Membrane protein orientation and refinement using a knowledge-based statistical potential

PI3 kinase inhibitor PI828 uncouples aminergic GPCRs and Ca2+ mobilization irrespectively of its primary target

The phosphoinositide 3-kinase (PI3K) is involved in regulation of multiple intracellular processes. Although the inhibitory analysis is generally employed for validating a physiological role of PI3K, increasing body of evidence suggests that PI3K inhibitors can exhibit PI3K-unrelated activity as well. Here we studied Ca2+ signaling initiated by aminergic agonists in a variety of different cells and analyzed effects of the PI3K inhibitor PI828 on cell responsiveness. It turned out that PI828 inhibited Ca2+ transients elicited by acetylcholine (ACh), histamine, and serotonin, but did not affect Ca2+ responses to norepinephrine and ATP. Another PI3K inhibitor wortmannin negligibly affected Ca2+ signaling initiated by any one of the tested agonists. Using the genetically encoded PIP3 sensor PH(Akt)-Venus, we confirmed that both PI828 and wortmannin effectively inhibited PI3K and ascertained that this kinase negligibly contributed to ACh transduction. These findings suggested that PI828 inhibited Ca2+ responses to aminergic agonists tested, involving an unknown cellular mechanism unrelated to the PI3K inhibition. Complementary physiological experiments provided evidence that PI828 could inhibit Ca2+ signals induced by certain agonists, by acting extracellularly, presumably, through their surface receptors. For the muscarinic M3 receptor, this possibility was verified with molecular docking and molecular dynamics. As demonstrated with these tools, wortmannin could be bound in the extracellular vestibule at the muscarinic M3 receptor but this did not preclude binding of ACh to the M3 receptor followed by its activation. In contrast, PI828 could sterically block the passage of ACh into the allosteric site, preventing activation of the muscarinic M3 receptor.

Deep learning for the PSIPRED Protein Analysis Workbench

The PSIRED Workbench is a long established and popular bioinformatics web service offering a wide range of machine learning based analyses for characterizing protein structure and function. In this paper we provide an update of the recent additions and developments to the webserver, with a focus on new Deep Learning based methods. We briefly discuss some trends in server usage since the publication of AlphaFold2 and we give an overview of some upcoming developments for the service. The PSIPRED Workbench is available at http://bioinf.cs.ucl.ac.uk/psipred.

Can Protein Structure Prediction Methods Capture Alternative Conformations of Membrane Transporters?

Understanding the conformational dynamics of proteins, such as the inward-facing (IF) and outward-facing (OF) transition observed in transporters, is vital for elucidating their functional mechanisms. Despite significant advances in protein structure prediction (PSP) over the past three decades, most efforts have been focused on single-state prediction, leaving multistate or alternative conformation prediction (ACP) relatively unexplored. This discrepancy has led to the development of highly accurate PSP methods such as AlphaFold, yet their capabilities for ACP remain limited. To investigate the performance of current PSP methods in ACP, we curated a data set, named IOMemP, consisting of 32 experimentally determined high-resolution IF and OF structures of 16 membrane proteins with substantial conformational changes. We benchmarked 12 representative PSP methods, along with two recent multistate methods based on AlphaFold, against this data set. Our findings reveal a remarkably consistent preference for specific states across various PSP methods. We elucidated how coevolution information in MSAs influences state preference. Moreover, we showed that AlphaFold, when excluding coevolution information, estimated similar energies between the experimental IF and OF conformations, indicating that the energy model learned by AlphaFold is not biased toward any particular state. Our IOMemP data set and benchmark results are anticipated to advance the development of robust ACP methods.

Synthesis of lipid-linked precursors of the bacterial cell wall is governed by a feedback control mechanism in Pseudomonas aeruginosa

Many bacterial surface glycans such as the peptidoglycan (PG) cell wall are built from monomeric units linked to a polyprenyl lipid carrier. How this limiting carrier is distributed among competing pathways has remained unclear. Here we describe the isolation of hyperactive variants of Pseudomonas aeruginosa MraY, the enzyme that forms the first lipid-linked PG precursor. These variants result in the elevated production of the final PG precursor lipid II in cells and are hyperactive in vitro. The activated MraY variants have substitutions that map to a cavity on the extracellular side of the dimer interface, far from the active site. Our structural and molecular dynamics results suggest that this cavity is a binding site for externalized lipid II. Overall, our results support a model in which excess externalized lipid II allosterically inhibits MraY, providing a feedback mechanism that prevents the sequestration of lipid carrier in the PG biogenesis pathway.

Melamine-cored glucosides for membrane protein solubilization and stabilization: importance of water-mediated intermolecular hydrogen bonding in detergent performance

Membrane proteins play essential roles in a number of biological processes, and their structures are important in elucidating such processes at the molecular level and also for rational drug design and development. Membrane protein structure determination is notoriously challenging compared to that of soluble proteins, due largely to the inherent instability of their structures in non-lipid environments. Micelles formed by conventional detergents have been widely used for membrane protein manipulation, but they are suboptimal for long-term stability of membrane proteins, making downstream characterization difficult. Hence, there is an unmet need for the development of new amphipathic agents with enhanced efficacy for membrane protein stabilization. In this study, we designed and synthesized a set of glucoside amphiphiles with a melamine core, denoted melamine-cored glucosides (MGs). When evaluated with four membrane proteins (two transporters and two G protein-coupled receptors), MG-C11 conferred notably enhanced stability compared to the commonly used detergents, DDM and LMNG. These promising findings are mainly attributed to a unique feature of the MGs, i.e., the ability to form dynamic water-mediated hydrogen-bond networks between detergent molecules, as supported by molecular dynamics simulations. Thus, MG-C11 is the first example of a non-peptide amphiphile capable of forming intermolecular hydrogen bonds within a protein-detergent complex environment. Detergent micelles formed via a hydrogen-bond network could represent the next generation of highly effective membrane-mimetic systems useful for membrane protein structural studies.

Structural basis of peptidoglycan synthesis by E. coli RodA-PBP2 complex

Peptidoglycan (PG) is an essential structural component of the bacterial cell wall that is synthetized during cell division and elongation. PG forms an extracellular polymer crucial for cellular viability, the synthesis of which is the target of many antibiotics. PG assembly requires a glycosyltransferase (GT) to generate a glycan polymer using a Lipid II substrate, which is then crosslinked to the existing PG via a transpeptidase (TP) reaction. A Shape, Elongation, Division and Sporulation (SEDS) GT enzyme and a Class B Penicillin Binding Protein (PBP) form the core of the multi-protein complex required for PG assembly. Here we used single particle cryo-electron microscopy to determine the structure of a cell elongation-specific E. coli RodA-PBP2 complex. We combine this information with biochemical, genetic, spectroscopic, and computational analyses to identify the Lipid II binding sites and propose a mechanism for Lipid II polymerization. Our data suggest a hypothesis for the movement of the glycan strand from the Lipid II polymerization site of RodA towards the TP site of PBP2, functionally linking these two central enzymatic activities required for cell wall peptidoglycan biosynthesis.

Active Binding Modes of Caffeine with Cytochrome P450 1A2 Determine Its Metabolite Profiles

Caffeine is a very common kind of nervous stimulant, and it is primarily metabolized by Cytochrome P450 1A2 (CYP1A2) in the human body. Over the years, determining the interactions between caffeine and CYP1A2 has been a tough issue. The active binding modes and the catalytic regioselectivity of the metabolism between CYP1A2 and caffeine remain unclear. Here, to investigate the interactions between CYP1A2 and caffeine, we constructed the all-sequence CYP1A2-caffeine-membrane system using a multiple template approach. According to our simulation results, four active binding modes between CYP1A2 and caffeine that correspond to the four metabolic sites of caffeine are determined. What is more, a pre-reaction state for the CYP1A2-catalyzed reaction at caffeine's N3 site is identified. A more preponderant active binding mode might be the reason why the N3 site of caffeine becomes the primary metabolic site. Our findings could enhance our knowledge of the interactions between CYP1A2 and caffeine and help us better understand the regioselectivity of the metabolism between CYP1A2 and caffeine.

Structure-Based Modeling of Sigma 1 Receptor Interactions with Ligands and Cholesterol and Implications for Its Biological Function

The sigma 1 receptor (S1R) is a 223-amino-acid-long transmembrane endoplasmic reticulum (ER) protein. The S1R plays an important role in neuronal health and it is an established therapeutic target for neurodegenerative and neuropsychiatric disorders. Despite its importance in physiology and disease, the biological function of S1R is poorly understood. To gain insight into the biological and signaling functions of S1R, we took advantage of recently reported crystal structures of human and Xenopus S1Rs and performed structural modeling of S1R interactions with ligands and cholesterol in the presence of the membrane. By combining bioinformatics analysis of S1R sequence and structural modelling approaches, we proposed a model that suggests that S1R may exist in two distinct conformations-"dynamic monomer" (DM) and "anchored monomer" (AM). We further propose that equilibrium between AM and DM conformations of S1R is essential for its biological function in cells, with AM conformation facilitating the oligomerization of S1R and DM conformation facilitating deoligomerization. Consistent with experimental evidence, our hypothesis predicts that increased levels of membrane cholesterol and S1R antagonists should promote the oligomeric state of S1R, but S1R agonists and pathogenic mutations should promote its deoligomerization. Obtained results provide mechanistic insights into signaling functions of S1R in cells, and the proposed model may help to explain neuroprotective effects of S1R modulators.

A feedback control mechanism governs the synthesis of lipid-linked precursors of the bacterial cell wall

Many bacterial surface glycans such as the peptidoglycan (PG) cell wall, O-antigens, and capsules are built from monomeric units linked to a polyprenyl lipid carrier. How this limiting lipid carrier is effectively distributed among competing pathways has remained unclear for some time. Here, we describe the isolation and characterization of hyperactive variants of Pseudomonas aeruginosa MraY, the essential and conserved enzyme catalyzing the formation of the first lipid-linked PG precursor called lipid I. These variants result in the elevated production of the final PG precursor lipid II in cells and are hyperactive in a purified system. Amino acid substitutions within the activated MraY variants unexpectedly map to a cavity on the extracellular side of the dimer interface, far from the active site. Our structural evidence and molecular dynamics simulations suggest that the cavity is a binding site for lipid II molecules that have been transported to the outer leaflet of the membrane. Overall, our results support a model in which excess externalized lipid II allosterically inhibits MraY, providing a feedback mechanism to prevent the sequestration of lipid carrier in the PG biogenesis pathway. MraY belongs to the broadly distributed polyprenyl-phosphate N-acetylhexosamine 1-phosphate transferase (PNPT) superfamily of enzymes. We therefore propose that similar feedback mechanisms may be widely employed to coordinate precursor supply with demand by polymerases, thereby optimizing the partitioning of lipid carriers between competing glycan biogenesis pathways.

PLSCR1 is a cell-autonomous defence factor against SARS-CoV-2 infection

Understanding protective immunity to COVID-19 facilitates preparedness for future pandemics and combats new SARS-CoV-2 variants emerging in the human population. Neutralizing antibodies have been widely studied; however, on the basis of large-scale exome sequencing of protected versus severely ill patients with COVID-19, local cell-autonomous defence is also crucial1-4. Here we identify phospholipid scramblase 1 (PLSCR1) as a potent cell-autonomous restriction factor against live SARS-CoV-2 infection in parallel genome-wide CRISPR-Cas9 screens of human lung epithelia and hepatocytes before and after stimulation with interferon-γ (IFNγ). IFNγ-induced PLSCR1 not only restricted SARS-CoV-2 USA-WA1/2020, but was also effective against the Delta B.1.617.2 and Omicron BA.1 lineages. Its robust activity extended to other highly pathogenic coronaviruses, was functionally conserved in bats and mice, and interfered with the uptake of SARS-CoV-2 in both the endocytic and the TMPRSS2-dependent fusion routes. Whole-cell 4Pi single-molecule switching nanoscopy together with bipartite nano-reporter assays found that PLSCR1 directly targeted SARS-CoV-2-containing vesicles to prevent spike-mediated fusion and viral escape. A PLSCR1 C-terminal β-barrel domain-but not lipid scramblase activity-was essential for this fusogenic blockade. Our mechanistic studies, together with reports that COVID-associated PLSCR1 mutations are found in some susceptible people3,4, identify an anti-coronavirus protein that interferes at a late entry step before viral RNA is released into the host-cell cytosol.

Identification of conserved genomic signatures specific to Bifidobacterium species colonising the human gut

Bifidobacterium species are known for their ability to inhabit various habitats and are often regarded as the first colonisers of the human gut. In the present work, we have used comparative genomics to identify conserved genomic signatures specific to Bifidobacterium species associated with the human gut. Our approach discovered five genomic signatures with varying lengths and confidence. Among the predicted five signatures, a 1790 bp multi-drug resistance (MDR) signature was found to be remarkably specific to only those species that can colonise the human gut. The signature codes for a membrane transport protein belonging to the major facilitator superfamily (MFS) generally involved in MDR. Phylogenetic analyses of the MDR signature suggest a lineage-specific evolution of the MDR signature in bifidobacteria colonising the human gut. Functional annotation led to the discovery of two conserved domains in the protein; a catalytic MFS domain involved in the efflux of drugs and toxins, and a regulatory cystathionine-β-synthase (CBS) domain that can interact with adenosyl-carriers. Molecular docking simulation performed with the modelled tertiary structure of the MDR signature revealed the putative functional role of the covalently linked domains. The MFS domain displayed a high affinity towards various protein synthesis inhibitor antibiotics and human bile acids, whereas the C-terminally linked CBS domain exhibited favourable binding with molecular structures of ATP and AMP. Therefore, we believe that the predicted signature represents a niche-specific survival trait involved in bile and antibiotic resistance, imparting an adaptive advantage to the Bifidobacterium species colonising the human gut.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03492-4.

Supramolecular organization and dynamics of mannosylated phosphatidylinositol lipids in the mycobacterial plasma membrane

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), a disease that claims ~1.6 million lives annually. The current treatment regime is long and expensive, and missed doses contribute to drug resistance. Therefore, development of new anti-TB drugs remains one of the highest public health priorities. Mtb has evolved a complex cell envelope that represents a formidable barrier to antibiotics. The Mtb cell envelop consists of four distinct layers enriched for Mtb specific lipids and glycans. Although the outer membrane, comprised of mycolic acid esters, has been extensively studied, less is known about the plasma membrane, which also plays a critical role in impacting antibiotic efficacy. The Mtb plasma membrane has a unique lipid composition, with mannosylated phosphatidylinositol lipids (phosphatidyl-myoinositol mannosides, PIMs) comprising more than 50% of the lipids. However, the role of PIMs in the structure and function of the membrane remains elusive. Here, we used multiscale molecular dynamics (MD) simulations to understand the structure-function relationship of the PIM lipid family and decipher how they self-organize to shape the biophysical properties of mycobacterial plasma membranes. We assess both symmetric and asymmetric assemblies of the Mtb plasma membrane and compare this with residue distributions of Mtb integral membrane protein structures. To further validate the model, we tested known anti-TB drugs and demonstrated that our models agree with experimental results. Thus, our work sheds new light on the organization of the mycobacterial plasma membrane. This paves the way for future studies on antibiotic development and understanding Mtb membrane protein function.

Characterization and Expression Analysis of B12D-Like Gene From Pearl Millet

B12D-Like is a member of the B12D domain-containing protein family, which includes several transmembrane proteins in plants. In this study, the cDNA of PgB12D-Like from Pennisetum glaucum subsp. monodii (Maire) Brunken was sequenced and characterized. The 446-bp cDNA for PgB12D-Like encodes for a deduced protein of 95 amino acids. The PgB12D-Like protein contains a B12D domain and a transmembrane helix embedded in the mitochondrial membrane. Cis-regulatory elements analysis reveals binding sites for various transcription factors involved in responses to stress, light, and plant hormones in the putative promoter sequence for PgB12D-Like. Several proteins involved in floral organ development were also found to have binding sites in the PgB12D-Like promoter, such as agamous-like proteins and squamosa promoter binding proteins. Real-time PCR reveals high expression of PgB12D-Like in flowers during heading, whereas its expression in a 4-day-old seedling shoot was the lowest. Moreover, cold, drought, and heat stress were found to upregulate PgB12D-Like, whereas gibberellic acid downregulated its expression in seedlings. The present study helps to uncover the function of the B12D-Like in response to plant hormones and abiotic stress during P. glaucum development.

Dawn of a New Era for Membrane Protein Design

A major advancement has recently occurred in the ability to predict protein secondary structure from sequence using artificial neural networks. This new accessibility to high-quality predicted structures provides a big opportunity for the protein design community. It is particularly welcome for membrane protein design, where the scarcity of solved structures has been a major limitation of the field for decades. Here, we review the work done to date on the membrane protein design and set out established and emerging tools that can be used to most effectively exploit this new access to structures.

Membrane contact probability: An essential and predictive character for the structural and functional studies of membrane proteins

One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.

The distribution of residues on protein surfaces is largely determined by the surrounding environment. For soluble proteins, most of the residues on the outer surface are hydrophilic, and people use the quantity “solvent accessibility” to describe and predict these surface residues. In contrast, for membrane proteins that are embedded in a lipid bilayer, many of their surface residues are hydrophobic and membrane-contacting, but there is yet a widely-accepted quantity for the description or prediction of this characteristic property. Here, we propose a new quantity termed “membrane contact probability (MCP)”, which can be used to describe and predict the membrane-contacting surface residues of proteins. We also propose a machine learning-based method to predict MCP from protein sequences, utilizing the dataset generated by physics-based computer simulations. We demonstrate that a quantity such as MCP is helpful for protein structure prediction, and we believe that it will find broad applications in the structure and function studies of membrane proteins.

Spatial arrangement of proteins in planar and curved membranes by PPM 3.0

Cellular protrusions, invaginations, and many intracellular organelles have strongly curved membrane regions. Transmembrane and peripheral membrane proteins that induce, sense, or stabilize such regions cannot be properly fitted into a single flat bilayer. To treat such proteins, we developed a new method and a web tool, PPM 3.0, for positioning proteins in curved or planar, single or multiple membranes. This method determines the energetically optimal spatial position, the hydrophobic thickness, and the radius of intrinsic curvature of a membrane-deforming protein structure by arranging it in a single or several sphere-shaped or planar membrane sections. In addition, it can define the lipid-embedded regions of a protein that simultaneously spans several membranes or determine the optimal position of a peptide in a spherical micelle. The PPM 3.0 web server operates with 17 types of biological membranes and 4 types of artificial bilayers. It is publicly available at https://opm.phar.umich.edu/ppm_server3. PPM 3.0 was applied to identify and characterize arrangements in membranes of 128 proteins with a significant intrinsic curvature, such as BAR domains, annexins, Piezo, and MscS mechanosensitive channels, cation-chloride cotransporters, as well as mitochondrial ATP synthases, calcium uniporters, and TOM complexes. These proteins form large complexes that are mainly localized in mitochondria, plasma membranes, and endosomes. Structures of bacterial drug efflux pumps, AcrAB-TolC, MexAB-OrpM, and MacAB-TolC, were positioned in both membranes of the bacterial cell envelop, while structures of multimeric gap-junction channels were arranged in two opposed cellular membranes.

Interdependence of a mechanosensitive anion channel and glutamate receptors in distal wound signaling

Glutamate has dual roles in metabolism and signaling; thus, signaling functions must be isolatable and distinct from metabolic fluctuations, as seen in low-glutamate domains at synapses. In plants, wounding triggers electrical and calcium (Ca²⁺) signaling, which involve homologs of mammalian glutamate receptors. The hydraulic dispersal and squeeze-cell hypotheses implicate pressure as a key component of systemic signaling. Here, we identify the stretch-activated anion channel MSL10 as necessary for proper wound-induced electrical and Ca²⁺ signaling. Wound gene induction, genetics, and Ca²⁺ imaging indicate that MSL10 acts in the same pathway as the glutamate receptor–like proteins (GLRs). Analogous to mammalian NMDA glutamate receptors, GLRs may serve as coincidence detectors gated by the combined requirement for ligand binding and membrane depolarization, here mediated by stretch activation of MSL10. This study provides a molecular genetic basis for a role of mechanical signal perception and the transmission of long-distance electrical and Ca²⁺ signals in plants.

Positive selection on two mitochondrial coding genes and adaptation signals in hares (genus Lepus) from China

BACKGROUND

Animal mitochondria play a central role in energy production in the cells through the oxidative phosphorylation (OXPHOS) pathway. Recent studies of selection on different mitochondrial OXPHOS genes have revealed the adaptive implications of amino acid changes in these subunits. In hares, climatic variation and/or introgression were suggested to be at the origin of such adaptation. Here we looked for evidence of positive selection in three mitochondrial OXPHOS genes, using tests of selection, protein structure modelling and effects of amino acid substitutions on the protein function and stability. We also used statistical models to test for climate and introgression effects on sites under positive selection.

RESULTS

Our results revealed seven sites under positive selection in ND4 and three sites in Cytb. However, no sites under positive selection were observed in the COX1 gene. All three subunits presented a high number of codons under negative selection. Sites under positive selection were mapped on the tridimensional structure of the predicted models for the respective mitochondrial subunit. Of the ten amino acid replacements inferred to have evolved under positive selection for both subunits, six were located in the transmembrane domain. On the other hand, three codons were identified as sites lining proton translocation channels. Furthermore, four codons were identified as destabilizing with a significant variation of Δ vibrational entropy energy between wild and mutant type. Moreover, our PROVEAN analysis suggested that among all positively selected sites two fixed amino acid replacements altered the protein functioning. Our statistical models indicated significant effects of climate on the presence of ND4 and Cytb protein variants, but no effect by trans-specific mitochondrial DNA introgression, which is not uncommon in a number of hare species.

CONCLUSIONS

Positive selection was observed in several codons in two OXPHOS genes. We found that substitutions in the positively selected codons have structural and functional impacts on the encoded proteins. Our results are concordantly suggesting that adaptations have strongly affected the evolution of mtDNA of hare species with potential effects on the protein function. Environmental/climatic changes appear to be a major trigger of this adaptation, whereas trans-specific introgressive hybridization seems to play no major role for the occurrence of protein variants.

Representations of protein structure for exploring the conformational space: A speed-accuracy trade-off

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We compare ten structural representations, either atomistic or coarse-grained.

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Thus, ten distance-dependent statistical potentials of mean force (PMF) were built.

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The Cβ-only and Cα + Cβ representations provide the best speed–accuracy trade-off.

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Including glycines through Cα, in a Cβ-only representation, yields a higher accuracy.

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We generalize the conclusions to the total information gain (TIG) scoring function.

The recent breakthrough in the field of protein structure prediction shows the relevance of using knowledge-based based scoring functions in combination with a low-resolution 3D representation of protein macromolecules. The choice of not using all atoms is barely supported by any data in the literature, and is mostly motivated by empirical and practical reasons, such as the computational cost of assessing the numerous folds of the protein conformational space. Here, we present a comprehensive study, carried on a large and balanced benchmark of predicted protein structures, to see how different types of structural representations rank in either accuracy or calculation speed, and which ones offer the best compromise between these two criteria. We tested ten representations, including low-resolution, high-resolution, and coarse-grained approaches. We also investigated the generalization of the findings to other formalisms than the widely-used “potential of mean force” (PMF) method. Thus, we observed that representing protein structures by their β carbons—combined or not with Cα—provides the best speed–accuracy trade-off, when using a “total information gain” scoring function. For statistical PMFs, using MARTINI backbone and side-chains beads is the best option. Finally, we also demonstrated the necessity of training the reference state on all atom types, and of including the Cα atoms of glycine residues, in a Cβ-based representation.

Bovine seminal plasma osteopontin: Structural modelling, recombinant expression and its relationship with semen quality

Osteopontin (OPN) is a multifunctional phosphoprotein that has been linked to fertility in bulls. However, the exact mechanism by which OPN contributes to fertilisation is yet unknown. The biotechnological use of OPN in bovine reproduction is promising but some gaps remain unfilled. The present work aimed: (a) to verify whether the seminal plasma OPN is associated with seminal traits and a standard breeding soundness exam; (b) to predict OPN interactions with integrins, CD44 and glycosaminoglycans through molecular docking; and (c) to develop a protocol for recombinant expression of OPN from vesicular gland cDNA. Ejaculates from top ranked bulls had higher amounts of seminal plasma OPN in comparison with bulls classified as questionable (p < .01). The structural modelling and molecular docking predictions indicated that bovine OPN binds to heparin disaccharide, hyaluronic acid and hyaluronan. In addition, docking studies described the binding complexes of OPN with CD44 and the integrin heterodimers α5β1 and αVβ3. Finally, expression of rOPN-6His was successfully obtained after 3 hr of induction with 0.5 mM IPTG at 37°C and a denaturing purification protocol resulted in efficiently purified recombinant OPN. The present results contribute to the development of biotechnological uses of OPN as a biomarker in bovine reproduction.

Evaluating inositol phospholipid interactions with inward rectifier potassium channels and characterising their role in disease

Membrane proteins are frequently modulated by specific protein-lipid interactions. The activation of human inward rectifying potassium (hKir) channels by phosphoinositides (PI) has been well characterised. Here, we apply a coarse-grained molecular dynamics free-energy perturbation (CG-FEP) protocol to capture the energetics of binding of PI lipids to hKir channels. By using either a single- or multi-step approach, we establish a consistent value for the binding of PIP2 to hKir channels, relative to the binding of the bulk phosphatidylcholine phospholipid. Furthermore, by perturbing amino acid side chains on hKir6.2, we show that the neonatal diabetes mutation E179K increases PIP2 affinity, while the congenital hyperinsulinism mutation K67N results in a reduced affinity. We show good agreement with electrophysiological data where E179K exhibits a reduction in neomycin sensitivity, implying that PIP2 binds more tightly E179K channels. This illustrates the application of CG-FEP to compare affinities between lipid species, and for annotating amino acid residues.

An information gain-based approach for evaluating protein structure models

For three decades now, knowledge-based scoring functions that operate through the "potential of mean force" (PMF) approach have continuously proven useful for studying protein structures. Although these statistical potentials are not to be confused with their physics-based counterparts of the same name-i.e. PMFs obtained by molecular dynamics simulations-their particular success in assessing the native-like character of protein structure predictions has lead authors to consider the computed scores as approximations of the free energy. However, this physical justification is a matter of controversy since the beginning. Alternative interpretations based on Bayes' theorem have been proposed, but the misleading formalism that invokes the inverse Boltzmann law remains recurrent in the literature. In this article, we present a conceptually new method for ranking protein structure models by quality, which is (i) independent of any physics-based explanation and (ii) relevant to statistics and to a general definition of information gain. The theoretical development described in this study provides new insights into how statistical PMFs work, in comparison with our approach. To prove the concept, we have built interatomic distance-dependent scoring functions, based on the former and new equations, and compared their performance on an independent benchmark of 60,000 protein structures. The results demonstrate that our new formalism outperforms statistical PMFs in evaluating the quality of protein structural decoys. Therefore, this original type of score offers a possibility to improve the success of statistical PMFs in the various fields of structural biology where they are applied. The open-source code is available for download at https://gitlab.rpbs.univ-paris-diderot.fr/src/ig-score.

In silico virtual screening, characterization, docking and molecular dynamics studies of crucial SARS-CoV-2 proteins

The ongoing pandemic COVID-19 (COrona Virus Immuno Deficiency-2019) which is caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome–CoronaVirus-2) has emerged as a pandemic with 400,000 plus deaths till date. We do not have any drug or vaccine available for the inhibition of this deadly virus. The expedition for searching a potential drug or vaccine against COVID-19 will be of massive potential and favor. This study is focused on finding an effective natural origin compound which can put a check on the activity of this virus. We chose important proteins from the SARS-CoV-2 genome such as NSP4, NSP15 and RdRp along-with the human ACE2 receptor which is the first point of contact with the virus. Virtual screening and followed up molecular docking resulted in Baicalin and Limonin as the final lead molecules. 200 ns of MD simulation for each protein-ligand complex provides the insights that Baicalin has a potential to target NSP4, NSP15 and RdRp proteins. Limonin which is largely used in traditional Indian medicine system is found to inhibit the human ACE2 receptor (making it inefficient in binding to the receptor binding domain of SARS-CoV-2). Our studies propose Baicalin and Limonin in combination to be studied in vitro and in vivo against COVID-19.

Communicated by Ramaswamy H. Sarma

From sequence analysis of DPP-4 to molecular docking based searching of its inhibitors

Literature data suggests that Dipeptidyl peptidase-4 (DPP-4) is a potential target for type 2 Diabetes Mellitus. Therefore, it is of interest to identify new DPP-4 inhibitors using molecular docking analysis. We document compounds such as STOCK1N-98884, STOCK1N-98881, and STOCK1N-98866 with optimal binding features with DPP-4 from the ligand database at https://www.ibscreen.com/ for further consideration.

The effect of multiple simulation parameters on MM/PBSA performance for binding affinity prediction of CB1 cannabinoid receptor agonists and antagonists

Both the inactive- and active-state CB1 receptor crystal structures have now been solved, allowing their application in various structure-based drug design methods. One potential method utilizing these crystal structures is the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) method of predicting relative binding free.

The PSIPRED Protein Analysis Workbench: 20 years on

The PSIPRED Workbench is a web server offering a range of predictive methods to the bioscience community for 20 years. Here, we present the work we have completed to update the PSIPRED Protein Analysis Workbench and make it ready for the next 20 years. The main focus of our recent website upgrade work has been the acceleration of analyses in the face of increasing protein sequence database size. We additionally discuss any new software, the new hardware infrastructure, our webservices and web site. Lastly we survey updates to some of the key predictive algorithms available through our website.

Accelerated Molecular Dynamics Applied to the Peptaibol Folding Problem

The use of enhanced sampling molecular dynamics simulations to facilitate the folding of proteins is a relatively new approach which has quickly gained momentum in recent years. Accelerated molecular dynamics (aMD) can elucidate the dynamic path from the unfolded state to the near-native state, “flattened” by introducing a non-negative boost to the potential. Alamethicin F30/3 (Alm F30/3), chosen in this study, belongs to the class of peptaibols that are 7–20 residue long, non-ribosomally synthesized, amphipathic molecules that show interesting membrane perturbing activity. The recent studies undertaken on the Alm molecules and their transmembrane channels have been reviewed. Three consecutive simulations of ~900 ns each were carried out where N-terminal folding could be observed within the first 100 ns, while C-terminal folding could only be achieved almost after 800 ns. It took ~1 μs to attain the near-native conformation with stronger potential boost which may take several μs worth of classical MD to produce the same results. The Alm F30/3 hexamer channel was also simulated in an E. coli mimicking membrane under an external electric field that correlates with previous experiments. It can be concluded that aMD simulation techniques are suited to elucidate peptaibol structures and to understand their folding dynamics.

A comprehensive computational study of amino acid interactions in membrane proteins

Transmembrane proteins play a fundamental role in a wide series of biological processes but, despite their importance, they are less studied than globular proteins, essentially because their embedding in lipid membranes hampers their experimental characterization. In this paper, we improved our understanding of their structural stability through the development of new knowledge-based energy functions describing amino acid pair interactions that prevail in the transmembrane and extramembrane regions of membrane proteins. The comparison of these potentials and those derived from globular proteins yields an objective view of the relative strength of amino acid interactions in the different protein environments, and their role in protein stabilization. Separate potentials were also derived from α-helical and β-barrel transmembrane regions to investigate possible dissimilarities. We found that, in extramembrane regions, hydrophobic residues are less frequent but interactions between aromatic and aliphatic amino acids as well as aromatic-sulfur interactions contribute more to stability. In transmembrane regions, polar residues are less abundant but interactions between residues of equal or opposite charges or non-charged polar residues as well as anion-π interactions appear stronger. This shows indirectly the preference of the water and lipid molecules to interact with polar and hydrophobic residues, respectively. We applied these new energy functions to predict whether a residue is located in the trans- or extramembrane region, and obtained an AUC score of 83% in cross validation, which demonstrates their accuracy. As their application is, moreover, extremely fast, they are optimal instruments for membrane protein design and large-scale investigations of membrane protein stability.

MOLEonline: a web-based tool for analyzing channels, tunnels and pores (2018 update)

MOLEonline is an interactive, web-based application for the detection and characterization of channels (pores and tunnels) within biomacromolecular structures. The updated version of MOLEonline overcomes limitations of the previous version by incorporating the recently developed LiteMol Viewer visualization engine and providing a simple, fully interactive user experience. The application enables two modes of calculation: one is dedicated to the analysis of channels while the other was specifically designed for transmembrane pores. As the application can use both PDB and mmCIF formats, it can be leveraged to analyze a wide spectrum of biomacromolecular structures, e.g. stemming from NMR, X-ray and cryo-EM techniques. The tool is interconnected with other bioinformatics tools (e.g., PDBe, CSA, ChannelsDB, OPM, UniProt) to help both setup and the analysis of acquired results. MOLEonline provides unprecedented analytics for the detection and structural characterization of channels, as well as information about their numerous physicochemical features. Here we present the application of MOLEonline for structural analyses of α-hemolysin and transient receptor potential mucolipin 1 (TRMP1) pores. The MOLEonline application is freely available via the Internet at https://mole.upol.cz.

Networking of predicted post-translational modification (PTM) sites in human EGFR

Epidermal growth factor receptor (EGFR) binds to EGF activating tyrosine phosphorylation through receptor dimerization prompting uncontrolled multiplication. Domain organization, secondary structure combinations in motifs and interactome define such transitory changes responsible for the multi-functionality of human EGFR. We report the predicted phosphorylation sites on Ser, Thr and Tyr residues in addition to 74 auto-phosphorylation sites on Tyr in human EGFR. These data suggest a complex interplay between phosphorylation types for modification resulting in the modulation of human EGFR functionality. It is of further interest in future to thoroughly understand the associated data to clarify the various roles played by post translational modifications (PTM) in human EGFR.

PACKMOL-Memgen: A Simple-To-Use, Generalized Workflow for Membrane-Protein-Lipid-Bilayer System Building

We present PACKMOL-Memgen, a simple-to-use, generalized workflow for automated building of membrane-protein-lipid-bilayer systems based on open-source tools including Packmol, memembed, pdbremix, and AmberTools. Compared with web-interface-based related tools, PACKMOL-Memgen allows setup of multiple configurations of a system in a user-friendly and efficient manner within minutes. The generated systems are well-packed and thus well-suited as starting configurations in MD simulations under periodic boundary conditions, requiring only moderate equilibration times. PACKMOL-Memgen is distributed with AmberTools and runs on most computing platforms, and its output can also be used for CHARMM or adapted to other molecular-simulation packages.

Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation

The cellular membrane constitutes one of the most fundamental compartments of a living cell, where key processes such as selective transport of material and exchange of information between the cell and its environment are mediated by proteins that are closely associated with the membrane. The heterogeneity of lipid composition of biological membranes and the effect of lipid molecules on the structure, dynamics, and function of membrane proteins are now widely recognized. Characterization of these functionally important lipid-protein interactions with experimental techniques is however still prohibitively challenging. Molecular dynamics (MD) simulations offer a powerful complementary approach with sufficient temporal and spatial resolutions to gain atomic-level structural information and energetics on lipid-protein interactions. In this review, we aim to provide a broad survey of MD simulations focusing on exploring lipid-protein interactions and characterizing lipid-modulated protein structure and dynamics that have been successful in providing novel insight into the mechanism of membrane protein function.

Outer Membrane Proteins OmpA, FhuA, OmpF, EstA, BtuB, and OmpX Have Unique Lipopolysaccharide Fingerprints

The outer membrane of Gram-negative bacteria has a highly complex asymmetrical architecture, containing a mixture of phospholipids in the inner leaflet and almost exclusively lipopolysaccharide (LPS) molecules in the outer leaflet. In E. coli, the outer membrane contains a wide range of proteins with a β barrel architecture, that vary in size from the smallest having eight strands to larger barrels composed of 22 strands. Here we report coarse-grained molecular dynamics simulations of six proteins from the E. coli outer membrane OmpA, OmpX, BtuB, FhuA, OmpF, and EstA in a range of membrane environments, which are representative of the in vivo conditions for different strains of E. coli. We show that each protein has a unique pattern of interaction with the surrounding membrane, which is influenced by the composition of the protein, the level of LPS in the outer leaflet, and the differing mobilities of the lipids in the two leaflets of the membrane. Overall we present analyses from over 200 μs of simulation for each protein.

The MemProtMD database: a resource for membrane-embedded protein structures and their lipid interactions

Integral membrane proteins fulfil important roles in many crucial biological processes, including cell signalling, molecular transport and bioenergetic processes. Advancements in experimental techniques are revealing high resolution structures for an increasing number of membrane proteins. Yet, these structures are rarely resolved in complex with membrane lipids. In 2015, the MemProtMD pipeline was developed to allow the automated lipid bilayer assembly around new membrane protein structures, released from the Protein Data Bank (PDB). To make these data available to the scientific community, a web database (http://memprotmd.bioch.ox.ac.uk) has been developed. Simulations and the results of subsequent analysis can be viewed using a web browser, including interactive 3D visualizations of the assembled bilayer and 2D visualizations of lipid contact data and membrane protein topology. In addition, ensemble analyses are performed to detail conserved lipid interaction information across proteins, families and for the entire database of 3506 PDB entries. Proteins may be searched using keywords, PDB or Uniprot identifier, or browsed using classification systems, such as Pfam, Gene Ontology annotation, mpstruc or the Transporter Classification Database. All files required to run further molecular simulations of proteins in the database are provided.

Molecular Dynamics Simulations of Membrane Proteins: An Overview

Simulations of membrane proteins have been rising in popularity in the past decade. Advancements in technology and force fields made it possible to simulate behavior of membrane proteins. Membrane protein simulations can now be used as supporting evidence for experimental findings, for elucidating protein mechanisms, and validating protein crystal structures. Unrelated to experimental data, these simulations can also serve to investigate larger scale processes like protein sorting, protein-membrane interactions, and more. In this review, the history as well as the state-of-the-art methodologies in membrane protein simulations will be summarized. An emphasis will be put on how to set up the system and on the current models for the different components of the simulation system. An overview of the available tools for membrane protein simulation will be given, and current limitations and prospects will also be discussed.

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.

Comparing co-evolution methods and their application to template-free protein structure prediction

Motivation

Co-evolution methods have been used as contact predictors to identify pairs of residues that share spatial proximity. Such contact predictors have been compared in terms of the precision of their predictions, but there is no study that compares their usefulness to model generation.

Results

We compared eight different co-evolution methods for a set of ∼3500 proteins and found that metaPSICOV stage 2 produces, on average, the most precise predictions. Precision of all the methods is dependent on SCOP class, with most methods predicting contacts in all α and membrane proteins poorly. The contact predictions were then used to assist in de novo model generation. We found that it was not the method with the highest average precision, but rather metaPSICOV stage 1 predictions that consistently led to the best models being produced. Our modelling results show a correlation between the proportion of predicted long range contacts that are satisfied on a model and its quality. We used this proportion to effectively classify models as correct/incorrect; discarding decoys classified as incorrect led to an enrichment in the proportion of good decoys in our final ensemble by a factor of seven. For 17 out of the 18 cases where correct answers were generated, the best models were not discarded by this approach. We were also able to identify eight cases where no correct decoy had been generated.

Availability and Implementation

Data is available for download from: http://opig.stats.ox.ac.uk/resources.

Contact

saulo.deoliveira@dtc.ox.ac.uk

Supplimentary Information

Supplementary data are available at Bioinformatics online.

MyPMFs: a simple tool for creating statistical potentials to assess protein structural models

Evaluating the model quality of protein structures that evolve in environments with particular physicochemical properties requires scoring functions that are adapted to their specific residue compositions and/or structural characteristics. Thus, computational methods developed for structures from the cytosol cannot work properly on membrane or secreted proteins. Here, we present MyPMFs, an easy-to-use tool that allows users to train statistical potentials of mean force (PMFs) on the protein structures of their choice, with all parameters being adjustable. We demonstrate its use by creating an accurate statistical potential for transmembrane protein domains. We also show its usefulness to study the influence of the physical environment on residue interactions within protein structures. Our open-source software is freely available for download at https://github.com/bibip-impmc/mypmfs.

Crystal structure of undecaprenyl-pyrophosphate phosphatase and its role in peptidoglycan biosynthesis

As a protective envelope surrounding the bacterial cell, the peptidoglycan sacculus is a site of vulnerability and an antibiotic target. Peptidoglycan components, assembled in the cytoplasm, are shuttled across the membrane in a cycle that uses undecaprenyl-phosphate. A product of peptidoglycan synthesis, undecaprenyl-pyrophosphate, is converted to undecaprenyl-phosphate for reuse in the cycle by the membrane integral pyrophosphatase, BacA. To understand how BacA functions, we determine its crystal structure at 2.6 Å resolution. The enzyme is open to the periplasm and to the periplasmic leaflet via a pocket that extends into the membrane. Conserved residues map to the pocket where pyrophosphorolysis occurs. BacA incorporates an interdigitated inverted topology repeat, a topology type thus far only reported in transporters and channels. This unique topology raises issues regarding the ancestry of BacA, the possibility that BacA has alternate active sites on either side of the membrane and its possible function as a flippase.

Bacterial cell wall components are assembled in a transmembrane cycle that involves the membrane integral pyrophosphorylase, BacA. Here the authors solve the crystal structure of BacA which shows an interdigitated inverted topology repeat that hints towards a flippase function for BacA.

TMPL: a database of experimental and theoretical transmembrane protein models positioned in the lipid bilayer

Knowing the position of protein structures within the membrane is crucial for fundamental and applied research in the field of molecular biology. Only few web resources propose coordinate files of oriented transmembrane proteins, and these exclude predicted structures, although they represent the largest part of the available models. In this article, we present TMPL (http://www.dsimb.inserm.fr/TMPL/), a database of transmembrane protein structures (α-helical and β-sheet) positioned in the lipid bilayer. It is the first database to include theoretical models of transmembrane protein structures, making it a large repository with more than 11 000 entries. The TMPL database also contains experimentally solved protein structures, which are available as either atomistic or coarse-grained models. A unique feature of TMPL is the possibility for users to update the database by uploading, through an intuitive web interface, the membrane assignments they can obtain with our recent OREMPRO web server.

Intracellular allosteric antagonism of the CCR9 receptor

Chemokines and their G-protein-coupled receptors play a diverse role in immune defence by controlling the migration, activation and survival of immune cells. They are also involved in viral entry, tumour growth and metastasis and hence are important drug targets in a wide range of diseases. Despite very significant efforts by the pharmaceutical industry to develop drugs, with over 50 small-molecule drugs directed at the family entering clinical development, only two compounds have reached the market: maraviroc (CCR5) for HIV infection and plerixafor (CXCR4) for stem-cell mobilization. The high failure rate may in part be due to limited understanding of the mechanism of action of chemokine antagonists and an inability to optimize compounds in the absence of structural information. CC chemokine receptor type 9 (CCR9) activation by CCL25 plays a key role in leukocyte recruitment to the gut and represents a therapeutic target in inflammatory bowel disease. The selective CCR9 antagonist vercirnon progressed to phase 3 clinical trials in Crohn's disease but efficacy was limited, with the need for very high doses to block receptor activation. Here we report the crystal structure of the CCR9 receptor in complex with vercirnon at 2.8 Å resolution. Remarkably, vercirnon binds to the intracellular side of the receptor, exerting allosteric antagonism and preventing G-protein coupling. This binding site explains the need for relatively lipophilic ligands and describes another example of an allosteric site on G-protein-coupled receptors that can be targeted for drug design, not only at CCR9, but potentially extending to other chemokine receptors.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

OREMPRO web server: orientation and assessment of atomistic and coarse-grained structures of membrane proteins

: The experimental determination of membrane protein orientation within the lipid bilayer is extremely challenging, such that computational methods are most often the only solution. Moreover, obtaining all-atom 3D structures of membrane proteins is also technically difficult, and many of the available data are either experimental low-resolution structures or theoretical models, whose structural quality needs to be evaluated. Here, to address these two crucial problems, we propose OREMPRO, a web server capable of both (i) positioning α-helical and β-sheet transmembrane domains in the lipid bilayer and (ii) assessing their structural quality. Most importantly, OREMPRO uses the sole alpha carbon coordinates, which makes it the only web server compatible with both high and low structural resolutions. Finally, OREMPRO is also interesting in its ability to process coarse-grained protein models, by using coordinates of backbone beads in place of alpha carbons.

AVAILABILITY AND IMPLEMENTATION

http://www.dsimb.inserm.fr/OREMPRO/ CONTACT: : guillaume.postic@univ-paris-diderot.fr or jean-christophe.gelly@univ-paris-diderot.fr

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Efficient preparation and analysis of membrane and membrane protein systems

Molecular dynamics (MD) simulations have become a highly important technique to consider lipid membrane systems, and quite often they provide considerable added value to laboratory experiments. Rapid development of both software and hardware has enabled the increase of time and size scales reachable by MD simulations to match those attainable by several accurate experimental techniques. However, until recently, the quality and maturity of software tools available for building membrane models for simulations as well as analyzing the results of these simulations have seriously lagged behind. Here, we discuss the recent developments of such tools from the end-users' point of view. In particular, we review the software that can be employed to build lipid bilayers and other related structures with or without embedded membrane proteins to be employed in MD simulations. Additionally, we provide a brief critical insight into force fields and MD packages commonly used for membrane and membrane protein simulations. Finally, we list analysis tools that can be used to study the properties of membrane and membrane protein systems. In all these points we comment on the respective compatibility of the covered tools. We also share our opinion on the current state of the available software. We briefly discuss the most commonly employed tools and platforms on which new software can be built. We conclude the review by providing a few ideas and guidelines on how the development of tools can be further boosted to catch up with the rapid pace at which the field of membrane simulation progresses. This includes improving the compatibility between software tools and promoting the openness of the codes on which these applications rely. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

Membrane positioning for high- and low-resolution protein structures through a binary classification approach

The critical importance of algorithms for orienting proteins in the lipid bilayer stems from the extreme difficulty in obtaining experimental data about the membrane boundaries. Here, we present a computational method for positioning protein structures in the membrane, based on the sole alpha carbon coordinates and, therefore, compatible with both high and low structural resolutions. Our algorithm follows a new and simple approach, by treating the membrane assignment problem as a binary classification. Compared with the state-of-the-art algorithms, our method achieves similar accuracy, while being faster. Finally, our open-source software is also capable of processing coarse-grained models of protein structures.

Fast assessment of structural models of ion channels based on their predicted current-voltage characteristics

Computational prediction of protein structures is a difficult task, which involves fast and accurate evaluation of candidate model structures. We propose to enhance single-model quality assessment with a functionality evaluation phase for proteins whose quantitative functional characteristics are known. In particular, this idea can be applied to evaluation of structural models of ion channels, whose main function - conducting ions - can be quantitatively measured with the patch-clamp technique providing the current-voltage characteristics. The study was performed on a set of KcsA channel models obtained from complete and incomplete contact maps. A fast continuous electrodiffusion model was used for calculating the current-voltage characteristics of structural models. We found that the computed charge selectivity and total current were sensitive to structural and electrostatic quality of models. In practical terms, we show that evaluating predicted conductance values is an appropriate method to eliminate models with an occluded pore or with multiple erroneously created pores. Moreover, filtering models on the basis of their predicted charge selectivity results in a substantial enrichment of the candidate set in highly accurate models. Tests on three other ion channels indicate that, in addition to being a proof of the concept, our function-oriented single-model quality assessment method can be directly applied to evaluation of structural models of some classes of protein channels. Finally, our work raises an important question whether a computational validation of functionality should be included in the evaluation process of structural models, whenever possible.

Assembly of the MHC I peptide-loading complex determined by a conserved ionic lock-switch

Salt bridges in lipid bilayers play a decisive role in the dynamic assembly and downstream signaling of the natural killer and T-cell receptors. Here, we describe the identification of an inter-subunit salt bridge in the membrane within yet another key component of the immune system, the peptide-loading complex (PLC). The PLC regulates cell surface presentation of self-antigens and antigenic peptides via molecules of the major histocompatibility complex class I. We demonstrate that a single salt bridge in the membrane between the transporter associated with antigen processing TAP and the MHC I-specific chaperone tapasin is essential for the assembly of the PLC and for efficient MHC I antigen presentation. Molecular modeling and all-atom molecular dynamics simulations suggest an ionic lock-switch mechanism for the binding of TAP to tapasin, in which an unfavorable uncompensated charge in the ER-membrane is prevented through complex formation. Our findings not only deepen the understanding of the interaction network within the PLC, but also provide evidence for a general interaction principle of dynamic multiprotein membrane complexes in immunity.

Determining the N-terminal orientations of recombinant transmembrane proteins in the Escherichia coli plasma membrane

In silico algorithms have been the common approach for transmembrane (TM) protein topology prediction. However, computational tools may produce questionable results and experimental validation has proven difficult. Although biochemical strategies are available to determine the C-terminal orientation of TM proteins, experimental strategies to determine the N-terminal orientation are still limited but needed because the N-terminal end is essential for membrane targeting. Here, we describe a new and easy method to effectively determine the N-terminal orientation of the target TM proteins in Escherichia coli plasma membrane environment. D94N, the mutant of bacteriorhodopsin from Haloarcula marismortui, can be a fusion partner to increase the production of the target TM proteins if their N-termini are in cytoplasm (Nin orientation). To create a suitable linker for orientating the target TM proteins with the periplasmic N-termini (Nout orientation) correctly, we designed a three-TM-helix linker fused at the C-terminus of D94N fusion partner (termed D94N-3TM) and found that D94N-3TM can specifically improve the production of the Nout target TM proteins. In conclusion, D94N and D94N-3TM fusion partners can be applied to determine the N-terminal end of the target TM proteins oriented either Nin or Nout by evaluating the net expression of the fusion proteins.