency of each amino acid to form sequences destined for membrane insertion by the translocon.

Results

The learning phase of our approach is conducted on carefully chosen data and easily converges on an optimal solution called the PMIscale (Potential Membrane Insertion scale). Our study leads to two striking results. Firstly, with a very simple sliding-window prediction method, PMIscale enables an efficient discrimination between signal peptides and signal anchors. Secondly, PMIscale is also able to identify TM segments and to localize them within protein sequences.

Conclusions

Despite its simplicity, the localization method based on PMIscale nearly attains the highest level of TM topography prediction accuracy as the current state-of-the-art prediction methods. These observations confirm the prominent role of the translocon in the localization of TM segments and suggest several biological hypotheses about the physical properties of the translocon.

A functional genomic analysis of Arabidopsis thaliana PP2C clade D

In the reference dicot plant Arabidopsis thaliana, the PP2C family of P-protein phosphatases includes the products of 80 genes that have been separated into ten multi-protein clades plus six singletons. Clade D includes the products of nine genes distributed among three chromosomes (APD1, At3g12620; APD2, At3g17090; APD3, At3g51370; APD4, At3g55050; APD5, At4g33920; APD6, At4g38520; APD7, At5g02760; APD8, At5g06750; and APD9, At5g66080). As part of a functional genomics analysis of protein phosphorylation, we retrieved expression data from public databases and determined the subcellular protein localization of the members of clade D. While the nine proteins have been grouped together based upon primary sequence alignments, we observed no obvious common patterns in expression or localization. We found chimera with the GFP associated with the nucleus, plasma membrane, the endomembrane system, and mitochondria in transgenic plants.