Computational design of membrane proteins

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.

Supramolecular assembly of protein building blocks: from folding to function

Several phenomena occurring throughout the life of living things start and end with proteins. Various proteins form one complex structure to control detailed reactions. In contrast, one protein forms various structures and implements other biological phenomena depending on the situation. The basic principle that forms these hierarchical structures is protein self-assembly. A single building block is sufficient to create homogeneous structures with complex shapes, such as rings, filaments, or containers. These assemblies are widely used in biology as they enable multivalent binding, ultra-sensitive regulation, and compartmentalization. Moreover, with advances in the computational design of protein folding and protein-protein interfaces, considerable progress has recently been made in the de novo design of protein assemblies. Our review presents a description of the components of supramolecular protein assembly and their application in understanding biological phenomena to therapeutics.

Non-extensitivity and criticality of atomic hydropathicity around a voltage-gated sodium channel's pore: a modeling study

Voltage-gated sodium channels (NavChs) are pore-forming membrane proteins that regulate the transport of sodium ions through the cell membrane. Understanding the structure and function of NavChs is of major biophysical, as well as clinical, importance given their key role in cellular pathophysiology. In this work, we provide a computational framework for modeling system-size-dependent, i.e., cumulative, atomic properties around a NavCh's pore. We illustrate our methodologies on the bacterial NavAb channel captured in a closed-pore state where we demonstrate that the atomic environment around its pore exhibits a bi-phasic spatial organization dictated by the structural separation of the pore domains (PDs) from the voltage-sensing domains (VSDs). Accordingly, a mathematical model describing packing of atoms around NavAb's pore is constructed that allows-under certain conservation conditions-for a power-law approximation of the cumulative hydropathic dipole field effect acting along NavAb's pore. This verified the non-extensitivity hypothesis for the closed-pore NavAb channel and revealed a long-range hydropathic interactions law regulating atom-packing around the NavAb's selectivity filter. Our model predicts a PDs-VSDs coupling energy of [Formula: see text] kcal/mol corresponding to a global maximum of the atom-packing energy profile. Crucially, we demonstrate for the first time how critical phenomena can emerge in a single-channel structure as a consequence of the non-extensive character of its atomic porous environment.

Membrane Protein Engineering with Rosetta

Protein engineering can yield new molecular tools for nanotechnology and therapeutic applications through modulating physiochemical and biological properties. Engineering membrane proteins is especially attractive because they perform key cellular processes including transport, nutrient uptake, removal of toxins, respiration, motility, and signaling. In this chapter, we describe two protocols for membrane protein engineering with the Rosetta software: (1) ΔΔG calculations for single point mutations and (2) sequence optimization in different membrane lipid compositions. These modular protocols are easily adaptable for more complex problems and serve as a foundation for efficient membrane protein engineering calculations.

Designing minimalist membrane proteins

The construction of artificial membrane proteins from first principles is of fundamental interest and holds considerable promise for new biotechnologies. This review considers the potential advantages of adopting a strictly minimalist approach to the process of membrane protein design. As well as the practical benefits of miniaturisation and simplicity for understanding sequence-structure-function relationships, minimalism should also support the abstract conceptualisation of membrane proteins as modular components for synthetic biology. These ideas are illustrated with selected examples that focus upon α-helical membrane proteins, and which demonstrate how such minimalist membrane proteins might be integrated into living biosystems.

Proteins as diverse, efficient, and evolvable scaffolds for artificial metalloenzymes

We have extracted and categorized the desirable properties of proteins that are adapted as the scaffolds for artificial metalloenzymes.

Supramolecular organization of membrane proteins with anisotropic hydrophobic thickness

Experiments have revealed that membrane proteins often self-assemble into locally ordered clusters. Such membrane protein lattices can play key roles in the functional organization of cell membranes. Membrane protein organization can be driven, at least in part, by bilayer-mediated elastic interactions between membrane proteins. For membrane proteins with anisotropic hydrophobic thickness, bilayer-mediated protein interactions are inherently directional. Here we establish general relations between anisotropy in membrane protein hydrophobic thickness and supramolecular membrane protein organization. We show that protein symmetry is distinctively reflected in the energy landscape of bilayer-mediated protein interactions, favoring characteristic lattice architectures of membrane protein clusters. We find that, in the presence of thermal fluctuations, anisotropy in protein hydrophobic thickness can induce membrane proteins to form mesh-like structures dividing the membrane into compartments. Our results help to elucidate the physical principles and mechanisms underlying the functional organization of cell membranes.

Structural Perspective on Revealing and Altering Molecular Functions of Genetic Variants Linked with Diseases

Structural information of biological macromolecules is crucial and necessary to deliver predictions about the effects of mutations-whether polymorphic or deleterious (i.e., disease causing), wherein, thermodynamic parameters, namely, folding and binding free energies potentially serve as effective biomarkers. It may be emphasized that the effect of a mutation depends on various factors, including the type of protein (globular, membrane or intrinsically disordered protein) and the structural context in which it occurs. Such information may positively aid drug-design. Furthermore, due to the intrinsic plasticity of proteins, even mutations involving radical change of the structural and physico⁻chemical properties of the amino acids (native vs. mutant) can still have minimal effects on protein thermodynamics. However, if a mutation causes significant perturbation by either folding or binding free energies, it is quite likely to be deleterious. Mitigating such effects is a promising alternative to the traditional approaches of designing inhibitors. This can be done by structure-based in silico screening of small molecules for which binding to the dysfunctional protein restores its wild type thermodynamics. In this review we emphasize the effects of mutations on two important biophysical properties, stability and binding affinity, and how structures can be used for structure-based drug design to mitigate the effects of disease-causing variants on the above biophysical properties.

Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins

We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins.

Recent advances in automated protein design and its future challenges

INTRODUCTION

Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered: The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.

Computational design of membrane proteins using RosettaMembrane

Computational membrane protein design is challenging due to the small number of high-resolution structures available to elucidate the physical basis of membrane protein structure, multiple functionally important conformational states, and a limited number of high-throughput biophysical assays to monitor function. However, structural determination of membrane proteins has made tremendous progress in the past years. Concurrently the field of soluble computational design has made impressive inroads. These developments allow us to tackle the formidable challenge of designing functional membrane proteins. Herein, Rosetta is benchmarked for membrane protein design. We evaluate strategies to cope with the often reduced quality of experimental membrane protein structures. Further, we test the usage of symmetry in design protocols, which is particularly important as many membrane proteins exist as homo-oligomers. We compare a soluble scoring function with a scoring function optimized for membrane proteins, RosettaMembrane. Both scoring functions recovered around half of the native sequence when completely redesigning membrane proteins. However, RosettaMembrane recovered the most native-like amino acid property composition. While leucine was overrepresented in the inner and outer-hydrophobic regions of RosettaMembrane designs, it resulted in a native-like surface hydrophobicity indicating that it is currently the best option for designing membrane proteins with Rosetta.

Membrane proteins: always an insoluble problem?

Membrane proteins play crucial roles in cellular processes and are often important pharmacological drug targets. The hydrophobic properties of these proteins make full structural and functional characterization challenging because of the need to use detergents or other solubilizing agents when extracting them from their native lipid membranes. To aid membrane protein research, new methodologies are required to allow these proteins to be expressed and purified cheaply, easily, in high yield and to provide water soluble proteins for subsequent study. This mini review focuses on the relatively new area of water soluble membrane proteins and in particular two innovative approaches: the redesign of membrane proteins to yield water soluble variants and how adding solubilizing fusion proteins can help to overcome these challenges. This review also looks at naturally occurring membrane proteins, which are able to exist as stable, functional, water soluble assemblies with no alteration to their native sequence.

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.

Outer membrane protein design

Membrane proteins are the gateway to the cell. These proteins are also a control center of the cell, as information from the outside is passed through membrane proteins as signals to the cellular machinery. The design of membrane proteins seeks to harness the power of these gateways and signal carriers. This review will focus on the design of the membrane proteins that are in the outer membrane, a membrane which only exists for gram negative bacteria, mitochondria, and chloroplasts. Unlike other membrane proteins, outer membrane proteins are uniquely shaped as β-barrels. Herein, I describe most known examples of membrane β-barrel design to date, focusing particularly on categorizing designs as: Firstly, structural deconstruction; secondly, structural changes; thirdly, chemical function design; and finally, the creation of new folds.

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

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

De novo design of a transmembrane Zn²⁺-transporting four-helix bundle

The design of functional membrane proteins from first principles represents a grand challenge in chemistry and structural biology. Here, we report the design of a membrane-spanning, four-helical bundle that transports first-row transition metal ions Zn(2+) and Co(2+), but not Ca(2+), across membranes. The conduction path was designed to contain two di-metal binding sites that bind with negative cooperativity. X-ray crystallography and solid-state and solution nuclear magnetic resonance indicate that the overall helical bundle is formed from two tightly interacting pairs of helices, which form individual domains that interact weakly along a more dynamic interface. Vesicle flux experiments show that as Zn(2+) ions diffuse down their concentration gradients, protons are antiported. These experiments illustrate the feasibility of designing membrane proteins with predefined structural and dynamic properties.

Characterization of a computationally designed water-soluble human μ-opioid receptor variant using available structural information

BACKGROUND

The recent X-ray crystal structure of the murine μ-opioid receptor (MUR) allowed the authors to reengineer a previously designed water-soluble variant of the transmembrane portion of the human MUR (wsMUR-TM).

METHODS

The new variant of water-soluble MUR (wsMUR-TM_v2) was engineered based on the murine MUR crystal structure. This novel variant was expressed in Escherichia coli and purified. The properties of the receptor were characterized and compared with those of wsMUR-TM.

RESULTS

Seven residues originally included for mutation in the design of the wsMUR-TM were reverted to their native identities. wsMUR-TM_v2 contains 16% mutations of the total sequence. It was overexpressed and purified with high yield. Although dimers and higher oligomers were observed to form over time, the wsMUR-TM_v2 stayed predominantly monomeric at concentrations as high as 7.5 mg/ml in buffer within a 2-month period. Its secondary structure was predominantly helical and comparable with those of both the original wsMUR-TM variant and the native MUR. The binding affinity of wsMUR-TM_v2 for naltrexone (K(d) approximately 70 nM) was in close agreement with that for wsMUR-TM. The helical content of wsMUR-TM_v2 decreased cooperatively with increasing temperature, and the introduction of sucrose was able to stabilize the protein.

CONCLUSIONS

A novel functional wsMUR-TM_v2 with only 16% mutations was successfully engineered, expressed in E. coli, and purified based on information from the crystal structure of murine MUR. This not only provides a novel alternative tool for MUR studies in solution conditions but also offers valuable information for protein engineering and structure-function relations.

Sequence and conformational preferences at termini of α-helices in membrane proteins: role of the helix environment

α-Helices are amongst the most common secondary structural elements seen in membrane proteins and are packed in the form of helix bundles. These α-helices encounter varying external environments (hydrophobic, hydrophilic) that may influence the sequence preferences at their N and C-termini. The role of the external environment in stabilization of the helix termini in membrane proteins is still unknown. Here we analyze α-helices in a high-resolution dataset of integral α-helical membrane proteins and establish that their sequence and conformational preferences differ from those in globular proteins. We specifically examine these preferences at the N and C-termini in helices initiating/terminating inside the membrane core as well as in linkers connecting these transmembrane helices. We find that the sequence preferences and structural motifs at capping (Ncap and Ccap) and near-helical (N' and C') positions are influenced by a combination of features including the membrane environment and the innate helix initiation and termination property of residues forming structural motifs. We also find that a large number of helix termini which do not form any particular capping motif are stabilized by formation of hydrogen bonds and hydrophobic interactions contributed from the neighboring helices in the membrane protein. We further validate the sequence preferences obtained from our analysis with data from an ultradeep sequencing study that identifies evolutionarily conserved amino acids in the rat neurotensin receptor. The results from our analysis provide insights for the secondary structure prediction, modeling and design of membrane proteins.

Scalable production of highly sensitive nanosensors based on graphene functionalized with a designed G protein-coupled receptor

We have developed a novel, all-electronic biosensor for opioids that consists of an engineered μ-opioid receptor protein, with high binding affinity for opioids, chemically bonded to a graphene field-effect transistor to read out ligand binding. A variant of the receptor protein that provided chemical recognition was computationally redesigned to enhance its solubility and stability in an aqueous environment. A shadow mask process was developed to fabricate arrays of hundreds of graphene transistors with average mobility of ∼1500 cm(2) V(-1) s(-1) and yield exceeding 98%. The biosensor exhibits high sensitivity and selectivity for the target naltrexone, an opioid receptor antagonist, with a detection limit of 10 pg/mL.

TanCAR: A Novel Bispecific Chimeric Antigen Receptor for Cancer Immunotherapy

Targeted T cells are emerging as effective non-toxic therapies for cancer. Multiple elements, however, contribute to the overall pathogenesis of cancer through both distinct and redundant mechanisms. Hence, targeting multiple cancer-specific markers simultaneously could result in better therapeutic efficacy. We created a functional chimeric antigen receptor-the TanCAR, a novel artificial molecule that mediates bispecific activation and targeting of T cells. We demonstrate the feasibility of cumulative integration of structure and docking simulation data using computational tools to interrogate the design and predict the functionality of such a complex bispecific molecule. Our prototype TanCAR induced distinct T cell reactivity against each of two tumor restricted antigens, and produced synergistic enhancement of effector functions when both antigens were simultaneously encountered. Furthermore, the TanCAR preserved the cytolytic ability of T cells upon loss of one of the target molecules and better controlled established experimental tumors by recognition of both targets in an animal disease model. This proof-of-concept approach can be used to increase the specificity of effector cells for malignant versus normal target cells, to offset antigen escape or to allow for targeting the tumor and its microenvironment.Molecular Therapy-Nucleic Acids (2013) 2, e105; doi:10.1038/mtna.2013.32; published online 9 July 2013.

A computationally designed water-soluble variant of a G-protein-coupled receptor: the human mu opioid receptor

G-protein-coupled receptors (GPCRs) play essential roles in various physiological processes, and are widely targeted by pharmaceutical drugs. Despite their importance, studying GPCRs has been problematic due to difficulties in isolating large quantities of these membrane proteins in forms that retain their ligand binding capabilities. Creating water-soluble variants of GPCRs by mutating the exterior, transmembrane residues provides a potential method to overcome these difficulties. Here we present the first study involving the computational design, expression and characterization of water-soluble variant of a human GPCR, the human mu opioid receptor (MUR), which is involved in pain and addiction. An atomistic structure of the transmembrane domain was built using comparative (homology) modeling and known GPCR structures. This structure was highly similar to the subsequently determined structure of the murine receptor and was used to computationally design 53 mutations of exterior residues in the transmembrane region, yielding a variant intended to be soluble in aqueous media. The designed variant expressed in high yield in Escherichia coli and was water soluble. The variant shared structural and functionally related features with the native human MUR, including helical secondary structure and comparable affinity for the antagonist naltrexone (K_d  = 65 nM). The roles of cholesterol and disulfide bonds on the stability of the receptor variant were also investigated. This study exemplifies the potential of the computational approach to produce water-soluble variants of GPCRs amenable for structural and functionally related characterization in aqueous solution.

Analyzing the effects of hydrophobic mismatch on transmembrane α-helices using tryptophan fluorescence spectroscopy

Hydrophobic matching between transmembrane protein segments and the lipid bilayer in which they are embedded is a significant factor in the behavior and orientation of such transmembrane segments. The condition of hydrophobic mismatch occurs when the hydrophobic thickness of a lipid bilayer is significantly different than the length of the membrane spanning segment of a protein, resulting in a mismatch. This mismatch can result in altered function of proteins as well as nonnative structural arrangements including effects on transmembrane α-helix tilt angles, oligomerization state, and/or the formation of non-transmembrane topographies. Here, a fluorescence-based protocol is described for testing model transmembrane α-helices and their sensitivity to hydrophobic mismatch by measuring the propensity of these helices to form non-transmembrane structures. Overall, good hydrophobic matching between the bilayer and transmembrane segments is an important factor that must be considered when designing membrane proteins or peptides.

Naturally evolved G protein-coupled receptors adopt metastable conformations

A wide range of membrane receptors signal through conformational changes, and the resulting protein conformational flexibility often hinders their structural studies. Because the determinants of membrane receptor conformational stability are still poorly understood, identifying a minimal set of perturbations stabilizing a membrane protein in a given conformation remains a major challenge in membrane protein structure determination. We present a novel approach integrating bioinformatics, computational design and experimental techniques that identifies and stabilizes metastable receptor regions. When applied to the beta1-adrenergic receptor, the method generated 13 novel receptor variants stabilized in the intended inactive state among which two exhibit an apparent thermostability higher than WT and M23 (a receptor variant previously stabilized by extensive scanning mutagenesis) by more than 30 °C and 11 °C, respectively. Targeted regions involve nonconserved unsatisfied polar residues or exhibit significant packing defects, features found in all class A G protein-coupled receptor structures. These findings suggest that natural G protein-coupled receptor sequences have evolved to be conformationally metastable through the design of suboptimal polar and van der Waals tertiary interactions. Given sufficiently accurate structural models, our approach should prove useful for designing stabilized variants of many uncharacterized membrane receptors.