Side-chain Packing Research Articles

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Effect of Grafting Density on the Crystallization Behavior of Molecular Bottlebrushes.

A unique case of sterically constrained crystallization arises in bottlebrush polymers bearing semicrystalline side chains. Bottlebrushes with grafted side chains can form crystalline structures governed by the complex interplay between side chain packing and backbone confinement. The confinement effect can be readily tuned by varying the side chain grafting density, thus affording control over the crystallization behavior of these systems. In this work, the grafting density effect on the crystallization behavior of molecular bottlebrushes comprising poly(ethylene oxide) (PEO) side chains grafted to a methacrylate backbone was systematically studied. Thermal analysis using differential scanning calorimetry showed that the bottlebrush polymers displayed suppressed crystallization temperatures, lower melting temperatures, and reduced crystallinities compared to linear homopolymer PEO. The crystalline morphology was investigated using polarized light, atomic force, and scanning electron microscopy. Isothermal crystallization experiments revealed a nonmonotonous dependence of the nucleation density on the side chain grafting density. The grafting density effect was also investigated using self-seeding experiments, revealing an increased clearing temperature and memory retention at higher grafting densities. This work highlights how grafting density influences the crystallization behavior of semicrystalline bottlebrushes, providing information for the processing and application of these unique polymers.

A structural and biochemical approach to effect of temperature and pH on the Molten Globule phenomenon in a thermophilic protease: Molecular dynamics simulation, fluorescence spectroscopy and circular dichroism

Proteins in the molten globule (MG) stage have a reasonably stable secondary structure content, but changes in side-chain packing cause a noticeable decrease in the number of tertiary structures. Here, we investigated serine protease as a suitable model to study the folding route and characteristics of a protein in the MG state. Upon induction with IPTG, the protein exhibited a molecular weight of 42 kDa and achieved a final concentration of 1.7 mg/mL after the concentration process. Serine protease's intrinsic and extrinsic fluorescence was examined in the pH range of 1–12 using fluorescence spectroscopy with maximum intrinsic fluorescence in 335 nm and a blue shift in 510 nm for extrinsic fluorescence. It was suggested that the protein transitions probably to an MG state at pH 3. Evidences showed that serine protease's secondary structure using far-UV circular dichroism (CD) showed a little shift in the MG state intermediate, pH 3, relative to the original state, pH 8, which is typical for MG. Maximum decreases was observed in 228 to 300 nm for UV-near CD. Also revealed a notable alteration in the pH 3 of the enzyme compared to pH 8, which is the pH at which the protein takes on its natural structure. By using acrylamide to quench the fluorescence, the Stern-Volmer constant (KSV) was determined at pH values of 8 and 3, yielding values of 20 and 14 M−1, respectively. This is likely correlated with an increase in the enzyme's molecular volume in the MG state. Molecular dynamics (MD) simulation showed that although the thermal stability of this enzyme at 90° was confirmed in the Root-Mean-Square-Deviation (RMSD), Root-Mean-Square-Fluctuation (RMSF), Radius of gyration (Rg) as well as Solvent-Accessible-Surface-Area (SASA) graphs, but pH 3 may significantly disturb the tertiary structure and secondary structure. These in-silico results may also be analyzed in line with the occurrence of MG at pH 3.

Invariant point message passing for protein side chain packing.

Protein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high-confidence and low-energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein-protein interactions, and protein-ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low-energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state-of-the-art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates using -angle distribution predictions and geometry-aware invariant point message passing (IPMP). On a test set of ∼1400 high-quality protein chains, PIPPack is highly competitive with other state-of-the-art PSCP methods in rotamer recovery and per-residue RMSD but is significantly faster.

Mechanistic Insight into the Mechanical Unfolding of the Integral Membrane Diacylglycerol Kinase.

The essential forces stabilizing membrane proteins and governing their folding and unfolding are difficult to decipher. Single-molecule atomic force spectroscopy mechanically unfolds individual membrane proteins and quantifies their dynamics and energetics. However, it remains challenging to structurally assign unfolding intermediates precisely and to deduce dominant interactions between specific residues that facilitate either the localized stabilization of these intermediates or the global assembly of membrane proteins. Here, we performed force spectroscopy experiments and multiscale molecular dynamics simulations to study the unfolding pathway of diacylglycerol kinase (DGK), a small trimeric multispan transmembrane enzyme. The remarkable agreement between experiments and simulations allowed precise structural assignment and interaction analysis of unfolding intermediates, bypassing existing limitations on structural mapping, and thus provided mechanistic explanations for the formation of these states. DGK unfolding was found to proceed with structural segments varying in size that do not correlate with its secondary structure. We identified intermolecular side-chain packing interactions as one of the major contributions to the stability of unfolding intermediates. Mutagenesis creating packing defects induced a dramatic decrease in the mechano-stability of corresponding intermediates and also in the thermo-stability of DGK trimer, in good agreement with predictions from simulations. Hence, the molecular determinants of the mechano- and thermo-stability of a membrane protein can be identified at residue resolution. The accurate structural assignment established and microscopic mechanism revealed in this work may substantially expand the scope of single-molecule studies of membrane proteins.

Microstructural Evolution of P(NDI2OD-T2) Films with Different Molecular Weight during Stretching Deformation.

Conjugated polymers exhibit excellent electrical and mechanical properties when their molecular weight (Mw) is above the critical molecular weight (Mc). The microstructural changes of polymers under strain are crucial to establish a structure-performance relationship. Herein, the tensile deformation of P(NDI2OD-T2) is visualized, and cracks are revealed either along the (100) crystal plane of side chain packing or along the main chain direction which depends on the Mw is below or above the Mc. When Mw < Mc, the film cracks along the (100) plane under small strains. When Mw > Mc, the polymer chains first undergo stretch-induced orientation and then fracture along the main chain direction at large strains. This is attributed to the fact that the low Mw film exhibits large crystalline domains and the absence of interdomain connectivity, which are vulnerable to mechanical stress. In contrast, the high Mw film displays a nearly amorphous morphology with adequate entanglements, the molecular chains can endure stresses in the stretching direction to release substantial strain energy under greater mechanical deformation. Therefore, the film with Mw > Mc exhibits the optimal electrical and mechanical performances simultaneously, i.e., the electron mobility is retained under 100% strain and after 100 stretching-releasing cycles.

De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO

By mediating interatomic interactions, water molecules play a major role in protein–protein, protein–DNA and protein–ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein–protein interfaces.

X-ray structure of the metastable SEPT14-SEPT7 coiled coil reveals a hendecad region crucial for heterodimerization.

Septins are membrane-associated, GTP-binding proteins that are present in most eukaryotes. They polymerize to play important roles as scaffolds and/or diffusion barriers as part of the cytoskeleton. α-Helical coiled-coil domains are believed to contribute to septin assembly, and those observed in both human SEPT6 and SEPT8 form antiparallel homodimers. These are not compatible with their parallel heterodimeric organization expected from the current model for protofilament assembly, but they could explain the interfilament cross-bridges observed by microscopy. Here, the first structure of a heterodimeric septin coiled coil is presented, that between SEPT14 and SEPT7; the former is a SEPT6/SEPT8 homolog. This new structure is parallel, with two long helices that are axially shifted by a full helical turn with reference to their sequence alignment. The structure also has unusual knobs-into-holes packing of side chains. Both standard seven-residue (heptad) and the less common 11-residue (hendecad) repeats are present, creating two distinct regions with opposite supercoiling, which gives rise to an overall straight coiled coil. Part of the hendecad region is required for heterodimerization and therefore may be crucial for selective septin recognition. These unconventional sequences and structural features produce a metastable heterocomplex that nonetheless has enough specificity to promote correct protofilament assembly. For instance, the lack of supercoiling may facilitate unzipping and transitioning to the antiparallel homodimeric state.

Influence of Protonation on the Norepinephrine Inhibiting α-Synuclein 71-82 Oligomerization.

The pathogenesis of Parkinson's disease (PD) is closely linked to the massive presence of Lewy vesicles and Lewy axons in the cytoplasm of neurons, mainly consisting of α-synuclein (αS). Norepinephrine (NE), whose secretion can be increased by exercise, has been demonstrated to prevent the fibrillation of αS and to break down the mature αS fibrils. In this work, we focus on the influence of protonation on the inhibitory ability of NE by using amyloid core fragment αS71-82 as a template. All-atom replica-exchange molecular dynamics simulations (accumulating to 33.6 μs) in explicit water were performed to explore the inhibitory effect of protonated and nonprotonated NE on αS oligomerization. Our results show that NE/NE+ can lead to a significant decrease in β-sheet content with increasing temperature, while isolated αS maintains relatively higher β-sheet conformations until 363 K, implying that both NE and NE+ can lower the critical temperature required for αS fibril decomposition. NE and NE+ also lead to the formation of less compact αS oligomers by preventing the backbone hydrogen bonds and the side-chain packing. The protonation would affect the binding affinity, interaction modes, and binding intensity of NE with αS. Interesting, NE and NE+ have a distinct binding free energy in the electrostatic and solvation terms, which mostly counter each other and produce a weak binding intensity with αS. Our work contributes to a better understanding of the inhibitory mechanism of NE and NE+ on αS oligomerization relevant to PD pathogenesis, which may provide clues for the design of antiamyloid medicine.

ZetaDesign: an end-to-end deep learning method for protein sequence design and side-chain packing.

Computational protein design has been demonstrated to be the most powerful tool in the last few years among protein designing and repacking tasks. In practice, these two tasks are strongly related but often treated separately. Besides, state-of-the-art deep-learning-based methods cannot provide interpretability from an energy perspective, affecting the accuracy of the design. Here we propose a new systematic approach, including both a posterior probability and a joint probability parts, to solve the two essential questions once for all. This approach takes the physicochemical property of amino acids into consideration and uses the joint probability model to ensure the convergence between structure and amino acid type. Our results demonstrated that this method could generate feasible, high-confidence sequences with low-energy side conformations. The designed sequences can fold into target structures with high confidence and maintain relatively stable biochemical properties. The side chain conformation has a significantly lower energy landscape without delegating to a rotamer library or performing the expensive conformational searches. Overall, we propose an end-to-end method that combines the advantages of both deep learning and energy-based methods. The design results of this model demonstrate high efficiency, and precision, as well as a low energy state and good interpretability.

An end-to-end deep learning method for protein side-chain packing and inverse folding

Protein side-chain packing (PSCP), the task of determining amino acid side-chain conformations given only backbone atom positions, has important applications to protein structure prediction, refinement, and design. Many methods have been proposed to tackle this problem, but their speed or accuracy is still unsatisfactory. To address this, we present AttnPacker, a deep learning (DL) method for directly predicting protein side-chain coordinates. Unlike existing methods, AttnPacker directly incorporates backbone 3D geometry to simultaneously compute all side-chain coordinates without delegating to a discrete rotamer library or performing expensive conformational search and sampling steps. This enables a significant increase in computational efficiency, decreasing inference time by over 100× compared to the DL-based method DLPacker and physics-based RosettaPacker. Tested on the CASP13 and CASP14 native and nonnative protein backbones, AttnPacker computes physically realistic side-chain conformations, reducing steric clashes and improving both rmsd and dihedral accuracy compared to state-of-the-art methods SCWRL4, FASPR, RosettaPacker, and DLPacker. Different from traditional PSCP approaches, AttnPacker can also codesign sequences and side chains, producing designs with subnative Rosetta energy and high in silico consistency.

In silico investigation of the structural stability as the origin of the pathogenicity of α-synuclein protofibrils

α-Synuclein is a presynaptic neuronal protein. The fibril form of α-synuclein is a major constituent of the intraneuronal inclusion called Lewy body, a characteristic hallmark of Parkinson’s disease. Recent ssNMR and cryo-EM experiments of wild-type α-synuclein fibrils have shown polymorphism and observed two major polymorphs, rod and twister. To associate the cytotoxicity of α-synuclein fibrils with their structural features, it is essential to understand the origins of their structural stability. In this study, we performed molecular dynamics simulations of the two major polymorphs of wild-type α-synuclein fibrils. The predominance of specific fibril polymorphs was rationalized in terms of relative structural stability in aqueous environments, which was attributed to the cooperative contributions of various stabilizing features. The results of the simulations indicated that highly stable structures in aqueous environments could be maintained by the cooperation of compact sidechain packing in the hydrophobic core, backbone geometry of the maximal β-sheet content wrapping the hydrophobic core, and solvent-exposed sidechains with large fluctuations maximizing the solvation entropy. The paired structure of the two protofilaments provides additional stability, especially at the interface region, by forming steric zipper interactions and hiding the hydrophobic residues from exposure to water. The sidechain interaction analyses and pulling simulations showed that the rod polymorph has stronger sidechain interactions and exhibits higher dissociation energy than the twister polymorph. It is expected that our study will provide a basis for understanding the pathogenic behaviors of diverse amyloid strains in terms of their structural properties.Communicated by Ramaswamy H. Sarma

NMR Studies of Aromatic Ring Flips to Probe Conformational Fluctuations in Proteins.

Aromatic residues form a significant part of the protein core, where they make tight interactions with multiple surrounding side chains. Despite the dense packing of internal side chains, the aromatic rings of phenylalanine and tyrosine residues undergo 180° rotations, or flips, which are mediated by transient and large-scale "breathing" motions that generate sufficient void volume around the aromatic ring. Forty years after the seminal work by Wagner and Wüthrich, NMR studies of aromatic ring flips are now undergoing a renaissance as a powerful means of probing fundamental dynamic properties of proteins. Recent developments of improved NMR methods and isotope labeling schemes have enabled a number of advances in addressing the mechanisms and energetics of aromatic ring flips. The nature of the transition states associated with ring flips can be described by thermodynamic activation parameters, including the activation enthalpy, activation entropy, activation volume, and also the isothermal volume compressibility of activation. Consequently, it is of great interest to study how ring flip rate constants and activation parameters might vary with protein structure and external conditions like temperature and pressure. The field is beginning to gather such data for aromatic residues in a variety of environments, ranging from surface exposed to buried. In the future, the combination of solution and solid-state NMR spectroscopy together with molecular dynamics simulations and other computational approaches is likely to provide detailed information about the coupled dynamics of aromatic rings and neighboring residues. In this Perspective, we highlight recent developments and provide an outlook toward the future.

Regulating polystyrene glass transition temperature by varying the hydration levels of aromatic ring/Li+ interaction.

Polymer properties can be altered via lithium ion doping, whereby adsorbed Li+ binds with H2O within the polymer chain. However, direct spectroscopic evidence of the tightness of Li+/H2O binding in the solid state is limited, and the impact of Li+ on polymer sidechain packing is rarely reported. Here, we investigate a polystyrene/H2O/LiCl system using solid-state NMR, from which we determined a dipolar coupling of 11.4 kHz between adsorbed Li+ and H2O protons. This coupling corroborates a model whereby Li+ interacts with the oxygen atom in H2O via charge affinity, which we believe is the main driving force of Li+ binding. We demonstrated the impact of hydrated Li+ on sidechain packing and dynamics in polystyrene using proton-detected solid-state NMR. Experimental data and density functional theory (DFT) simulations revealed that the addition of Li+ and the increase in the hydration levels of Li+, coupled with aromatic ring binding, change the energy barrier of sidechain packing and dynamics and, consequently, changes the glass transition temperature of polystyrene.

Improved interface packing and design opportunities revealed by CryoEM analysis of a designed protein nanocage

Symmetric protein assemblies play important roles in nature which makes them an attractive target for engineering. De novo symmetric protein complexes can be created through computational protein design to tailor their properties from first principles, and recently several protein nanocages have been created by bringing together protein components through hydrophobic interactions. Accurate experimental structures of newly-developed proteins are essential to validate their design, improve assembly stability, and tailor downstream applications. We describe the CryoEM structure of the nanocage I3-01, at an overall resolution of 3.5 Å. I3-01, comprising 60 aldolase subunits arranged with icosahedral symmetry, has resisted high-resolution characterization. Some key differences between the refined structure and the original design are identified, such as improved packing of hydrophobic sidechains, providing insight to the resistance of I3-01 to high-resolution averaging. Based on our analysis, we suggest factors important in the design and structural processing of new assemblies.

Butyl rubber as a macro-cross-linker in the preparation of a shape-memory and self-healing polymer

Recently, a simple strategy was developed for preparing interconnected interpenetrating polymer networks (IPNs) based on butyl rubber (IIR) and poly(n-octadecyl acrylate) (PC18A). Solvent-free UV polymerization of n-octadecyl acrylate (C18A) monomer in the melt of IIR at ambient temperature resulted in IPNs with self-healing and shape-memory functions. Here, we demonstrate that the use of IIR grafted with acrylic acid, methacrylic acid, and 10-undecenoic acid instead of unmodified IIR provides a significant improvement in the mechanical properties of IPNs. Differential scanning calorimetry, small-angle x-ray scattering, and wide-angle x-ray scattering analysis reveal side-by-side packing of C18 side chains of PC18A to form lamellar crystals with a melting temperature Tm between 46 and 52 °C. Transmission electron microscopy analysis indicates the existence of quasispherical nanoparticles composed of crystalline domains, which are dispersed in a continuous interpenetrating rubber-PC18A matrix. This microstructure provides them a complete self-recovery behavior induced by heating and an efficient shape-memory function. IPNs exhibit around tenfold higher chemical cross-link density as compared to those prepared from the native IIR, reflecting the effect of pendant vinyl groups on the extent of covalent interconnections between the IIR and PC18A components. The type of the grafted monomers significantly affects the mechanical performance of IPNs, which can be explained with the individual contributions of chemical and physical cross-links to the total cross-link density. The amount of the grafted rubbers in IPN could be further increased up to 80 wt. % by the incorporation of toluene into the reaction system, resulting in IPNs with a wide range of tunable thermal and mechanical properties.

Site-specific Heterogeneity of Multi-domain Human Serum Albumin and its Origin: A Red Edge Excitation Shift Study†.

Conformational heterogeneity is a defining characteristic of a protein and is vital in understanding its function and folding landscape. In the present work, we interrogated the presence of conformational heterogeneity in multi-domain human serum albumin in a domain-specific manner using red edge excitation shift (REES) in its native state and also monitored its variation along the unfolding transition. We also looked into the origin of such conformational heterogeneity by varying the solution viscosity. We observed (1) even in the native state, the heterogeneity and dynamics of the side chain exhibit varied behaviors depending on which domain of the multi-domain human serum albumin (HSA) is being examined. (2) When the protein is in the unfolded state, the extent of REES is rendered unimportant since there is a greater quantity of free water present, in addition to the disruption of the protein's structure. (3) While the rigid protein matrix provides the rigidity of domain-I and domain-III, the rigidity of domain-II is provided by water molecules, which indicates that the role of water molecules in providing the rigidity is significant. Overall, our results provide direct evidence of the rigidity and alternate side chain packing arrangement of protein core that varies domain-wise in multi-domain HSA.

Folding Coarse-Grained Oligomer Models with PyRosetta.

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta's ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. We show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

Studying protein-protein interaction through side-chain modeling method OPUS-Mut.

Protein side chains are vitally important to many biological processes such as protein-protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65) and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms other methods measured by all residues or by the interfacial residues. We also demonstrate our method on evaluating protein-protein docking pose on a dataset Oligomer-Dock (75) created using the top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies the native pose as the top-1 in 45 out of 75 targets. Different from traditional scoring functions, our method is based on the overall side-chain packing favorableness in accordance with the local packing environment. It emphasizes the significance of side chains and provides a new and effective scoring term for studying protein-protein interaction.

Engineered Spider Silk Proteins for Biomimetic Spinning of Fibers with Toughness Equal to Dragline Silks.

Spider silk is the toughest fiber found in nature, and bulk production of artificial spider silk that matches its mechanical properties remains elusive. Development of miniature spider silk proteins (mini-spidroins) has made large-scale fiber production economically feasible, but the fibers' mechanical properties are inferior to native silk. The spider silk fiber's tensile strength is conferred by poly-alanine stretches that are zipped together by tight side chain packing in β-sheet crystals. Spidroins are secreted so they must be void of long stretches of hydrophobic residues, since such segments get inserted into the endoplasmic reticulum membrane. At the same time, hydrophobic residues have high β-strand propensity and can mediate tight inter-β-sheet interactions, features that are attractive for generation of strong artificial silks. Protein production in prokaryotes can circumvent biological laws that spiders, being eukaryotic organisms, must obey, and the authors thus design mini-spidroins that are predicted to more avidly form stronger β-sheets than the wildtype protein. Biomimetic spinning of the engineered mini-spidroins indeed results in fibers with increased tensile strength and two fiber types display toughness equal to native dragline silks. Bioreactor expression and purification result in a protein yield of ≈9gL-1 which is in line with requirements for economically feasible bulk scale production.