Computational design of a water-soluble analog of phospholamban

Design of a water-soluble transmembrane receptor kinase with intact molecular function by QTY code

Membrane proteins are critical to biological processes and central to life sciences and modern medicine. However, membrane proteins are notoriously challenging to study, mainly owing to difficulties dictated by their highly hydrophobic nature. Previously, we reported QTY code, which is a simple method for designing water-soluble membrane proteins. Here, we apply QTY code to a transmembrane receptor, histidine kinase CpxA, to render it completely water-soluble. The designed CpxAQTY exhibits expected biophysical properties and highly preserved native molecular function, including the activities of (i) autokinase, (ii) phosphotransferase, (iii) phosphatase, and (iv) signaling receptor, involving a water-solubilized transmembrane domain. We probe the principles underlying the balance of structural stability and activity in the water-solubilized transmembrane domain. Computational approaches suggest that an extensive and dynamic hydrogen-bond network introduced by QTY code and its flexibility may play an important role. Our successful functional preservation further substantiates the robustness and comprehensiveness of QTY code.

ProRefiner: an entropy-based refining strategy for inverse protein folding with global graph attention

Inverse Protein Folding (IPF) is an important task of protein design, which aims to design sequences compatible with a given backbone structure. Despite the prosperous development of algorithms for this task, existing methods tend to rely on noisy predicted residues located in the local neighborhood when generating sequences. To address this limitation, we propose an entropy-based residue selection method to remove noise in the input residue context. Additionally, we introduce ProRefiner, a memory-efficient global graph attention model to fully utilize the denoised context. Our proposed method achieves state-of-the-art performance on multiple sequence design benchmarks in different design settings. Furthermore, we demonstrate the applicability of ProRefiner in redesigning Transposon-associated transposase B, where six out of the 20 variants we propose exhibit improved gene editing activity.

Protein Design: From the Aspect of Water Solubility and Stability

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Hiding in plain sight: three chemically distinct α-helix types

Linus Pauling in 1950 published a three-dimensional model for a universal protein secondary structure motif which he initially called the alpha-spiral. Jack Dunitz, then a postdoc in Pauling's lab suggested to Pauling that the term helix is more accurate than spiral when describing the right-handed peptide and protein coiled structures. Pauling agreed, hence the rise of the alpha-helix, and, by extension, the ‘double helix’ structure of DNA. Although structural biologists and protein chemists are familiar with varying polar and apolar characters of amino acids in alpha-helices, to non-experts the three chemically distinct alpha-helix types classified here may hide in plain sight.

Computational Design of Homotetrameric Peptide Bundle Variants Spanning a Wide Range of Charge States

With the ability to design their sequences and structures, peptides can be engineered to realize a wide variety of functionalities and structures. Herein, computational design was used to identify a set of 17 peptides having a wide range of putative charge states but the same tetrameric coiled-coil bundle structure. Calculations were performed to identify suitable locations for ionizable residues (D, E, K, and R) at the bundle's exterior sites, while interior hydrophobic interactions were retained. The designed bundle structures spanned putative charge states of -32 to +32 in units of electron charge. The peptides were experimentally investigated using spectroscopic and scattering techniques. Thermal stabilities of the bundles were investigated using circular dichroism. Molecular dynamics simulations assessed structural fluctuations within the bundles. The cylindrical peptide bundles, 4 nm long by 2 nm in diameter, were covalently linked to form rigid, micron-scale polymers and characterized using transmission electron microscopy. The designed suite of sequences provides a set of readily realized nanometer-scale structures of tunable charge that can also be polymerized to yield rigid-rod polyelectrolytes.

A sequence space search engine for computational protein design to modulate molecular functionality

De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma.

Principles and Methods in Computational Membrane Protein Design

After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.

The G protein coupled receptor CXCR4 designed by the QTY code becomes more hydrophilic and retains cell signaling activity

G protein-coupled receptors (GPCRs) are vital for diverse biological functions, including vision, smell, and aging. They are involved in a wide range of diseases, and are among the most important targets of medicinal drugs. Tools that facilitate GPCR studies or GPCR-based technologies or therapies are thus critical to develop. Here we report using our QTY (glutamine, threonine, tyrosine) code to systematically replace 29 membrane-facing leucine, isoleucine, valine, and phenylalanine residues in the transmembrane α-helices of the GPCR CXCR4. This variant, CXCR4^QTY29, became more hydrophilic, while retaining the ability to bind its ligand CXCL12. When transfected into HEK293 cells, it inserted into the cell membrane, and initiated cellular signaling. This QTY code has the potential to improve GPCR and membrane protein studies by making it possible to design functional hydrophilic receptors. This tool can be applied to diverse α-helical membrane proteins, and may aid in the development of other applications, including clinical therapies.

ProDCoNN: Protein design using a convolutional neural network

Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C _α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets.

Surface patches on recombinant erythropoietin predict protein solubility: engineering proteins to minimise aggregation

BACKGROUND

Protein solubility characteristics are important determinants of success for recombinant proteins in relation to expression, purification, storage and administration. Escherichia coli offers a cost-efficient expression system. An important limitation, whether for biophysical studies or industrial-scale production, is the formation of insoluble protein aggregates in the cytoplasm. Several strategies have been implemented to improve soluble expression, ranging from modification of culture conditions to inclusion of solubility-enhancing tags.

RESULTS

Surface patch analysis has been applied to predict amino acid changes that can alter the solubility of expressed recombinant human erythropoietin (rHuEPO) in E. coli, a factor that has importance for both yield and subsequent downstream processing of recombinant proteins. A set of rHuEPO proteins (rHuEPO E13K, F48D, R150D, and F48D/R150D) was designed (from the framework of wild-type protein, rHuEPO WT, via amino acid mutations) that varied in terms of positively-charged patches. A variant predicted to promote aggregation (rHuEPO E13K) decreased solubility significantly compared to rHuEPO WT. In contrast, variants predicted to diminish aggregation (rHuEPO F48D, R150D, and F48D/R150D) increased solubility up to 60% in relation to rHuEPO WT.

CONCLUSIONS

These findings are discussed in the wider context of biophysical calculations applied to the family of EPO orthologues, yielding a diverse range of calculated values. It is suggested that combining such calculations with naturally-occurring sequence variation, and 3D model generation, could lead to a valuable tool for protein solubility design.

Membrane protein engineering to the rescue

The inherent hydrophobicity of membrane proteins is a major barrier to membrane protein research and understanding. Their low stability and solubility in aqueous environments coupled with poor expression levels make them a challenging area of research. For many years, the only way of working with membrane proteins was to optimise the environment to suit the protein, through the use of different detergents, solubilising additives, and other adaptations. However, with innovative protein engineering methodologies, the membrane proteins themselves are now being adapted to suit the environment. This mini-review looks at the types of adaptations which are applied to membrane proteins from a variety of different fields, including water solubilising fusion tags, thermostabilising mutation screening, scaffold proteins, stabilising protein chimeras, and isolating water-soluble domains.

QTY code enables design of detergent-free chemokine receptors that retain ligand-binding activities

Structure and function studies of membrane proteins, particularly G protein-coupled receptors and multipass transmembrane proteins, require detergents. We have devised a simple tool, the QTY code (glutamine, threonine, and tyrosine), for designing hydrophobic domains to become water soluble without detergents. Here we report using the QTY code to systematically replace the hydrophobic amino acids leucine, valine, isoleucine, and phenylalanine in the seven transmembrane α-helices of CCR5, CXCR4, CCR10, and CXCR7. We show that QTY code-designed chemokine receptor variants retain their thermostabilities, α-helical structures, and ligand-binding activities in buffer and 50% human serum. CCR5QTY, CXCR4QTY, and CXCR7QTY also bind to HIV coat protein gp41-120. Despite substantial transmembrane domain changes, the detergent-free QTY variants maintain stable structures and retain their ligand-binding activities. We believe the QTY code will be useful for designing water-soluble variants of membrane proteins and other water-insoluble aggregated proteins.

The Framework of Computational Protein Design

Computational protein design (CPD) has established itself as a leading field in basic and applied science with a strong coupling between the two. Proteins are computationally designed from the level of amino acids to the level of a functional protein complex. Design targets range from increased thermo- (or other) stability to specific requested reactions such as protein-protein binding, enzymatic reactions, or nanotechnology applications. The design scheme may encompass small regions of the proteins or the entire protein. In either case, the design may aim at the side-chains or at the full backbone conformation. Herein, the main framework for the process is outlined highlighting key elements in the CPD iterative cycle. These include the very definition of CPD, the diverse goals of CPD, components of the CPD protocol, methods for searching sequence and structure space, scoring functions, and augmenting the CPD with other optimization tools. Taken together, this chapter aims to introduce the framework of CPD.

Achievements and Challenges in Computational Protein Design

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

Empirical estimation of local dielectric constants: Toward atomistic design of collagen mimetic peptides

One of the key challenges in modeling protein energetics is the treatment of solvent interactions. This is particularly important in the case of peptides, where much of the molecule is highly exposed to solvent due to its small size. In this study, we develop an empirical method for estimating the local dielectric constant based on an additive model of atomic polarizabilities. Calculated values match reported apparent dielectric constants for a series of Staphylococcus aureus nuclease mutants. Calculated constants are used to determine screening effects on Coulombic interactions and to determine solvation contributions based on a modified Generalized Born model. These terms are incorporated into the protein modeling platform protCAD, and benchmarked on a data set of collagen mimetic peptides for which experimentally determined stabilities are available. Computing local dielectric constants using atomistic protein models and the assumption of additive atomic polarizabilities is a rapid and potentially useful method for improving electrostatics and solvation calculations that can be applied in the computational design of peptides.

Computational redesign of the lipid-facing surface of the outer membrane protein OmpA

Advances in computational design methods have made possible extensive engineering of soluble proteins, but designed β-barrel membrane proteins await improvements in our understanding of the sequence determinants of folding and stability. A subset of the amino acid residues of membrane proteins interact with the cell membrane, and the design rules that govern this lipid-facing surface are poorly understood. We applied a residue-level depth potential for β-barrel membrane proteins to the complete redesign of the lipid-facing surface of Escherichia coli OmpA. Initial designs failed to fold correctly, but reversion of a small number of mutations indicated by backcross experiments yielded designs with substitutions to up to 60% of the surface that did support folding and membrane insertion.

Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins

We present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of soluble proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with respective reference structures and all-atom molecular dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their molecular interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resolution. An efficient and robust heuristic algorithm based on particle swarm optimization is used for the derivation of CG parameters via a force-matching procedure. The ability of this protocol to deal with high dimensional search spaces suggests that the extension of this optimization procedure to larger data sets may lead to the generation of a fully transferable CG force field. At the present stage, these electrostatic-consistent CG potentials are easily and efficiently parametrized, show a good degree of transferability, and can be used to simulate soluble proteins or, more interestingly, large macromolecular assemblies for which long all-atom simulations may not be easily affordable.

Solubilization and humanization of paraoxonase-1

Paraoxonase-1 (PON1) is a serum protein, the activity of which is related to susceptibility to cardiovascular disease and intoxication by organophosphorus (OP) compounds. It may also be involved in innate immunity, and it is a possible lead molecule in the development of a catalytic bioscavenger of OP pesticides and nerve agents. Human PON1 expressed in E. coli is mostly found in the insoluble fraction, which motivated the engineering of soluble variants, such as G2E6, with more than 50 mutations from huPON1. We examined the effect on the solubility, activity, and stability of three sets of mutations designed to solubilize huPON1 with fewer overall changes: deletion of the N-terminal leader, polar mutations in the putative HDL binding site, and selection of the subset of residues that became more polar in going from huPON1 to G2E6. All three sets of mutations increase the solubility of huPON1; the HDL-binding mutant has the largest effect on solubility, but it also decreases the activity and stability the most. Based on the G2E6 polar mutations, we “humanized” an engineered variant of PON1 with high activity against cyclosarin (GF) and found that it was still very active against GF with much greater similarity to the human sequence.

Computational design of intermolecular stability and specificity in protein self-assembly

The ability to engineer novel proteins using the principles of molecular structure and energetics is a stringent test of our basic understanding of how proteins fold and maintain structure. The design of protein self-assembly has the potential to impact many fields of biology from molecular recognition to cell signaling to biomaterials. Most progress in computational design of protein self-assembly has focused on α-helical systems, exploring ways to concurrently optimize the stability and specificity of a target state. Applying these methods to collagen self-assembly is very challenging, due to fundamental differences in folding and structure of α- versus triple-helices. Here, we explore various computational methods for designing stable and specific oligomeric systems, with a focus on α-helix and collagen self-assembly.

Amino acid contribution to protein solubility: Asp, Glu, and Ser contribute more favorably than the other hydrophilic amino acids in RNase Sa

Poor protein solubility is a common problem in high-resolution structural studies, formulation of protein pharmaceuticals, and biochemical characterization of proteins. One popular strategy to improve protein solubility is to use site-directed mutagenesis to make hydrophobic to hydrophilic mutations on the protein surface. However, a systematic investigation of the relative contributions of all 20 amino acids to protein solubility has not been done. Here, 20 variants at the completely solvent-exposed position 76 of ribonuclease (RNase) Sa are made to compare the contributions of each amino acid. Stability measurements were also made for these variants, which occur at the i+1 position of a type II beta-turn. Solubility measurements in ammonium sulfate solutions were made at high positive net charge, low net charge, and high negative net charge. Surprisingly, there was a wide range of contributions to protein solubility even among the hydrophilic amino acids. The results suggest that aspartic acid, glutamic acid, and serine contribute significantly more favorably than the other hydrophilic amino acids especially at high net charge. Therefore, to increase protein solubility, asparagine, glutamine, or threonine should be replaced with aspartic acid, glutamic acid or serine.

Energetic determinants of oligomeric state specificity in coiled coils

The coiled coil is one of the simplest and best-studied protein structural motifs, consisting of two to five helices wound around each other. Empirical rules have been established on the tendency of different core sequences to form a certain oligomeric state but the physical forces behind this specificity are unclear. In this work, we model four sequences onto the structures of dimeric, trimeric, tetrameric, and pentameric coiled coils. We first examine the ability of an effective energy function (EEF1.1) to discriminate the correct oligomeric state for a given sequence. We find that inclusion of the translational, rotational, and side-chain conformational entropy is necessary for discriminating the native structures from their misassembled counterparts. The decomposition of the effective energy into residue contributions yields theoretical values for the oligomeric propensity of different residue types at different heptad positions. We find that certain calculated residue propensities are general and consistent with existing rules. For example, leucine at d favors dimers, leucine at a favors tetramers or pentamers, and isoleucine at a favors trimers. Other residue propensities are sequence context dependent. For example, glutamine at d favors trimers in one context and pentamers in another. Charged residues at e and g positions usually destabilize higher oligomers due to higher desolvation. Nonpolar residues at these positions confer pentamer specificity when combined with certain residues at positions a and d. Specifically, the pair Leua-Alag' or the inverse was found to stabilize the pentamer. The small energy gap between the native and misfolded counterparts explains why a few mutations at the core sites are sufficient to induce a change in the oligomeric state of these peptides. A large number of possible experiments are suggested by these results.

Structure of anti-FLAG M2 Fab domain and its use in the stabilization of engineered membrane proteins

The inherent difficulties of stabilizing detergent-solubilized integral membrane proteins for biophysical or structural analysis demand the development of new methodologies to improve success rates. One proven strategy is the use of antibody fragments to increase the ;soluble' portion of any membrane protein, but this approach is limited by the difficulties and expense associated with producing monoclonal antibodies to an appropriate exposed epitope on the target protein. Here, the stabilization of a detergent-solubilized K(+) channel protein, KvPae, by engineering a FLAG-binding epitope into a known loop region of the protein and creating a complex with Fab fragments from commercially available anti-FLAG M2 monoclonal antibodies is reported. Although well diffracting crystals of the complex have not yet been obtained, during the course of crystallization trials the structure of the anti-FLAG M2 Fab domain was solved to 1.86 A resolution. This structure, which should aid future structure-determination efforts using this approach by facilitating molecular-replacement phasing, reveals that the binding pocket appears to be specific only for the first four amino acids of the traditional FLAG epitope, namely DYKD. Thus, the use of antibody fragments for improving the stability of target proteins can be rapidly applied to the study of membrane-protein structure by placing the short DKYD motif within a predicted peripheral loop of that protein and utilizing commercially available anti-FLAG M2 antibody fragments.

Knowledge-based potentials in protein design

Knowledge-based potentials are statistical parameters derived from databases of known protein properties that empirically capture aspects of the physical chemistry of protein structure and function. These potentials play a key role in protein design by improving the accuracy of physics-based models of interatomic interactions and enhancing the computational efficiency of the design process by limiting the complexity of searching sequence space. Recently, knowledge-based potentials (in isolation or in combination with physics-based potentials) have been applied to the modification of existing protein function, the redesign of natural protein folds and the complete design of a non-natural protein fold. In addition, knowledge-based potentials appear to be providing important information about the global topology of amino acid interactions in natural proteins. A detailed study of the methods and products of these protein design efforts promises to greatly expand our understanding of proteins and the evolutionary process that created them.

Coiled coils at the edge of configurational heterogeneity. Structural analyses of parallel and antiparallel homotetrameric coiled coils reveal configurational sensitivity to a single solvent-exposed amino acid substitution

A detailed understanding of the mechanisms by which particular amino acid sequences can give rise to more than one folded structure, such as for proteins that undergo large conformational changes or misfolding, is a long-standing objective of protein chemistry. Here, we describe the crystal structures of a single coiled-coil peptide in distinct parallel and antiparallel tetrameric configurations and further describe the parallel or antiparallel crystal structures of several related peptide sequences; the antiparallel tetrameric assemblies represent the first crystal structures of GCN4-derived peptides exhibiting such a configuration. Intriguingly, substitution of a single solvent-exposed residue enabled the parallel coiled-coil tetramer GCN4-pLI to populate the antiparallel configuration, suggesting that the two configurations are close enough in energy for subtle sequence changes to have important structural consequences. We present a structural analysis of the small changes to the helix register and side-chain conformations that accommodate the two configurations and have supplemented these results using solution studies and a molecular dynamics energetic analysis using a replica exchange methodology. Considering the previous examples of structural nonspecificity in coiled-coil peptides, the findings reported here not only emphasize the predisposition of the coiled-coil motif to adopt multiple configurations but also call attention to the associated risk that observed crytstal structures may not represent the only (or even the major) species present in solution.

Molecular Dynamics Simulation of WSK-3, a Computationally Designed, Water-Soluble Variant of the Integral Membrane Protein KcsA

Poor solubility and low expression levels often make membrane proteins difficult to study. An alternative to the use of detergents to solubilize these aggregation-prone proteins is the partial redesign of the sequence so as to confer water solubility. Recently, computationally assisted membrane protein solubilization (CAMPS) has been reported, where exposed hydrophobic residues on a protein's surface are computationally redesigned. Herein, the structure and fluctuations of a designed, water-soluble variant of KcsA (WSK-3) were studied using molecular dynamics simulations. The root mean square deviation of the protein from its starting structure, where the backbone coordinates are those of KcsA, was 1.8 angstroms. The structure of salt bridges involved in structural specificity and solubility were examined. The preferred configuration of ions and water in the selectivity filter of WSK-3 was consistent with the reported preferences for KcsA. The structure of the selectivity filter was maintained, which is consistent with WSK-3 having an affinity for agitoxin2 comparable to that of wild-type KcsA. In contrast to KcsA, the central cavity's side chains were observed to reorient, allowing water diffusion through the side of the cavity wall. These simulations provide an atomistic analysis of the CAMPS strategy and its implications for further investigations of membrane proteins.

X-ray structure of a water-soluble analog of the membrane protein phospholamban: sequence determinants defining the topology of tetrameric and pentameric coiled coils

Phospholamban (PLB) is a pentameric transmembrane protein that regulates the Ca(2+)-dependent ATPase SERCA2a in sarcoplasmic reticulum membranes. We previously described the computational design of a water-soluble variant of phospholamban, WSPLB, which reproduced many of the structural and functional properties of the native membrane-soluble protein. While the full-length WSPLB forms a pentamer in solution, a truncated variant forms very stable tetramers. To obtain insight into the tetramer-pentamer cytoplasmic switch, we solved the crystal structure of the truncated construct, WSPLB 21-52. This peptide has a heptad sequence repeat with Leu residues at a- and Ile at d-positions from residues 31-52. The crystal structure revealed that WSPLB 21-52 adopted an antiparallel tetrameric coiled coil. This topology contrasts with the parallel topology of an analogue of the coiled-coil of GCN4 with the same Leu(a) Ile(d) repeat. Analysis of these structures revealed how the nature of the partially exposed residues at e- and g-positions influence the topology formed by the bundle. We also constructed a model for the pentameric form of PLB using the coiled-coil parameters derived from a single monomer in the tetrameric structure. This model suggests that both buried and interfacial hydrogen bonds are important for stabilizing the parallel pentamer.

Redesigning an integral membrane K+ channel into a soluble protein

Even though the structure determination of soluble proteins has become routine, the number of unrelated integral membrane protein structures remains at a few dozen. The importance of this class of proteins to the molecular mechanisms underlying numerous biological phenomena demands that novel experimental techniques be developed to overcome the limitations imposed by conventional detergent-dependent approaches. Here we report the re-engineering of a putative K+ channel protein of unknown structure into a water-soluble analogue. By analyzing evolutionary conservation patterns of related sequences, lipid-facing residues of the primitive channel were identified and mutagenized into more polar alternatives. Further stabilization of the resultant construct was achieved through fusion with maltose-binding protein. The final soluble protein forms a tetramer, suggesting that it accurately models its predecessor. This methodology, as a viable alternative to the use of detergents, should be applicable to a wide range of integral membrane protein families including transporters and other signal transducers.

De novo design of a pentameric coiled-coil: decoding the motif for tetramer versus pentamer formation in water-soluble phospholamban*

Water-soluble phospholamban (WSPLB) is a designed, water-soluble analogue of the pentameric membrane protein phospholamban (PLB), which contains the same core and interhelical residues as PLB, with only the solvent-exposed positions mutated. WSPLB contains the same secondary and quaternary structure as PLB. The hydrophobic cores of PLB and WSPLB contain Leu and Ile at the a- and d-positions of a heptad repeat (abcdefg) from residues 31-52, while residues 21-30 are rich in polar amino acids at these positions. While the full-length WSPLB forms pentamers in solution, truncated peptides lacking residues 21-30 are largely tetrameric. Thus, truncation of residues 1-20 promotes a switch from pentamer to tetramer formation. Here, the motifs for WSPLB pentamerization were elucidated by characterizing a series of peptides, which were progressively truncated in this polar 'switch' region. When fully present, the 'switch' region promotes pentamer formation in WSPLB, by destabilizing a more stable tetrameric species which exists in its absence. We find that the burial of hydrogen bonding residues from 21 to 30 drives WSPLB from a tetramer to a pentamer, with direct implications for coiled-coil design.

Conversion of a mechanosensitive channel protein from a membrane-embedded to a water-soluble form by covalent modification with amphiphiles

Covalent modification of integral membrane proteins with amphiphiles may provide a general approach to the conversion of membrane proteins into water-soluble forms for biophysical and high-resolution structural studies. To test this approach, we mutated four surface residues of the pentameric Mycobacterium tuberculosis mechanosensitive channel of large conductance (MscL) to cysteine residues as anchors for amphiphile attachment. A series of modified ion channels with four amphiphile groups attached per channel subunit was prepared. One construct showed the highest water solubility to a concentration of up to 4mg/ml in the absence of detergent. This analog also formed native-like, alpha-helical homo-pentamers in the absence of detergent as judged by circular dichroism spectroscopy, size-exclusion chromatography and various light-scattering techniques. Proteins with longer, or shorter polymers attached, or proteins modified exclusively with polar cysteine-reactive small molecules, exhibited reduced to no solubility and higher-order aggregation. Electron microscopy revealed a homogeneous population of particles consistent with a pentameric channel. Solubilization of membrane proteins by covalent attachment of amphiphiles results in homogeneous particles that may prove useful for crystallization, solution NMR spectroscopy, and electron microscopy.

Advances in computational protein design

Computational protein design continues to experience a variety of methodological advances. Several improvements have been suggested for the objective functions used to quantify sequence/structure compatibility. Disparate design strategies based upon dead-end elimination, simulated annealing and statistical design have each recently yielded striking successes involving de novo designed proteins with sizes on the order of 100 residues or greater. Such methods may be used to design new proteins, as well as to redesign natural proteins to facilitate structural and biophysical studies.

Computational design of water-soluble analogues of the potassium channel KcsA

Although the interiors of membrane and water-soluble proteins are similar in their physicochemical properties, membrane proteins differ in having larger fractions of hydrophobic residues on their exteriors. Thus, it should be possible to water-solubilize membrane proteins by mutating their lipid-contacting side chains to more polar groups. Here, a computational approach was used to generate water-soluble variants of the potassium channel KcsA. As a probe of the correctness of the fold, the proteins contain an agitoxin2 binding site from a mammalian homologue of the channel. The resulting proteins express in high yield in Escherichia coli and share the intended functional and structural properties with KcsA, including secondary structure, tetrameric quaternary structure, and tight specific binding to both agitoxin2 and a small molecule channel blocker.

Spatial and dynamic interactions between phospholamban and the canine cardiac Ca2+ pump revealed with use of heterobifunctional cross-linking agents

Heterobifunctional thiol to amine cross-linking agents were used to gain new insights on the dynamics and conformational factors governing the interaction between the cardiac Ca2+ pump (SERCA2a) and phospholamban (PLB). PLB is a small protein inhibitor of SERCA2a that reduces enzyme affinity for Ca2+ and thereby regulates cardiac contractility. We found that the PLB monomer with Asn27 or Asn30 changed to Cys (N27C-PLB or N30C-PLB) cross-linked to lysine of SERCA2a within seconds with > or =80% efficiency. Optimal cross-linking occurred at spacer chain lengths of 10 and 15 A for N27C and N30C, respectively. The rapid time course of cross-linking indicated that neither dissociation of PLB pentamers nor binding of PLB monomers to SERCA2a was rate-limiting. Cross-linking occurred only to the E2 (Ca2+-free) conformation of SERCA2a, was strongly favored by nucleotide binding to this state, and was completely inhibited by thapsigargin. Protein sequencing in combination with mutagenesis identified of Lys328 of SERCA2a as the target of cross-linking. A three-dimensional map of interacting residues indicated that the cross-linking distances were entirely compatible with the 10-A distance recently determined between N30C of PLB and Cys318 of SERCA2a. In contrast, Lys3 of PLB did not cross-link to any Lys (or Cys) of SERCA2a, suggesting that previous three-dimensional models that constrain Lys3 near residues 397-400 of thapsigargin-inhibited SERCA2a should be viewed with caution. Furthermore, although earlier models of PLB.SERCA2a are based on thapsigargin-bound SERCA, our results suggest that the nucleotide-bound, E2 conformation is substantially different and represents the key conformational state for interacting with PLB.