Computational protein design with explicit consideration of surface hydrophobic patches

Rational Redesign of Chitosanase to Enhance Thermostability and Catalytic Activity to Produce Chitooligosaccharides with a Relatively High Degree of Polymerization

Chitooligosaccharides (hdpCOS) with a high degree of polymerization (hdp, DP 4-10) generally have greater biological activities than those of low-DP (ldp, DP 2-3) COS. Chitosanase from Bacillus amyloliquefaciens KCP2 (Csn46) can degrade chitosan to more hdpCOS at high temperature (70 °C), but low thermal stability at this temperature makes it unsuitable for industrial application; the wild-type enzyme can only produce COS (DP 2-4) at lower temperatures. Several thermostable mutants were obtained by modifying chitosanase using a comprehensive strategy based on a computer-aided mutant design. A combination of four beneficial single-point mutations (A129L/T175 V/K70T/D34G) to Csn46 was selected to obtain a markedly improved mutant, Mut4, with a half-life at 60 °C extended from 34.31 to 690.80 min, and the specific activity increased from 1671.73 to 3528.77 U/mg. Mut4 produced COS with DPs of 2-4 and 2-7 at 60 and 70 °C, respectively. Therefore, Mut4 has the potential to be applied to the industrial-scale preparation of hdpCOS with high biological activity.

Virus on surfaces: Chemical mechanism, influence factors, disinfection strategies, and implications for virus repelling surface design

While SARS-CoV-2 is generally under control, the question of variants and infections still persists. Fundamental information on how the virus interacts with inanimate surfaces commonly found in our daily life and when in contact with the skin will be helpful in developing strategies to inhibit the spread of the virus. Here in, a critically important review of current understanding of the interaction between virus and surface is summarized from chemistry point-of-view. The Derjaguin-Landau-Verwey-Overbeek and extended Derjaguin-Landau-Verwey-Overbeek theories to model virus attachments on surfaces are introduced, along with the interaction type and strength, and quantification of each component. The virus survival and transfer are affected by a combination of biological, physical, and chemical parameters, as well as environmental parameters. The surface properties for virus and virus survival on typical surfaces such as metals, plastics, and glass are summarized. Attention is also paid to the transfer of virus to/from surfaces and skin. Typical virus disinfection strategies utilizing heat, light, chemicals, and ozone are discussed together with their disinfection mechanism. In the last section, design principles for virus repelling surface chemistry such as surperhydrophobic or surperhydrophilic surfaces are also introduced, to demonstrate how the integration of surface property control and advanced material fabrication can lead to the development of functional surfaces for mitigating the effect of viral infection upon contact.

Design, Production, and Characterization of Catalytically Active Inclusion Bodies

Catalytically active inclusion bodies (CatIBs) are promising biologically produced enzyme/protein immobilizates for application in biocatalysis, synthetic chemistry, and biomedicine. CatIB formation is commonly induced by fusion of suitable aggregation-inducing tags to a given target protein. Heterologous production of the fusion protein in turn yields CatIBs. This chapter presents the methodology needed to design, produce, and characterize CatIBs.

Inhibitory effect of lignin on the hydrolysis of xylan by thermophilic and thermolabile GH11 xylanases

Background

Enzymatic hydrolysis of lignocellulosic biomass into platform sugars can be enhanced by the addition of accessory enzymes, such as xylanases. Lignin from steam pretreated biomasses is known to inhibit enzymes by non-productively binding enzymes and limiting access to cellulose. The effect of enzymatically isolated lignin on the hydrolysis of xylan by four glycoside hydrolase (GH) family 11 xylanases was studied. Two xylanases from the mesophilic Trichoderma reesei, TrXyn1, TrXyn2, and two forms of a thermostable metagenomic xylanase Xyl40 were compared.

Results

Lignin isolated from steam pretreated spruce decreased the hydrolysis yields of xylan for all the xylanases at 40 and 50 °C. At elevated hydrolysis temperature of 50 °C, the least thermostable xylanase TrXyn1 was most inhibited by lignin and the most thermostable xylanase, the catalytic domain (CD) of Xyl40, was least inhibited by lignin. Enzyme activity and binding to lignin were studied after incubation of the xylanases with lignin for up to 24 h at 40 °C. All the studied xylanases bound to lignin, but the thermostable xylanases retained 22–39% of activity on the lignin surface for 24 h, whereas the mesophilic T. reesei xylanases become inactive. Removing of N-glycans from the catalytic domain of Xyl40 increased lignin inhibition in hydrolysis of xylan when compared to the glycosylated form. By comparing the 3D structures of these xylanases, features contributing to the increased thermal stability of Xyl40 were identified.

Conclusions

High thermal stability of xylanases Xyl40 and Xyl40-CD enabled the enzymes to remain partially active on the lignin surface. N-glycosylation of the catalytic domain of Xyl40 increased the lignin tolerance of the enzyme. Thermostability of Xyl40 was most likely contributed by a disulphide bond and salt bridge in the N-terminal and α-helix regions.

Graphical Abstract

A Roadmap for Building Waterborne Virus Traps

Outbreaks of waterborne viruses pose a massive threat to human health, claiming the lives of hundreds of thousands of people every year. Adsorption-based filtration offers a promising facile and environmentally friendly approach to help provide safe drinking water to a world population of almost 8 billion people, particularly in communities that lack the infrastructure for large-scale facilities. The search for a material that can effectively trap viruses has been mainly driven by a top-down approach, in which old and new materials have been tested for this purpose. Despite substantial advances, finding a material that achieves this crucial goal and meets all associated challenges remains elusive. We suggest that the road forward should strongly rely on a complementary bottom-up approach based on our fundamental understanding of virus interactions at interfaces. We review the state-of-the-art physicochemical knowledge of the forces that drive the adsorption of viruses at solid-water interfaces. Compared to other nanometric colloids, viruses have heterogeneous surface chemistry and diverse morphologies. We advocate that advancing our understanding of virus interactions would require describing their physicochemical properties using novel descriptors that reflect their heterogeneity and diversity. Several other related topics are also addressed, including the effect of coadsorbates on virus adsorption, virus inactivation at interfaces, and experimental considerations to ensure well-grounded research results. We finally conclude with selected examples of materials that made notable advances in the field.

Identifying well-folded de novo proteins in the new era of accurate structure prediction

Computational de novo protein design tailors proteins for target structures and oligomerisation states with high stability, which allows overcoming many limitations of natural proteins when redesigned for new functions. Despite significant advances in the field over the past decade, it remains challenging to predict sequences that will fold as stable monomers in solution or binders to a particular protein target; thereby requiring substantial experimental resources to identify proteins with the desired properties. To overcome this, here we leveraged the large amount of design data accumulated in the last decade, and the breakthrough in protein structure prediction from last year to investigate on improved ways of selecting promising designs before experimental testing. We collected de novo proteins from previous studies, 518 designed as monomers of different folds and 2112 as binders against the Botulinum neurotoxin, and analysed their structures with AlphaFold2, RoseTTAFold and fragment quality descriptors in combination with other properties related to surface interactions. These features showed high complementarity in rationalizing the experimental results, which allowed us to generate quite accurate machine learning models for predicting well-folded monomers and binders with a small set of descriptors. Cross-validating designs with varied orthogonal computational techniques should guide us for identifying design imperfections, rescuing designs and making more robust design selections before experimental testing.

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.

A Leucyl-tRNA Synthetase Urzyme: Authenticity of tRNA Synthetase Catalytic Activities and Promiscuous Phosphorylation of Leucyl-5'AMP

Aminoacyl-tRNA synthetase (aaRS)/tRNA cognate pairs translate the genetic code by synthesizing specific aminoacyl-tRNAs that are assembled on messenger RNA by the ribosome. Deconstruction of the two distinct aaRS superfamilies (Classes) has provided conceptual and experimental models for their early evolution. Urzymes, containing ~120–130 amino acids excerpted from regions where genetic coding sequence complementarities have been identified, are key experimental models motivated by the proposal of a single bidirectional ancestral gene. Previous reports that Class I and Class II urzymes accelerate both amino acid activation and tRNA aminoacylation have not been extended to other synthetases. We describe a third urzyme (LeuAC) prepared from the Class IA Pyrococcus horikoshii leucyl-tRNA synthetase. We adduce multiple lines of evidence for the authenticity of its catalysis of both canonical reactions, amino acid activation and tRNA^Leu aminoacylation. Mutation of the three active-site lysine residues to alanine causes significant, but modest reduction in both amino acid activation and aminoacylation. LeuAC also catalyzes production of ADP, a non-canonical enzymatic function that has been overlooked since it first was described for several full-length aaRS in the 1970s. Structural data suggest that the LeuAC active site accommodates two ATP conformations that are prominent in water but rarely seen bound to proteins, accounting for successive, in situ phosphorylation of the bound leucyl-5′AMP phosphate, accounting for ADP production. This unusual ATP consumption regenerates the transition state for amino acid activation and suggests, in turn, that in the absence of the editing and anticodon-binding domains, LeuAC releases leu-5′AMP unusually slowly, relative to the two phosphorylation reactions.

Structure and activity of a thermally stable mutant of Acanthamoeba actophorin

Actophorin, which was recently tested for crystallization under microgravity on the International Space Station, was subjected to mutagenesis to identify a construct with improved biophysical properties that were expected to improve the extent of diffraction. First, 20 mutations, including one C-terminal deletion of three residues, were introduced individually into actophorin, resulting in modest increases in thermal stability of between +0.5°C and +2.2°C. All but two of the stabilizing mutants increased both the rates of severing F-actin filaments and of spontaneous polymerization of pyrenyl G-actin in vitro. When the individual mutations were combined into a single actophorin variant, Acto-2, the overall thermal stability was 22°C higher than that of wild-type actophorin. When an inactivating S2P mutation in Acto-2 was restored, Acto-2/P2S was more stable by 20°C but was notably more active than the wild-type protein. The inactivating S2P mutation reaffirms the importance that Ser2 plays in the F-actin-severing reaction. The crystal structure of Acto-2 was solved to 1.7 Å resolution in a monoclinic space group, a first for actophorin. Surprisingly, despite the increase in thermal stability, the extended β-turn region, which is intimately involved in interactions with F-actin, is disordered in one copy of Acto-2 in the asymmetric unit. These observations emphasize the complex interplay among protein thermal stability, function and dynamics.

In Silico Analysis of Glucose Oxidase from Aspergillus niger: Potential Cysteine Mutation Sites for Enhancing Protein Stability

Glucose oxidase (GOx) holds considerable advantages for various applications. Nevertheless, the thermal instability of the enzyme remains a grand challenge, impeding the success in applications outside the well-controlled laboratories, particularly in practical bioelectronics. Many strategies to modify GOx to achieve better thermal stability have been proposed. However, modification of this enzyme by adding extra disulfide bonds is yet to be explored. This work describes the in silico bioengineering of GOx from Aspergillus niger by judiciously analyzing characteristics of disulfide bonds found in the Top8000 protein database, then scanning for amino acid residue pairs that are suitable to be replaced with cysteines in order to establish disulfide bonds. Next, we predicted and assessed the mutant GOx models in terms of disulfide bond quality (bond length and α angles), functional impact by means of residue conservation, and structural impact as indicated by Gibbs free energy. We found eight putative residue pairs that can be engineered to form disulfide bonds. Five of these are located in less conserved regions and, therefore, are unlikely to have a deleterious impact on functionality. Finally, two mutations, Pro149Cys and His158Cys, showed potential for stabilizing the protein structure as confirmed by a structure-based stability analysis tool. The findings in this study highlight the opportunity of using disulfide bond modification as a new alternative technique to enhance the thermal stability of GOx.

Recombinant expression of insoluble enzymes in Escherichia coli: a systematic review of experimental design and its manufacturing implications

Recombinant enzyme expression in Escherichia coli is one of the most popular methods to produce bulk concentrations of protein product. However, this method is often limited by the inadvertent formation of inclusion bodies. Our analysis systematically reviews literature from 2010 to 2021 and details the methods and strategies researchers have utilized for expression of difficult to express (DtE), industrially relevant recombinant enzymes in E. coli expression strains. Our review identifies an absence of a coherent strategy with disparate practices being used to promote solubility. We discuss the potential to approach recombinant expression systematically, with the aid of modern bioinformatics, modelling, and ‘omics’ based systems-level analysis techniques to provide a structured, holistic approach. Our analysis also identifies potential gaps in the methods used to report metadata in publications and the impact on the reproducibility and growth of the research in this field.

Computational and Experimental Assessment of Backbone Templates for Computational Redesign of the Thioredoxin Fold

Computational protein design has taken big strides in recent years; however, the tools available are still not at a state where a sequence can be designed to fold into a given protein structure at will and with high probability. We have applied here a recent release of Rosetta Design to redesign a set of structurally very similar proteins belonging to the thioredoxin fold. We used a genetic screening tool to estimate solubility/folding of the designed proteins in E. coli and to select the best hits from this for further biochemical characterization. We have previously used this set of template proteins for redesign and found that success was highly dependent on template structure, a trait which was also found in this study. Nevertheless, state-of-the-art design software is now able to predict the best template, most likely due to the introduction of an energy term that reports on stress in covalent bond lengths and angles. The template that led to the greatest fraction of successful designs was the same (a thioredoxin from spinach) as that identified in our previous study. Our previously described redesign of thioredoxin, which also used the spinach protein as a template, however also performed well as a template. In the present study, both of these templates yielded proteins with compact folded structures and enforced the conclusion that any design project must carefully consider different design templates. Fortunately, selecting designs based on energies appears to correctly identify such templates.

Protein Surface Printer for Exploring Protein Domains

The surface of proteins is vital in determining protein functions. Herein, a program, Protein Surface Printer (PSP), is built that performs multiple functions in quantifying protein surface domains. Two proteins, PETase and cytochrome P450, are used to validate that the program supports atomistic simulations with different combinations of programs and force fields. A case study is conducted on the structural analysis of the spike proteins of SARS-CoV-2 and SARS-CoV and the human cell receptor ACE2. Although the surface domains of both spike proteins are highly similar, their receptor-binding domains (RBDs) and the O-linked glycan domains are structurally different. The O-linked glycan domain of SARS-CoV-2 is highly positively charged, which may promote binding to negatively charged human cells.

Catalytically-active inclusion bodies for biotechnology-general concepts, optimization, and application

Bacterial inclusion bodies (IBs) have long been considered as inactive, unfolded waste material produced by heterologous overexpression of recombinant genes. In industrial applications, they are occasionally used as an alternative in cases where a protein cannot be expressed in soluble form and in high enough amounts. Then, however, refolding approaches are needed to transform inactive IBs into active soluble protein. While anecdotal reports about IBs themselves showing catalytic functionality/activity (CatIB) are found throughout literature, only recently, the use of protein engineering methods has facilitated the on-demand production of CatIBs. CatIB formation is induced usually by fusing short peptide tags or aggregation-inducing protein domains to a target protein. The resulting proteinaceous particles formed by heterologous expression of the respective genes can be regarded as a biologically produced bionanomaterial or, if enzymes are used as target protein, carrier-free enzyme immobilizates. In the present contribution, we review general concepts important for CatIB production, processing, and application. KEY POINTS: • Catalytically active inclusion bodies (CatIBs) are promising bionanomaterials. • Potential applications in biocatalysis, synthetic chemistry, and biotechnology. • CatIB formation represents a generic approach for enzyme immobilization. • CatIB formation efficiency depends on construct design and expression conditions.

Evaluating Protein Engineering Thermostability Prediction Tools Using an Independently Generated Dataset

Engineering proteins to enhance thermal stability is a widely utilized approach for creating industrially relevant biocatalysts. The development of new experimental datasets and computational tools to guide these engineering efforts remains an active area of research. Thus, to complement the previously reported measures of T 50 and kinetic constants, we are reporting an expansion of our previously published dataset of mutants for β-glucosidase to include both measures of T M and ΔΔG. For a set of 51 mutants, we found that T 50 and T M are moderately correlated, with a Pearson correlation coefficient and Spearman's rank coefficient of 0.58 and 0.47, respectively, indicating that the two methods capture different physical features. The performance of predicted stability using nine computational tools was also evaluated on the dataset of 51 mutants, none of which are found to be strong predictors of the observed changes in T 50, T M, or ΔΔG. Furthermore, the ability of the nine algorithms to predict the production of isolatable soluble protein was examined, which revealed that Rosetta ΔΔG, FoldX, DeepDDG, PoPMuSiC, and SDM were capable of predicting if a mutant could be produced and isolated as a soluble protein. These results further highlight the need for new algorithms for predicting modest, yet important, changes in thermal stability as well as a new utility for current algorithms for prescreening designs for the production of mutants that maintain fold and soluble production properties.

Design on a Rational Basis of High-Affinity Peptides Inhibiting the Histone Chaperone ASF1

Anti-silencing function 1 (ASF1) is a conserved H3-H4 histone chaperone involved in histone dynamics during replication, transcription, and DNA repair. Overexpressed in proliferating tissues including many tumors, ASF1 has emerged as a promising therapeutic target. Here, we combine structural, computational, and biochemical approaches to design peptides that inhibit the ASF1-histone interaction. Starting from the structure of the human ASF1-histone complex, we developed a rational design strategy combining epitope tethering and optimization of interface contacts to identify a potent peptide inhibitor with a dissociation constant of 3 nM. When introduced into cultured cells, the inhibitors impair cell proliferation, perturb cell-cycle progression, and reduce cell migration and invasion in a manner commensurate with their affinity for ASF1. Finally, we find that direct injection of the most potent ASF1 peptide inhibitor in mouse allografts reduces tumor growth. Our results open new avenues to use ASF1 inhibitors as promising leads for cancer therapy.

Role for Gag-CA Interdomain Linker in Primate Lentiviral Replication

Gag proteins underlie retroviral replication by fulfilling numerous functional roles at various stages during viral life cycle. Out of the four mature proteins, Gag-capsid (CA) is a major component of viral particles, and has been most well studied biogenetically, biochemically and structurally. Gag-CA is composed of two structured domains, and also of a short stretch of disordered and flexible interdomain linker. While the two domains, namely, N-terminal and C-terminal domains (NTD and CTD), have been the central target for Gag research, the linker region connecting the two has been poorly studied. We recently have performed systemic mutational analyses on the Gag-CA linker region of HIV-1 by various experimental and in silico systems. In total, we have demonstrated that the linker region acts as a cis-modulator to optimize the Gag-related viral replication process. We also have noted, during the course of conducting the research project, that HIV-1 and SIVmac, belonging to distinct primate lentiviral lineages, share a similarly biologically active linker region with each other. In this brief article, we summarize and report the results obtained by mutational studies that are relevant to the functional significance of the interdomain linker of HIV/SIV Gag-CA. Based on this investigation, we discuss about the future directions of the research in this line.

Targeting trimeric transmembrane domain 5 of oncogenic latent membrane protein 1 using a computationally designed peptide

A peptide inhibitor was designed in silico and validated experimentally to disrupt homotrimeric transmembrane helix assembly.

Protein–protein interactions are involved in diverse biological processes. These interactions are therefore vital targets for drug development. However, the design of peptide modulators targeting membrane-based protein–protein interactions is a challenging goal owing to the lack of experimentally-determined structures and efficient protocols to probe their functions. Here we employed rational peptide design and molecular dynamics simulations to design a membrane-insertable peptide that disrupts the strong trimeric self-association of the fifth transmembrane domain (TMD5) of the oncogenic Epstein–Barr virus (EBV) latent membrane protein-1 (LMP-1). The designed anti-TMD5 peptide formed 1 : 2 heterotrimers with TMD5 in micelles and inhibited TMD5 oligomerization in bacterial membranes. Moreover, the designed peptide inhibited LMP-1 homotrimerization based on NF-κB activity in EVB positive lymphoma cells. The results indicated that the designed anti-TMD5 peptide may represent a promising starting point for elaboration of anti-EBV therapeutics via inhibition of LMP-1 oligomerization. To the best of our knowledge, this represents the first example of disrupting homotrimeric transmembrane helices using a designed peptide inhibitor.

Tailoring the properties of (catalytically)-active inclusion bodies

Background

Immobilization is an appropriate tool to ease the handling and recycling of enzymes in biocatalytic processes and to increase their stability. Most of the established immobilization methods require case-to-case optimization, which is laborious and time-consuming. Often, (chromatographic) enzyme purification is required and stable immobilization usually includes additional cross-linking or adsorption steps. We have previously shown in a few case studies that the molecular biological fusion of an aggregation-inducing tag to a target protein induces the intracellular formation of protein aggregates, so called inclusion bodies (IBs), which to a certain degree retain their (catalytic) function. This enables the combination of protein production and immobilization in one step. Hence, those biologically-produced immobilizates were named catalytically-active inclusion bodies (CatIBs) or, in case of proteins without catalytic activity, functional IBs (FIBs). While this strategy has been proven successful, the efficiency, the potential for optimization and important CatIB/FIB properties like yield, activity and morphology have not been investigated systematically.

Results

We here evaluated a CatIB/FIB toolbox of different enzymes and proteins. Different optimization strategies, like linker deletion, C- versus N-terminal fusion and the fusion of alternative aggregation-inducing tags were evaluated. The obtained CatIBs/FIBs varied with respect to formation efficiency, yield, composition and residual activity, which could be correlated to differences in their morphology; as revealed by (electron) microscopy. Last but not least, we demonstrate that the CatIB/FIB formation efficiency appears to be correlated to the solvent-accessible hydrophobic surface area of the target protein, providing a structure-based rationale for our strategy and opening up the possibility to predict its efficiency for any given target protein.

Conclusion

We here provide evidence for the general applicability, predictability and flexibility of the CatIB/FIB immobilization strategy, highlighting the application potential of CatIB-based enzyme immobilizates for synthetic chemistry, biocatalysis and industry.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1081-5) contains supplementary material, which is available to authorized users.

Discovery and engineering of enhanced SUMO protease enzymes

Small ubiquitin-like modifier (SUMO) is commonly used as a protein fusion domain to facilitate expression and purification of recombinant proteins, and a SUMO-specific protease is then used to remove SUMO from these proteins. Although this protease is highly specific, its limited solubility and stability hamper its utility as an in vitro reagent. Here, we report improved SUMO protease enzymes obtained via two approaches. First, we developed a computational method and used it to re-engineer WT Ulp1 from Saccharomyces cerevisiae to improve protein solubility. Second, we discovered an improved SUMO protease via genomic mining of the thermophilic fungus Chaetomium thermophilum, as proteins from thermophilic organisms are commonly employed as reagent enzymes. Following expression in Escherichia coli, we found that these re-engineered enzymes can be more thermostable and up to 12 times more soluble, all while retaining WT-or-better levels of SUMO protease activity. The computational method we developed to design solubility-enhancing substitutions is based on the RosettaScripts application for the macromolecular modeling suite Rosetta, and it is broadly applicable for the improvement of solution properties of other proteins. Moreover, we determined the X-ray crystal structure of a SUMO protease from C. thermophilum to 1.44 Å resolution. This structure revealed that this enzyme exhibits structural and functional conservation with the S. cerevisiae SUMO protease, despite exhibiting only 28% sequence identity. In summary, by re-engineering the Ulp1 protease and discovering a SUMO protease from C. thermophilum, we have obtained proteases that are more soluble, more thermostable, and more efficient than the current commercially available Ulp1 enzyme.

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.

Review: Engineering of thermostable enzymes for industrial applications

The catalytic properties of some selected enzymes have long been exploited to carry out efficient and cost-effective bioconversions in a multitude of research and industrial sectors, such as food, health, cosmetics, agriculture, chemistry, energy, and others. Nonetheless, for several applications, naturally occurring enzymes are not considered to be viable options owing to their limited stability in the required working conditions. Over the years, the quest for novel enzymes with actual potential for biotechnological applications has involved various complementary approaches such as mining enzyme variants from organisms living in extreme conditions (extremophiles), mimicking evolution in the laboratory to develop more stable enzyme variants, and more recently, using rational, computer-assisted enzyme engineering strategies. In this review, we provide an overview of the most relevant enzymes that are used for industrial applications and we discuss the strategies that are adopted to enhance enzyme stability and/or activity, along with some of the most relevant achievements. In all living species, many different enzymes catalyze fundamental chemical reactions with high substrate specificity and rate enhancements. Besides specificity, enzymes also possess many other favorable properties, such as, for instance, cost-effectiveness, good stability under mild pH and temperature conditions, generally low toxicity levels, and ease of termination of activity. As efficient natural biocatalysts, enzymes provide great opportunities to carry out important chemical reactions in several research and industrial settings, ranging from food to pharmaceutical, cosmetic, agricultural, and other crucial economic sectors.

Thermal stabilization of the deglycating enzyme Amadoriase I by rational design

Amadoriases are a class of FAD-dependent enzymes that are found in fungi, yeast and bacteria and that are able to hydrolyze glycated amino acids, cleaving the sugar moiety from the amino acidic portion. So far, engineered Amadoriases have mostly found practical application in the measurement of the concentration of glycated albumin in blood samples. However, these engineered forms of Amadoriases show relatively low absolute activity and stability levels, which affect their conditions of use. Therefore, enzyme stabilization is desirable prior to function-altering molecular engineering. In this work, we describe a rational design strategy based on a computational screening method to evaluate a library of potentially stabilizing disulfide bonds. Our approach allowed the identification of two thermostable Amadoriase I mutants (SS03 and SS17) featuring a significantly higher T₅₀ (55.3 °C and 60.6 °C, respectively) compared to the wild-type enzyme (52.4 °C). Moreover, SS17 shows clear hyperstabilization, with residual activity up to 95 °C, whereas the wild-type enzyme is fully inactive at 55 °C. Our computational screening method can therefore be considered as a promising approach to expedite the design of thermostable enzymes.

Computational tools help improve protein stability but with a solubility tradeoff

Accurately predicting changes in protein stability upon amino acid substitution is a much sought after goal. Destabilizing mutations are often implicated in disease, whereas stabilizing mutations are of great value for industrial and therapeutic biotechnology. Increasing protein stability is an especially challenging task, with random substitution yielding stabilizing mutations in only ∼2% of cases. To overcome this bottleneck, computational tools that aim to predict the effect of mutations have been developed; however, achieving accuracy and consistency remains challenging. Here, we combined 11 freely available tools into a meta-predictor (meieringlab.uwaterloo.ca/stabilitypredict/). Validation against ∼600 experimental mutations indicated that our meta-predictor has improved performance over any of the individual tools. The meta-predictor was then used to recommend 10 mutations in a previously designed protein of moderate thermodynamic stability, ThreeFoil. Experimental characterization showed that four mutations increased protein stability and could be amplified through ThreeFoil's structural symmetry to yield several multiple mutants with >2-kcal/mol stabilization. By avoiding residues within functional ties, we could maintain ThreeFoil's glycan-binding capacity. Despite successfully achieving substantial stabilization, however, almost all mutations decreased protein solubility, the most common cause of protein design failure. Examination of the 600-mutation data set revealed that stabilizing mutations on the protein surface tend to increase hydrophobicity and that the individual tools favor this approach to gain stability. Thus, whereas currently available tools can increase protein stability and combining them into a meta-predictor yields enhanced reliability, improvements to the potentials/force fields underlying these tools are needed to avoid gaining protein stability at the cost of solubility.

Lignin-derived inhibition of monocomponent cellulases and a xylanase in the hydrolysis of lignocellulosics

Non-productive enzyme binding onto lignin is the major inhibitory mechanism, which reduces hydrolysis rates and yields and prevents efficient enzyme recycling in the hydrolysis of lignocellulosics. The detailed mechanisms of binding are still poorly understood. Enzyme-lignin interactions were investigated by comparing the structural properties and binding behaviour of fungal monocomponent enzymes, cellobiohydrolases TrCel7A and TrCel6A, endoglucanases TrCel7B and TrCel5A, a xylanase TrXyn11 and a β-glucosidase AnCel3A, onto lignins isolated from steam pretreated spruce and wheat straw. The enzymes exhibited decreasing affinity onto lignin model films in the following order: TrCel7B>TrCel6A>TrCel5A>AnCel3A>TrCel7A>TrXyn11. As analysed in Avicel hydrolysis, TrCel6A and TrCel7B were most inhibited by lignin isolated from pretreated spruce. This could be partially explained by adsorption of the enzyme onto the lignin surface. Enzyme properties, such as enzyme surface charge, thermal stability or surface hydrophobicity could not alone explain the adsorption behaviour.

An Evolution-Based Approach to De Novo Protein Design

EvoDesign is a computational algorithm that allows the rapid creation of new protein sequences that are compatible with specific protein structures. As such, it can be used to optimize protein stability, to resculpt the protein surface to eliminate undesired protein-protein interactions, and to optimize protein-protein binding. A major distinguishing feature of EvoDesign in comparison to other protein design programs is the use of evolutionary information in the design process to guide the sequence search toward native-like sequences known to adopt structurally similar folds as the target. The observed frequencies of amino acids in specific positions in the structure in the form of structural profiles collected from proteins with similar folds and complexes with similar interfaces can implicitly capture many subtle effects that are essential for correct folding and protein-binding interactions. As a result of the inclusion of evolutionary information, the sequences designed by EvoDesign have native-like folding and binding properties not seen by other physics-based design methods. In this chapter, we describe how EvoDesign can be used to redesign proteins with a focus on the computational and experimental procedures that can be used to validate the designs.

Tertiary alphabet for the observable protein structural universe

Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.

Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability

Upon heterologous overexpression, many proteins misfold or aggregate, thus resulting in low functional yields. Human acetylcholinesterase (hAChE), an enzyme mediating synaptic transmission, is a typical case of a human protein that necessitates mammalian systems to obtain functional expression. We developed a computational strategy and designed an AChE variant bearing 51 mutations that improved core packing, surface polarity, and backbone rigidity. This variant expressed at ∼2,000-fold higher levels in E. coli compared to wild-type hAChE and exhibited 20°C higher thermostability with no change in enzymatic properties or in the active-site configuration as determined by crystallography. To demonstrate broad utility, we similarly designed four other human and bacterial proteins. Testing at most three designs per protein, we obtained enhanced stability and/or higher yields of soluble and active protein in E. coli. Our algorithm requires only a 3D structure and several dozen sequences of naturally occurring homologs, and is available at http://pross.weizmann.ac.il.

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A new computational method is used to stabilize five recalcitrant proteins

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Designed variants show higher expression and stability with unmodified function

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A designed human acetylcholinesterase variant expresses solubly in bacteria

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The method is fully automated and implemented on a webserver

Computational protein design for given backbone: recent progresses in general method-related aspects

To achieve high success rate in protein design requires a reliable sequence design method to find amino acid sequences that stably fold into a desired backbone structure. This problem is addressed by computational protein design through the approach of energy minimization. Here we review recent method progresses related to improving the accuracy of this approach. First, the quality of the energy model is a key factor. Second, with structure sensitive energy functions, whether and how backbone flexibility is considered can have large effects on design accuracy, although usually only small adjustments of the backbone structure itself are involved. Third, the effective accuracy of design results can be boosted by post-processing a small number of designed sequences with complementary models that may not be efficient enough for full sequence optimization. Finally, computational method development will benefit greatly from increasingly efficient experimental approaches that can be applied to obtain extensive feedbacks.

De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity

In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.

Using natural sequences and modularity to design common and novel protein topologies

Protein design is still a challenging undertaking, often requiring multiple attempts or iterations for success. Typically, the source of failure is unclear, and scoring metrics appear similar between successful and failed cases. Nevertheless, the use of sequence statistics, modularity and symmetry from natural proteins, combined with computational design both at the coarse-grained and atomistic levels is propelling a new wave of design efforts to success. Here we highlight recent examples of design, showing how the wealth of natural protein sequence and topology data may be leveraged to reduce the search space and increase the likelihood of achieving desired outcomes.

Competitive Coadsorption Dynamics of Viruses and Dissolved Organic Matter to Positively Charged Sorbent Surfaces

Adsorption onto solid-water interfaces is a key process governing the fate and transport of waterborne viruses. Although negatively charged viruses are known to extensively adsorb onto positively charged adsorbent surfaces, virus adsorption in such systems in the presence of negatively charged dissolved organic matter (DOM) as coadsorbate remains poorly studied and understood. This work provides a systematic assessment of the adsorption dynamics of negatively charged viruses (i.e., bacteriophages MS2, fr, GA, and Qβ) and polystyrene nanospheres onto a positively charged model sorbent surface in the presence of varying DOM concentrations. In all systems studied, DOM competitively suppressed the adsorption of the viruses and nanospheres onto the model surface. Electrostatic repulsion of the highly negatively charged MS2, fr, and the nanospheres impaired their adsorption onto DOM adlayers that formed during the coadsorption process. In contrast, the effect of competition on overall adsorption was attenuated for less-negatively charged GA and Qβ because these viruses also adsorbed onto DOM adlayer surfaces. Competition in MS2-DOM coadsorbate systems were accurately described by a random sequential adsorption model that explicitly accounts for the unfolding of adsorbed DOM. Consistent findings for viruses and nanospheres suggest that the coadsorbate effects described herein generally apply to systems containing negatively charged nanoparticles and DOM.

Viruses at Solid-Water Interfaces: A Systematic Assessment of Interactions Driving Adsorption

Adsorption to solid-water interfaces is a major process governing the fate of waterborne viruses in natural and engineered systems. The relative contributions of different interaction forces to adsorption and their dependence on the physicochemical properties of the viruses remain, however, only poorly understood. Herein, we systematically studied the adsorption of four bacteriophages (MS2, fr, GA, and Qβ) to five model surfaces with varying surface chemistries and to three dissolved organic matter adlayers, as a function of solution pH and ionic strength, using quartz crystal microbalance with dissipation monitoring. The viruses were selected to have similar sizes and shapes but different surface charges, polarities, and topographies, as identified by modeling the distributions of amino acids in the virus capsids. Virus-sorbent interactions were governed by long-ranged electrostatics and favorable contributions from the hydrophobic effect, and shorter-ranged van der Waals interactions were of secondary importance. Steric effects depended on the topographic irregularities on both the virus and sorbent surfaces. Differences in the adsorption characteristics of the tested viruses were successfully linked to differences in their capsid surface properties. Besides identifying the major interaction forces, this work highlights the potential of computable virus surface charge and polarity descriptors to predict virus adsorption to solid-water interfaces.

Assessing the Indirect Photochemical Transformation of Dissolved Combined Amino Acids through the Use of Systematically Designed Histidine-Containing Oligopeptides

Photooxidation is an important abiotic transformation pathway for amino acids (AAs) in sunlit waters. Although dissolved free AAs are well studied, the photooxidation of dissolved combined AAs (DCAAs) remains poorly investigated. This study is a systematic investigation of the effect of neighboring photostable AA residues (i.e., aliphatic, cationic, anionic, or aromatic residues) on the environmental indirect photochemical transformation of histidine (His) in His-containing oligopeptides. The pKa values of His residues in the studied oligopeptides were found to be between 4.3 and 8.1. Accordingly, the phototransformation rate constants of the His-containing oligopeptides were highly pH-dependent in an environmentally relevant pH range with higher reactivity for neutral His than for the protonated species. The photostable AA residues significantly modulated the photoreactivity of oligopeptides either through altering the accessibility of His to photochemically produced oxidants or through shifting the pKa values of His residues. In addition, the influence of neighboring photostable AA residues on the sorption-enhanced phototransformation of oligopeptides in solutions containing chromophoric dissolved organic matter (CDOM) was assessed. The constituent photostable AA residues promoted sorption of His-containing oligopeptides to CDOM macromolecules through electrostatic attraction, hydrophobic effects, and/or low-barrier hydrogen bonds, and subsequently increased the apparent phototransformation rate constants by up to 2 orders of magnitude.

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies.

Few proteins carry out their tasks in isolation. Instead, proteins combine with each other in complicated ways that can be affected by either the natural genetic variation that occurs among people or by disease causing mutations such as those that occur in cancer or in genetic disorders. To understand how these mutations affect our health, it is necessary to understand how mutations can affect the strength of the interactions that bind proteins together. This is a difficult task to do in a laboratory on a large scale and scientists are increasingly turning to computational methods to predict these effects in advance. We show that by looking at the multiple alignments of similar protein-protein complex structures at the interface regions, new constraints based on the evolution of the three dimensional structures of proteins can be made to predict which mutations are compatible with two proteins interacting and which are not.

Methods for library-scale computational protein design

Faced with a protein engineering challenge, a contemporary researcher can choose from myriad design strategies. Library-scale computational protein design (LCPD) is a hybrid method suitable for the engineering of improved protein variants with diverse sequences. This chapter discusses the background and merits of several practical LCPD techniques. First, LCPD methods suitable for delocalized protein design are presented in the context of example design calculations for cellobiohydrolase II. Second, localized design methods are discussed in the context of an example design calculation intended to shift the substrate specificity of a ketol-acid reductoisomerase Rossmann domain from NADPH to NADH.

Morphological diversity and polymorphism of self-assembling collagen peptides controlled by length of hydrophobic domains

Synthetic collagen mimetic peptides are used to probe the role of hydrophobic forces in mediating protein self-assembly. Higher order association is an integral property of natural collagens, which assemble into fibers and meshes that comprise the extracellular matrix of connective tissues. The unique triple-helix fold fully exposes two-thirds of positions in the protein to solvent, providing ample opportunities for engineering interaction sites. Inclusion of just a few hydrophobic groups in a minimal peptide promotes a rich variety of self-assembly behaviors, resulting in hundred-nanometer to micron size nanodiscs and nanofibers. Morphology depends primarily on the length of hydrophobic domains. Peptide discs contain lipophilic domains capable of sequestering small hydrophobic dyes. Combining multiple peptide types result in composite structures of discs and fibers ranging from stars to plates-on-a-string. These systems provide valuable tools to shed insight into the fundamental principles underlying hydrophobicity-driven higher order protein association that will facilitate the design of self-assembling systems in biomaterials and nanomedical applications.

Lignin triggers irreversible cellulase loss during pretreated lignocellulosic biomass saccharification

BACKGROUND

Non-productive binding of enzymes to lignin is thought to impede the saccharification efficiency of pretreated lignocellulosic biomass to fermentable sugars. Due to a lack of suitable analytical techniques that track binding of individual enzymes within complex protein mixtures and the difficulty in distinguishing the contribution of productive (binding to specific glycans) versus non-productive (binding to lignin) binding of cellulases to lignocellulose, there is currently a poor understanding of individual enzyme adsorption to lignin during the time course of pretreated biomass saccharification.

RESULTS

In this study, we have utilized an FPLC (fast protein liquid chromatography)-based methodology to quantify free Trichoderma reesei cellulases (namely CBH I, CBH II, and EG I) concentration within a complex hydrolyzate mixture during the varying time course of biomass saccharification. Three pretreated corn stover (CS) samples were included in this study: Ammonia Fiber Expansion(a) (AFEX™-CS), dilute acid (DA-CS), and ionic liquid (IL-CS) pretreatments. The relative fraction of bound individual cellulases varied depending not only on the pretreated biomass type (and lignin abundance) but also on the type of cellulase. Acid pretreated biomass had the highest levels of non-recoverable cellulases, while ionic liquid pretreated biomass had the highest overall cellulase recovery. CBH II has the lowest thermal stability among the three T. reesei cellulases tested. By preparing recombinant family 1 carbohydrate binding module (CBM) fusion proteins, we have shown that family 1 CBMs are highly implicated in the non-productive binding of full-length T. reesei cellulases to lignin.

CONCLUSIONS

Our findings aid in further understanding the complex mechanisms of non-productive binding of cellulases to pretreated lignocellulosic biomass. Developing optimized pretreatment processes with reduced or modified lignin content to minimize non-productive enzyme binding or engineering pretreatment-specific, low-lignin binding cellulases will improve enzyme specific activity, facilitate enzyme recycling, and thereby permit production of cheaper biofuels.

On simplified global nonlinear function for fitness landscape: a case study of inverse protein folding

The construction of fitness landscape has broad implication in understanding molecular evolution, cellular epigenetic state, and protein structures. We studied the problem of constructing fitness landscape of inverse protein folding or protein design, with the aim to generate amino acid sequences that would fold into an a priori determined structural fold which would enable engineering novel or enhanced biochemistry. For this task, an effective fitness function should allow identification of correct sequences that would fold into the desired structure. In this study, we showed that nonlinear fitness function for protein design can be constructed using a rectangular kernel with a basis set of proteins and decoys chosen a priori. The full landscape for a large number of protein folds can be captured using only 480 native proteins and 3,200 non-protein decoys via a finite Newton method. A blind test of a simplified version of fitness function for sequence design was carried out to discriminate simultaneously 428 native sequences not homologous to any training proteins from 11 million challenging protein-like decoys. This simplified function correctly classified 408 native sequences (20 misclassifications, 95% correct rate), which outperforms several other statistical linear scoring function and optimized linear function. Our results further suggested that for the task of global sequence design of 428 selected proteins, the search space of protein shape and sequence can be effectively parametrized with just about 3,680 carefully chosen basis set of proteins and decoys, and we showed in addition that the overall landscape is not overly sensitive to the specific choice of this set. Our results can be generalized to construct other types of fitness landscape.

Computational library design for increasing haloalkane dehalogenase stability

We explored the use of a computational design framework for the stabilization of the haloalkane dehalogenase LinB. Energy calculations, disulfide bond design, molecular dynamics simulations, and rational inspection of mutant structures predicted many stabilizing mutations. Screening of these in small mutant libraries led to the discovery of seventeen point mutations and one disulfide bond that enhanced thermostability. Mutations located in or contacting flexible regions of the protein had a larger stabilizing effect than mutations outside such regions. The combined introduction of twelve stabilizing mutations resulted in a LinB mutant with a 23 °C increase in apparent melting temperature (Tm,app , 72.5 °C) and an over 200-fold longer half-life at 60 °C. The most stable LinB variants also displayed increased compatibility with co-solvents, thus allowing substrate conversion and kinetic resolution at much higher concentrations than with the wild-type enzyme.

Predicting enzyme adsorption to lignin films by calculating enzyme surface hydrophobicity

The inhibitory action of lignin on cellulase cocktails is a major challenge to the biological saccharification of plant cell wall polysaccharides. Although the mechanism remains unclear, hydrophobic interactions between enzymes and lignin are hypothesized to drive adsorption. Here we evaluate the role of hydrophobic interactions in enzyme-lignin binding. The hydrophobicity of the enzyme surface was quantified using an estimation of the clustering of nonpolar atoms, identifying potential interaction sites. The adsorption of enzymes to lignin surfaces, measured using the quartz crystal microbalance, correlates to the hydrophobic cluster scores. Further, these results suggest a minimum hydrophobic cluster size for a protein to preferentially adsorb to lignin. The impact of electrostatic contribution was ruled out by comparing the isoelectric point (pI) values to the adsorption of proteins to lignin surfaces. These results demonstrate the ability to predict enzyme-lignin adsorption and could potentially be used to design improved cellulase cocktails, thus lowering the overall cost of biofuel production.

Computationally designed libraries for rapid enzyme stabilization

The ability to engineer enzymes and other proteins to any desired stability would have wide-ranging applications. Here, we demonstrate that computational design of a library with chemically diverse stabilizing mutations allows the engineering of drastically stabilized and fully functional variants of the mesostable enzyme limonene epoxide hydrolase. First, point mutations were selected if they significantly improved the predicted free energy of protein folding. Disulfide bonds were designed using sampling of backbone conformational space, which tripled the number of experimentally stabilizing disulfide bridges. Next, orthogonal in silico screening steps were used to remove chemically unreasonable mutations and mutations that are predicted to increase protein flexibility. The resulting library of 64 variants was experimentally screened, which revealed 21 (pairs of) stabilizing mutations located both in relatively rigid and in flexible areas of the enzyme. Finally, combining 10-12 of these confirmed mutations resulted in multi-site mutants with an increase in apparent melting temperature from 50 to 85°C, enhanced catalytic activity, preserved regioselectivity and a >250-fold longer half-life. The developed Framework for Rapid Enzyme Stabilization by Computational libraries (FRESCO) requires far less screening than conventional directed evolution.

Alternative computational protocols for supercharging protein surfaces for reversible unfolding and retention of stability

Reengineering protein surfaces to exhibit high net charge, referred to as “supercharging”, can improve reversibility of unfolding by preventing aggregation of partially unfolded states. Incorporation of charged side chains should be optimized while considering structural and energetic consequences, as numerous mutations and accumulation of like-charges can also destabilize the native state. A previously demonstrated approach deterministically mutates flexible polar residues (amino acids DERKNQ) with the fewest average neighboring atoms per side chain atom (AvNAPSA). Our approach uses Rosetta-based energy calculations to choose the surface mutations. Both protocols are available for use through the ROSIE web server. The automated Rosetta and AvNAPSA approaches for supercharging choose dissimilar mutations, raising an interesting division in surface charging strategy. Rosetta-supercharged variants of GFP (RscG) ranging from −11 to −61 and +7 to +58 were experimentally tested, and for comparison, we re-tested the previously developed AvNAPSA-supercharged variants of GFP (AscG) with +36 and −30 net charge. Mid-charge variants demonstrated ∼3-fold improvement in refolding with retention of stability. However, as we pushed to higher net charges, expression and soluble yield decreased, indicating that net charge or mutational load may be limiting factors. Interestingly, the two different approaches resulted in GFP variants with similar refolding properties. Our results show that there are multiple sets of residues that can be mutated to successfully supercharge a protein, and combining alternative supercharge protocols with experimental testing can be an effective approach for charge-based improvement to refolding.

Combined computational design of a zinc-binding site and a protein-protein interaction: one open zinc coordination site was not a robust hotspot for de novo ubiquitin binding

We computationally designed a de novo protein-protein interaction between wild-type ubiquitin and a redesigned scaffold. Our strategy was to incorporate zinc at the designed interface to promote affinity and orientation specificity. A large set of monomeric scaffold surfaces were computationally engineered with three-residue zinc coordination sites, and the ubiquitin residue H68 was docked to the open coordination site to complete a tetrahedral zinc site. This single coordination bond was intended as a hotspot and polar interaction for ubiquitin binding, and surrounding residues on the scaffold were optimized primarily as hydrophobic residues using a rotamer-based sequence design protocol in Rosetta. From thousands of independent design simulations, four sequences were selected for experimental characterization. The best performing design, called Spelter, binds tightly to zinc (Kd  < 10 nM) and binds ubiquitin with a Kd of 20 µM in the presence of zinc and 68 µM in the absence of zinc. Mutagenesis studies and nuclear magnetic resonance chemical shift perturbation experiments indicate that Spelter interacts with H68 and the target surface on ubiquitin; however, H68 does not form a hotspot as intended. Instead, mutation of H68 to alanine results in tighter binding. Although a 3/1 zinc coordination arrangement at an interface cannot be ruled out as a means to improve affinity, our study led us to conclude that 2/2 coordination arrangements or multiple-zinc designs are more likely to promote high-affinity protein interactions.

Energy functions in de novo protein design: current challenges and future prospects

In the past decade, a concerted effort to successfully capture specific tertiary packing interactions produced specific three-dimensional structures for many de novo designed proteins that are validated by nuclear magnetic resonance and/or X-ray crystallographic techniques. However, the success rate of computational design remains low. In this review, we provide an overview of experimentally validated, de novo designed proteins and compare four available programs, RosettaDesign, EGAD, Liang-Grishin, and RosettaDesign-SR, by assessing designed sequences computationally. Computational assessment includes the recovery of native sequences, the calculation of sizes of hydrophobic patches and total solvent-accessible surface area, and the prediction of structural properties such as intrinsic disorder, secondary structures, and three-dimensional structures. This computational assessment, together with a recent community-wide experiment in assessing scoring functions for interface design, suggests that the next-generation protein-design scoring function will come from the right balance of complementary interaction terms. Such balance may be found when more negative experimental data become available as part of a training set.