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The advent of advanced coatings has transformed material functionalities, extending their roles from basic coverage and visual appeal to include unique properties such as self-healing, superior hydrophobicity, and antimicrobial action. However, the traditional dependency on petrochemical-derived materials for these coatings raises environmental concerns. This study proposes the use of renewable and alternative materials for coating development. We present the use of bioengineered spider silk-inspired protein (SSIP), produced through recombinant technology, as a viable, eco-friendly alternative due to their ease of processing under ambient pressure and the utilization of water as a solvent, alongside their exceptional physicochemical properties. Our research investigates the effects of different thermal treatments and protein concentrations on the mechanical strength and surface water repellency of coatings on silica bases. Our findings reveal a direct correlation between the temperature of heat treatment and the enhancements in surface hydrophobicity and mechanical strength, where elevated temperatures facilitate increased resistance to water and improved mechanical integrity. Consequently, we advocate SSIPs present a promising, sustainable choice for advanced coatings, providing a pathway to fine-tune coating recipes for better mechanical and hydrophobic properties with a reduced ecological footprint, finding potential uses in various fields such as electronics.

Protein engineering increasingly relies on machine learning models to computationally pre-screen promising novel candidates. Although machine learning approaches have proven effective, their performance on prospective screening data leaves room for improvement; prediction accuracy can vary greatly from one protein variant to the next. So far, it is unclear what characterizes variants that are associated with large prediction error. In order to establish whether structural characteristics influence predictability, we created a novel high-order combinatorial dataset for an enzyme spanning 3,706 variants, that can be partitioned into subsets of variants with mutations at positions exclusively belonging to a particular structural class. By training four different supervised variant effect prediction (VEP) models on structurally partitioned subsets of our data, we found that predictability strongly depended on all four structural characteristics we tested; buriedness, number of contact residues, proximity to the active site and presence of secondary structure elements. These dependencies were also found in several single mutation enzyme variant datasets, albeit with dataset specific directions. Most importantly, we found that these dependencies were similar for all four models we tested, indicating that there are specific structure and function determinants that are insufficiently accounted for by current machine learning algorithms. Overall, our findings suggest that improvements can be made to VEP models by exploring new inductive biases and by leveraging different data modalities of protein variants, and that stratified dataset design can highlight areas of improvement for machine learning guided protein engineering.

The formulation of high-concentration monoclonal antibody (mAb) solutions in low dose volumes for autoinjector devices poses challenges in manufacturability and patient administration due to elevated solution viscosity. Often many therapeutically potent mAbs are discovered, but their commercial development is stalled by unfavourable developability challenges. In this work, we present a systematic experimental framework for the computational screening of molecular descriptors to guide the design of 24 mutants with modified viscosity profiles accompanied by experimental evaluation. Our experimental observations using a model anti-IL8 mAb and eight engineered mutant variants reveal that viscosity reduction is influenced by the location of hydrophobic interactions, while targeting positively charged patches significantly increases viscosity in comparison to wild-type anti-IL-8 mAb. We conclude that most predicted in silico physicochemical properties exhibit poor correlation with measured experimental parameters for antibodies with suboptimal developability characteristics, emphasizing the need for comprehensive case-by-case evaluation of mAbs. This framework combining molecular design and triage via computational predictions with experimental evaluation aids the agile and rational design of mAbs with tailored solution viscosities, ensuring improved manufacturability and patient convenience in self-administration scenarios.

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

The thermostable α-amylase derived from Bacillus licheniformis (BLA) has multiple advantages, including enhancing the mass transfer rate and by reducing microbial contamination in starch hydrolysis. Nonetheless, the application of BLA is constrained by the accessibility and stability of enzymes capable of achieving high conversion rates at elevated temperatures. Moreover, the thermotolerance of BLA requires further enhancement. Here, we developed a computational strategy for constructing small and smart mutant libraries to identify variants with enhanced thermostability. Initially, molecular dynamics (MD) simulations were employed to identify the regions with high flexibility. Subsequently, FoldX, a computational design predictor, was used to design mutants by rigidifying highly flexible residues, whereas the simultaneous decrease in folding free energy assisted in improving thermostability. Through the utilization of MD and FoldX, residues K251, T277, N278, K319, and E336, situated at a distance of 5 Å from the catalytic triad, were chosen for mutation. Seventeen mutants were identified and characterized by evaluating enzymatic characteristics and kinetic parameters. The catalytic efficiency of the E271L/N278K mutant reached 184.1 g L−1 s−1, which is 1.88-fold larger than the corresponding value determined for the WT. Furthermore, the most thermostable mutant, E336S, exhibited a 1.43-fold improvement in half-life at 95 ℃, compared with that of the WT. This study, by combining computational simulation with experimental verification, establishes that potential sites can be computationally predicted to increase the activity and stability of BLA and thus provide a possible strategy by which to guide protein design.

FGF21 is an endocrine signaling protein belonging to the family of fibroblast growth factors (FGFs). It has emerged as a molecule of interest for treating various metabolic diseases due to its role in regulating glucogenesis and ketogenesis in the liver. However, FGF21 is prone to heat, proteolytic, and acid-mediated degradation, and its low molecular weight makes it susceptible to kidney clearance, significantly reducing its therapeutic potential. Protein engineering studies addressing these challenges have generally shown that increasing the thermostability of FGF21 led to improved pharmacokinetics. Here, we describe the computer-aided design and experimental characterization of FGF21 variants with enhanced melting temperature up to 15 °C, uncompromised efficacy at activation of MAPK/ERK signaling in Hep G2 cell culture, and ability to stimulate proliferation of Hep G2 and NIH 3T3 fibroblasts cells comparable with FGF21-WT. We propose that stabilizing the FGF21 molecule by rational design should be combined with other reported stabilization strategies to maximize the pharmaceutical potential of FGF21.

Adeno-associated virus (AAV) is a relatively safe and efficient vector for gene therapy. However, due to its 4.7-kb limit of cargo, SpCas9-mediated base editors cannot be packaged into a single AAV vector, which hinders their clinical application. The development of efficient miniature base editors becomes an urgent need. Un1Cas12f1 is a class II V-F-type CRISPR-Cas protein with only 529 amino acids. Although Un1Cas12f1 has been engineered to be a base editor in mammalian cells, the base-editing efficiency is less than 10%, which limits its therapeutic applications. Here, we developed hypercompact and high-efficiency base editors by engineering Un1Cas12f1, fusing non-specific DNA binding protein Sso7d, and truncating single guide RNA (sgRNA), termed STUminiBEs. We demonstrated robust A-to-G conversion (54% on average) by STUminiABEs or C-to-T conversion (45% on average) by STUminiCBEs. We packaged STUminiCBEs into AAVs and successfully introduced a premature stop codon on the PCSK9 gene in mammalian cells. In sum, STUminiBEs are efficient miniature base editors and could readily be packaged into AAVs for biological research or biomedical applications.

Spider silks are natural protein-based biomaterials which are renowned for their mechanical properties and hold great promise for applications ranging from high-performance textiles to regenerative medicine. While some spiders can produce several different types of silks, most spider silk types – including pyriform and aciniform silks – are relatively unstudied. Pyriform and aciniform silks have distinct mechanical behavior and physicochemical properties, with materials produced using combinations of these silks currently unexplored. Here, we introduce an engineered chimeric fusion protein consisting of two repeat units of pyriform (Py) silk followed by two repeat units of aciniform (W) silk named Py2W2. This recombinant ∼86.5 kDa protein is amenable to expression and purification from Escherichia coli and exhibits high α-helicity in a fluorinated acid- and alcohol-based solution used to form a dope for wet-spinning. Wet-spinning enables continuous fiber production and post-spin stretching of the wet-spun fibers in air or following submersion in water or ethanol leads to increases in optical anisotropy, consistent with increased molecular alignment along the fiber axis. Mechanical properties of the fibers vary as a function of post-spin stretching condition, with the highest extensibility and strength observed in air-stretched and ethanol-treated fibers, respectively, with mechanics being superior to fibers spun from either constituent protein alone. Notably, the maximum extensibility obtained (∼157 ± 38 %) is of the same magnitude reported for natural flagelliform silks, the class of spider silk most associated with being stretchable. Interestingly, Py2W2 is also water-compatible, unlike its constituent Py2. Fiber-state secondary structure correlates well with the observed mechanical properties, with depleted α-helicity and increased β-sheet content in cases of increased strength. Py2W2 fibers thus provide enhanced materials behavior in terms of their mechanics, tunability, and fiber properties, providing new directions for design and development of biomaterials suitable and tunable for disparate applications.

Synthetic biology greatly accelerated the building process of potential microbial cell factories for the production of industrially relevant compounds, e.g., chitooligosaccharides (COS) which have an enormous application potential in multiple industries, i.e., pharma, cosmetics and agrifood. COS are produced by the heterologous expression of the chitin oligosaccharide synthase, NodC, in Escherichia coli, mainly yielding mixtures of chitintetraose (A4) and/or chitinpentaose (A5). We rationalised here product formation limitations based on molecular modelling of the structures of several NodC enzymes. We used this information to protein engineer NodC, rendering longer COS. Hence, an in vivo platform of defined COS-producing strains with different degrees of polymerisation was developed and experimentally characterised. Significantly, several strains were producing long COS, such as chitinhexaose (A6) and −heptaose (A7), not identified in any other natural producer. Additionally, other engineered strains efficiently produce almost 100% specific A4 or A5 product. Altogether, our results indicate that electrostatics-driven dynamics effects are to be considered in the molecular ruler hypothesis. Charge density at the transmembrane helices of NodC affects the opening of the integral binding pocket and in this way the length of the produced chitin oligomers can be modulated. As a result, the internal ruler mechanism elaborated and validated in this manuscript can serve as a guideline to perform site-directed mutagenesis at positions in related NodC and chitin synthase enzymes for both industrial applications as for identification of therapeutic targets.

Neuroglobin is a hemoprotein expressed in several nervous system cell lineages with yet unknown physiological functions. Neuroglobin presents a very similar structure to that of the related globins hemoglobin and myoglobin, but shows an hexacoordinate heme as compared to the pentacoordinated heme of myoglobin and hemoglobin. While several reactions of neuroglobin have been characterized in vitro, the relative importance of most of those reactions in vivo is yet undefined. Neuroglobin, like other heme proteins, can reduce nitrite to nitric oxide, providing a possible route to generate nitric oxide in vivo in low oxygen conditions. The reaction kinetics are highly dependent on the nature of the distal residue, and replacement of the distal histidine His64(E7) can increase the reaction rate constants by several orders of magnitude. However, mutation of other distal pocket positions such as Phe28(B10) or Val68(E11) has more limited impact on the rates. Computational analysis using myoglobin as template, guided by the structure of dedicated nitrite reductases like cytochrome cd1 nitrite reductase, has pointed out that combined mutations of the residues B10 and CD1 could increase the nitrite reductase activity of myoglobin, by mimicking the environment of the distal heme pocket in cytochrome cd1 nitrite reductase. As neuroglobin shows high sequence and structural homology with myoglobin, we hypothesized that such mutations (F28H and F42Y in neuroglobin) could also modify the nitrite reductase activity of neuroglobin. Here we study the effect of these mutations. Unfortunately, we do not observe in any case an increase in the nitrite reduction rates. Our results provide some further indications of nitrite reductase regulation in neuroglobin and highlight the minor but critical differences between the structure of penta- and hexacoordinate globins.

Barriers to effective gene therapy for many diseases include the number of modified target cells required to achieve therapeutic outcomes and host immune responses to expressed therapeutic proteins. As long-lived cells specialized for protein secretion, antibody-secreting B cells are an attractive target for foreign protein expression in blood and tissue. To neutralize HIV-1, we developed a lentiviral vector (LV) gene therapy platform for delivery of the anti-HIV-1 immunoadhesin, eCD4-Ig, to B cells. The EμB29 enhancer/promoter in the LV limited gene expression in non-B cell lineages. By engineering a knob-in-hole-reversed (KiHR) modification in the CH3-Fc eCD4-Ig domain, we reduced interactions between eCD4-Ig and endogenous B cell immunoglobulin G proteins, which improved HIV-1 neutralization potency. Unlike previous approaches in non-lymphoid cells, eCD4-Ig-KiHR produced in B cells promoted HIV-1 neutralizing protection without requiring exogenous TPST2, a tyrosine sulfation enzyme required for eCD4-Ig-KiHR function. This finding indicated that B cell machinery is well suited to produce therapeutic proteins. Lastly, to overcome the inefficient transduction efficiency associated with VSV-G LV delivery to primary B cells, an optimized measles pseudotyped LV packaging methodology achieved up to 75% transduction efficiency. Overall, our findings support the utility of B cell gene therapy platforms for therapeutic protein delivery.

Adenosine is a potent immunosuppressive metabolite that accumulates in the extracellular space within solid tumors and inhibits the antitumor function of native immune cell responses as well as chimeric antigen receptor (CAR) T-cell therapies. Here, we show that engineered human cells can degrade extracellular adenosine through secretion of adenosine deaminase (ADA) enzymes—a possible therapeutic enhancement for CAR T cells. We first determine that the high-activity ADA1 isoform is naturally intracellularly restricted and show that the addition of canonical or computationally predicted secretory peptides did not allow for improved secretion. We did, however, determine that the lower-activity ADA2 isoform is naturally secreted. Thus, we utilized phylogenetic-based structural comparisons to guide a mutational survey of ADA2 active site residues, which when coupled with a high-throughput screen for enhanced ADA2-mediated extracellular adenosine rate allowed isolation of the most catalytically efficient ADA2 variant reported to date. When expressed by human cells, this variant exhibits 30× higher extracellular adenosine degradation activity than the wild-type enzyme. Finally, we demonstrate that Jurkat and CAR T cells engineered to express this secreted, high-activity ADA2 variant can degrade significant amounts of extracellular adenosine in vitro.

Natural products synthesized by plants have substantial industrial and medicinal values and are therefore attracting increasing interest in various related industries. Among the key enzyme families involved in the biosynthesis of natural products, uridine diphosphate-dependent glycosyltransferases (UGTs) play a crucial role in plants. In recent years, significant efforts have been made to elucidate the catalytic mechanisms and substrate recognition of plant UGTs and to improve them for desired functions. In this review, we presented a comprehensive overview of all currently published structures of plant UGTs, along with in-depth analyses of the corresponding catalytic and substrate recognition mechanisms. In addition, we summarized and evaluated the protein engineering strategies applied to improve the catalytic activities of plant UGTs, with a particular focus on high-throughput screening methods. The primary objective of this review is to provide readers with a comprehensive understanding of plant UGTs and to serve as a valuable reference for the latest techniques used to improve their activities.

Applications of lipases in low-water environments are found across a broad range of industries, including the pharmaceutical and oleochemical sectors. This includes condensation reactions in organic solvents where the enzyme activity has been found to depend strongly on both the solvent and the water activity (aw). Despite several experimental and computational studies, knowledge is largely empirical, and a general predictive approach is much needed. To close this gap, we chose native Candida antarctica lipase B (CALB) and two mutants thereof and used molecular dynamics (MD) simulations to gain a molecular understanding of the effect of aw on the specific activity of CALB in hexane. Based on the simulations, we propose four criteria to understand the performance of CALB in organic media, which is supported by enzyme kinetics experiments. First, the lipase must be stable in the organic solvent, which was the case for native CALB and the two mutants studied here. Secondly, water clusters that form and grow close to the active site must not block the path of substrate molecules into the active site. Thirdly, the lipase’s lid must not cover the active site. Finally, mutations and changes in aw must not disrupt the geometry of the active site. We show that mutating specific residues close to the active site can hinder water cluster formation and growth, making the lipase resistant to changes in aw. Our computational screening criteria could potentially be used to screen in-silico designed variants, so only promising candidates could be pushed forward to characterisation.

Organisms have developed effective mechanisms to sense the external environment. Human-designed biosensors exploit this natural optimization, where different biological machinery have been adapted to detect the presence of user-defined molecules. Specifically, the pheromone pathway in the model organism Saccharomyces cerevisiae represents a suitable candidate as a synthetic signaling system. Indeed, it expresses just one G-Protein Coupled Receptor (GPCR), Ste2, able to recognize pheromone and initiate the expression of pheromone-dependent genes. To date, the standard procedure to engineer this system relies on the substitution of the yeast GPCR with another one and on the modification of the yeast G-protein to bind the inserted receptor. Here, we propose an innovative computational procedure, based on geometrical and chemical optimization of protein binding pockets, to select the amino acid substitutions required to make the native yeast GPCR able to recognize a user-defined ligand. This procedure would allow the yeast to recognize a wide range of ligands, without a-priori knowledge about a GPCR recognizing them or the corresponding G protein. We used Monte Carlo simulations to design on Ste2 a binding pocket able to recognize epinephrine, selected as a test ligand. We validated Ste2 mutants via molecular docking and molecular dynamics. We verified that the amino acid substitutions we identified make Ste2 able to accommodate and remain firmly bound to epinephrine. Our results indicate that we sampled efficiently the huge space of possible mutants, proposing such a strategy as a promising starting point for the development of a new kind of S.cerevisiae-based biosensors.

Fusion of catalytic domains can accelerate cascade reactions by bringing enzymes in close proximity. However, the design of a protein fusion and the choice of a linker are often challenging and lack of guidance. To determine the impact of linker parameters on fusion proteins, a library of linkers featuring various lengths, secondary structures, extensions and hydrophobicities was designed. Linkers were used to fuse the lycopene cyclase (crtY) and β-carotene hydroxylase (crtZ) from Pantoea ananatis to create fusion proteins to produce zeaxanthin. The fusion efficiency was assessed by comparing the carotenoids content in a carotenoid-producer Escherichia coli strain. It was shown that in addition to the orientation of the enzymes and the size of the linker, the first amino acid of the linker is also a key factor in determining the efficiency of a protein fusion. The wide range of sequence diversity in our linker library enables the fine tuning of protein fusion and this approach can be easily transferred to other enzyme couples.

Abstract Background The production of monoclonal antibodies for immunoglobulin detection is not cost-effective, while polyclonal antibody production depends on laboratory animals, raising concerns on animal welfare. The widespread use of immunoglobulins in the pharmaceutical industry and the increasing number and variety of new antibodies entering the market require new detection and purification strategies. The Tripartite motif-containing protein 21 is a soluble intracellular immunoglobulin G receptor that binds to the constant region of immunoglobulin G from various species with high affinity. We hypothesized that using this protein as an antibody-binding module to create immunoglobulin detection probes will improve the portfolio of antibody affinity ligands for diagnostic or therapeutic purposes. Results We created a chimeric protein containing a mutated form of the C-terminal domain of mouse Tripartite motif-containing protein 21 linked to streptavidin to detect immunoglobulin G from various species of mammals. The protein is produced by heterologous expression and consists of an improved molecular tool, expanding the portfolio of antibody-affinity ligands for immunoassays. We also demonstrate that this affinity ligand may be used for purification purposes since imidazole elution of antibodies can be achieved instead of acidic elution conditions of current antibody purification methods. Conclusion Data reported here provides an additional and superior alternative to the use of secondary antibodies, expanding the portfolio of antibodies affinity ligands for detection and purification purposes.

Protein-based cancer therapies are considered an alternative to conventional anticancer regimens, providing multifunctional properties while showing low toxicity. However, its widespread use is limited by absorption and instability issues, resulting in higher dosage requirements and a prolonged onset of bioactivity to elicit the desired response. Here, we developed a non-invasive antitumor treatment using designed ankyrin repeat protein (DARPin)-anticancer protein-conjugate that specifically targets the cancer biomarker, epithelial cell adhesion molecule (EpCAM). The DARPin-anticancer proteins bind to EpCAM-positive cancer cells and improve the in vitro anticancer efficacy by over 100-folds within 24 h, where the DARPin-tagged human lactoferrin fragment (drtHLF4) IC50 value is within the nanomolar range. Orally administered drtHLF4 was readily absorbed into the systemic flow of the HT-29 cancer murine model, exerting its anticancer effect on other tumors in the host body. Orally administered drtHFL4 cleared HT29-colorectal tumors using a single dose, whereas intratumoral injection cleared HT29-subcutaneous tumors within three doses. This approach addresses the limitations of other protein-based anticancer treatments by providing a non-invasive anticancer therapy with improved potency and tumor-specificity.

The human infectious disease COVID-19 caused by the SARS-CoV-2 virus has become a major threat to global public health. Developing a vaccine is the preferred prophylactic response to epidemics and pandemics. However, for individuals who have contracted the disease, the rapid design of antibodies that can target the SARS-CoV-2 virus fulfils a critical need. Further, discovering antibodies that bind multiple variants of SARS-CoV-2 can aid in the development of rapid antigen tests (RATs) which are critical for the identification and isolation of individuals currently carrying COVID-19. Here we provide a proof-of-concept study for the computational design of high-affinity antibodies that bind to multiple variants of the SARS-CoV-2 spike protein using RosettaAntibodyDesign (RAbD). Well characterized antibodies that bind with high affinity to the SARS-CoV-1 (but not SARS-CoV-2) spike protein were used as templates and re-designed to bind the SARS-CoV-2 spike protein with high affinity, resulting in a specificity switch. A panel of designed antibodies were experimentally validated. One design bound to a broad range of variants of concern including the Omicron, Delta, Wuhan, and South African spike protein variants.

Papain-like cysteine proteases are widely expressed enzymes that mostly regulate protein turnover in the acidic conditions of lysosomes. However, in the last twenty years, these proteases have been evidenced to exert specific functions within different organelles as well as outside the cell. The most studied proteases of this family are human cysteine cathepsins involved both in physiological and pathological processes. The specificity of each protease to its substrates is mostly defined by the structure of the binding cleft. Different patterns of amino acid motif in this area determine the interaction between the protease and the ligands. Moreover, this specificity can be altered under the specific media conditions and in case other proteins are present. Understanding how this network works would allow researchers to design the diagnostic selective probes and therapeutic inhibitors. Moreover, this knowledge might serve as a key for redesigning and de novo engineering of the proteases for a wide range of applications.

Protein solubility is an attractive engineering target primarily due to its relation to yields in protein production and manufacturing. Moreover, better knowledge of the mutational effects on protein solubility could connect several serious human diseases with protein aggregation. However, we have limited understanding of the protein structural determinants of solubility, and the available data have mostly been scattered in the literature. Here, we present SoluProtMutDB – the first database containing data on protein solubility changes upon mutations. Our database accommodates 33000 measurements of 17000 protein variants in 103 different proteins. The database can serve as an essential source of information for the researchers designing improved protein variants or those developing machine learning tools to predict the effects of mutations on solubility. The database comprises all the previously published solubility datasets and thousands of new data points from recent publications, including deep mutational scanning experiments. Moreover, it features many available experimental conditions known to affect protein solubility. The datasets have been manually curated with substantial corrections, improving suitability for machine learning applications. The database is available at loschmidt.chemi.muni.cz/soluprotmutdb.

Synthetic biology is a rapidly growing field with applications in biotechnology and biomedicine. Through various approaches, remarkable achievements, such as cell and tissue engineering, have been already accomplished. In synthetic glycobiology, the engineering of glycan binding proteins is being exploited for producing tools with precise topology and specificity. We developed the concept of engineered chimeric lectins, i.e., Janus lectin, with increased valency, and additional specificity. The novel engineered lectin, assembled as a fusion protein between the β-propeller domain from Ralstonia solanacearum and the β-trefoil domain from fungus Marasmius oreades, is specific for fucose and α-galactose and its unique protein architecture allows to bind these ligands simultaneously. The protein activity was tested with glycosylated giant unilamellar vesicles, resulting in the formation of proto-tissue-like structures through cross-linking of such protocells. The engineered protein recognizes and binds H1299 human lung epithelial cancer cells by its two domains. The biophysical properties of this new construct were compared with the two already existing Janus lectins, RSL-CBM40 and RSL-CBM77Rf. Denaturation profiles of the proteins indicate that the fold of each has a significant role in protein stability and should be considered during protein engineering.

Self-labelling protein tags (SLPs) are resourceful tools that revolutionized sensor imaging, having the versatile ability of being genetically fused with any protein of interest and undergoing activation with alternative probes specifically designed for each variant (namely, SNAP-tag, CLIP-tag and Halo-tag). Commercially available SLPs are highly useful in studying molecular aspects of mesophilic organisms, while they fail in characterizing model organisms that thrive in harsh conditions. By applying an integrated computational and structural approach, we designed a engineered variant of the alkylguanine-DNA-alkyl-transferase (OGT) from the hyper-thermophilic archaeon Saccharolobus solfataricus (SsOGT), with no DNA-binding activity, able to covalently react with O6-benzyl-cytosine (BC-) derivatives, obtaining the first thermostable CLIP-tag, named SsOGT-MC8.The presented construct is able to recognize and to covalently bind BC- substrates with a marked specificity, displaying a very low activity on orthogonal benzyl-guanine (BG-) substrate and showing a remarkable thermal stability that broadens the applicability of SLPs. The rational mutagenesis that, starting from SsOGT, led to the production of SsOGT-MC8 was first evaluated by structural predictions to precisely design the chimeric construct, by mutating specific residues involved in protein stability and substrate recognition. The final construct was further validated by biochemical characterization and X-ray crystallography, allowing us to present here the first structural model of a CLIP-tag establishing the molecular determinants of its activity, as well as proposing a general approach for the rational engineering of any O6-alkylguanine-DNA-alkyl-transferase turning it into a SNAP- and a CLIP-tag variant.

Enzymes with buried active sites maintain their catalytic function via a single tunnel or tunnel network. In this study we analyzed the functionality of soluble epoxide hydrolases (sEHs) tunnel network, by comparing the overall enzyme structure with the tunnel’s shape and size. sEHs were divided into three groups based on their structure and the tunnel usage. The obtained results were compared with known substrate preferences of the studied enzymes, as well as reported in our other work evolutionary analyses data. The tunnel network architecture corresponded well with the evolutionary lineage of the source organism and large differences between enzymes were observed from long fragments insertions. This strategy can be used during protein re-engineering process for large changes introduction, whereas tunnel modification can be applied for fine-tuning of enzyme.

Ionic liquids (IL) and aqueous ionic liquids (aIL) are attractive (co-)solvents for green industrial processes involving biocatalysts, but often reduce enzyme activity. Experimental and computational methods are applied to predict favorable substitution sites and, most often, subsequent site-directed surface charge modifications are introduced to enhance enzyme resistance towards aIL. However, almost no studies evaluate the prediction precision with random mutagenesis or the application of simple data-driven filtering processes. Here, we systematically and rigorously evaluated the performance of 22 previously described structure-based approaches to increase enzyme resistance to aIL based on an experimental complete site-saturation mutagenesis library of Bacillus subtilis Lipase A (BsLipA) screened against four aIL. We show that, surprisingly, most of the approaches yield low gain-in-precision (GiP) values, particularly for predicting relevant positions: 14 approaches perform worse than random mutagenesis. Encouragingly, exploiting experimental information on the thermostability of BsLipA or structural weak spots of BsLipA predicted by rigidity theory yields GiP = 3.03 and 2.39 for relevant variants and GiP = 1.61 and 1.41 for relevant positions. Combining five simple-to-compute physicochemical and evolutionary properties substantially increases the precision of predicting relevant variants and positions, yielding GiP = 3.35 and 1.29. Finally, combining these properties with predictions of structural weak spots identified by rigidity theory additionally improves GiP for relevant variants up to 4-fold to ∼10 and sustains or increases GiP for relevant positions, resulting in a prediction precision of ∼90% compared to ∼9% in random mutagenesis. This combination should be applicable to other enzyme systems for guiding protein engineering approaches towards improved aIL resistance.

The importance of protein engineering in the research and development of biopharmaceuticals and biomaterials has increased. Machine learning in computer-aided protein engineering can markedly reduce the experimental effort in identifying optimal sequences that satisfy the desired properties from a large number of possible protein sequences. To develop general protein descriptors for computer-aided protein engineering tasks, we devised new protein descriptors, one sequence-based descriptor (PCgrades), and three structure-based descriptors (PCspairs, 3D-SPIEs_5.4 Å, and 3D-SPIEs_8Å). While the PCgrades and PCspairs include general and statistical information in physicochemical properties in single and pairwise amino acids respectively, the 3D-SPIEs include specific and quantum–mechanical information with parameterized quantum mechanical calculations (FMO2-DFTB3/D/PCM). To evaluate the protein descriptors, we made prediction models with the new descriptors and previously developed descriptors for diverse protein datasets including protein expression and binding affinity change in SARS-CoV-2 spike glycoprotein. As a result, the newly devised descriptors showed a good performance in diverse datasets, in which the PCspairs showed the best performance (R2=0.783 for protein expression and R2=0.711 for binding affinity). As a result, the newly devised descriptors showed a good performance in diverse datasets, in which the PCspairs showed the best performance. Similar approaches with those descriptors would be promising and useful if the prediction models are trained with sufficient quantitative experimental data from high-throughput assays for industrial enzymes or protein drugs.

Protein stability is a requisite for most biotechnological and medical applications of proteins. As natural proteins tend to suffer from a low conformational stability ex vivo, great efforts have been devoted toward increasing their stability through rational design and engineering of appropriate mutations. Unfortunately, even the best currently used predictors fail to compute the stability of protein variants with sufficient accuracy and their usefulness as tools to guide the rational stabilisation of proteins is limited. We present here Protposer, a protein stabilising tool based on a different approach. Instead of quantifying changes in stability, Protposer uses structure- and sequence-based screening modules to nominate candidate mutations for subsequent evaluation by a logistic regression model, carefully trained to avoid overfitting. Thus, Protposer analyses PDB files in search for stabilization opportunities and provides a ranked list of promising mutations with their estimated success rates (eSR), their probabilities of being stabilising by at least 0.5 kcal/mol. The agreement between eSRs and actual positive predictive values (PPV) on external datasets of mutations is excellent. When Protposer is used with its Optimal kappa selection threshold, its PPV is above 0.7. Even with less stringent thresholds, Protposer largely outperforms FoldX, Rosetta and PoPMusiC. Indicating the PDB file of the protein suffices to obtain a ranked list of mutations, their eSRs and hints on the likely source of the stabilization expected. Protposer is a distinct, straightforward and highly successful tool to design protein stabilising mutations, and it is freely available for academic use at http://webapps.bifi.es/the-protposer.

Global warming is caused by human activity, such as the burning of fossil fuels, which produces high levels of greenhouse gasses. As a consequence, climate change impacts all organisms and the greater ecosystem through changing conditions from weather patterns to the temperature, pH and salt concentrations found in waterways and soil. These environmental changes fundamentally alter many parameters of the living world, from the kinetics of chemical reactions and cellular signaling pathways to the accumulation of unforeseen chemicals in the environment, the appearance and dispersal of new diseases, and the availability of traditional foods. Some organisms adapt to extremes, while others cannot. This article asks five questions that prompt us to consider the foundational knowledge that biochemistry can bring to the table as we meet the challenge of climate change. We approach climate change from the molecular point of view, identifying how cells and organisms – from microbes to plants and animals – respond to changing environmental conditions. To embrace the concept of “one health” for all life on the planet, we argue that we must leverage biochemistry, cell biology, molecular biophysics and genetics to fully understand the impact of climate change on the living world and to bring positive change.

l-Asparaginases catalyze the hydrolysis of l-asparagine to l-aspartic acid and ammonia. These enzymes have potential applications in therapeutics and food industry. Tk1656, a highly active and thermostable l-asparaginase from Thermococcus kodakarensis, has been proved effective in selective killing of acute lymphocytic leukemia cells and in reducing acrylamide formation in baked and fried foods. However, it displayed <5 % activity under physiological conditions compared to the optimal activity at 85 °C and pH 9.5. We have attempted engineering of this valuable enzyme to improve the characteristics required for therapeutic and industrial applications. Based on the literature and crystal structure of Tk1656, nine specific mutant variants were designed, produced in Escherichia coli, and the purified mutant enzymes were compared with the wild-type. One of the mutants, K299L, displayed >20 % increase in activity at 85 °C. H158S substitution resulted in >5 °C increase in the optimal temperature. Similarly, a mesophilic-like mutation L56D, resulted in >5-fold increase in activity at pH 7.0 and 37 °C compared to that of the wild-type enzyme. The substrate specificity of the mutant variants remained unchanged. These results demonstrate that L56D and K299L variants of Tk1656 are the potent enzymes for therapeutics and acrylamide mitigation applications, respectively., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Porphyra is one of the most economically valuable species of red algae, with porphyran being its primary bioactive polysaccharide. Highly active enzymes play a significant role in the research and development of porphyran. This study identified a PKD domain within a polysaccharide-binding protein, displaying an apparent molecular weight (M w ) of 20.20 kDa that is approximately twice the theoretical value, thereby suggesting the possibility of self-aggregation. By fusing it with porphyranase Por16B&#95;Wf, a chimeric enzyme PKD-Por16B was constructed. It was confirmed that the fusion enzyme successfully assembles into an aggregation under the mediation of PKD domain, with its apparent M w (65.13 kDa) significantly higher than theoretical M w (46.02 kDa). The activity of PKD-Por16B was remarkably enhanced from 65.31 U/mg to 325.69 U/mg, accompanied by an improvement in enzymatic stability. Meanwhile, the hydrolysis pattern of PKD-Por16B remained unaltered in comparison to that of Por16B&#95;Wf, indicating no significant deviation in its substrate specificity or reaction mechanism. These results suggest the feasibility of a strategy based on domain-induced aggregation to enhance enzyme activity, which is easy and economical., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Recognizing the critical need to elucidate the molecular determinants of this selectivity offers a pathway to engineer enzymes with broader and more versatile catalytic capabilities. Through integrated methods including phylogenetic analysis, molecular docking, and structural analysis, we identified a pivotal amino acid residue, αTrp116, linking the substrate binding pocket and the active site of a NHase from Pseudonocardia thermophila JCM 3095 (PtNHase). This residue acts as a crucial determinant of substrate specificity within the NHase enzyme. The mutant αW116R modified the substrate specificity of PtNHase, significantly enhancing its catalytic efficiency towards aromatic substrates. The catalytic activity for aromatic compounds such as 3-Cyanopyridine was 14-fold that of the wild-type, whereas its activity for aliphatic substrates diminished to one-sixth. MD simulations revealed that replacing αTrp116 with Arg allowed aromatic nitrile substrates to achieve more favorable conformations within the active site. Based on the mutant αW116R, we further constructed a combinatorial variant Pt-4, tailored for aromatic substrates, which exhibited an enzyme activity 50 times that of the wild-type. These results highlight the critical influence of amino acid residues in the enzyme's active site on substrate specificity and offer fresh perspectives and approaches for the evolution of enzymes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Substrate access tunnel engineering is a useful strategy for enzyme modification. In this study, we improved the catalytic performance of Fe-type Nitrile hydratase (Fe-type NHase) from Pseudomonas fluorescens ZJUT001 (PfNHase) by mutating residue Q86 at the entrance of the substrate access tunnel. The catalytic activity of the mutant PfNHase-αQ86W towards benzonitrile, 2-cyanopyridine, 3-cyanopyridine, and 4-hydroxybenzonitrile was enhanced by 9.35-, 3.30-, 6.55-, and 2.71-fold, respectively, compared to that of the wild-type PfNHase (PfNHase-WT). In addition, the mutant PfNHase-αQ86W showed a catalytic efficiency (k cat /K m ) towards benzonitrile 17.32-fold higher than the PfNHase-WT. Interestingly, the substrate preference of PfNHase-αQ86W shifted from aliphatic nitriles to aromatic nitrile substrates. Our analysis delved into the structural changes that led to this altered substrate preference, highlighting an expanded entrance tunnel region, theenlarged substrate-binding pocket, and the increased hydrophobic interactions between the substrate and enzyme. Molecular dynamic simulations and dynamic cross-correlation Matrix (DCCM) further supported these findings, providing a comprehensive explanation for the enhanced catalytic activity towards aromatic nitrile substrates., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Site-specific incorporation of noncanonical amino acids (ncAAs) can be realized by genetic code expansion (GCE) technology. Different orthogonal tRNA synthetase/tRNA (RS/tRNA) pairs have been developed to introduce a ncAA at the desired site, delivering a wide variety of functionalities that can be installed into selected proteins. Cytoplasmic expression of RS/tRNA pairs can cause a problem with background ncAA incorporation into host proteins. The application of orthogonally translating organelles (OTOs), inspired by the concept of phase separation, provides a solution for this issue in mammalian cells, allowing site-specific and protein-selective ncAA incorporation. So far, only Methanosarcina mazei (Mm) pyrrolysyl-tRNA synthetase (PylRS) has been used within OTOs, limiting the method's potential. Here, we explored the implementation of four other widely used orthogonal RS/tRNA pairs with OTOs, which, to our surprise, were unsuccessful in generating mRNA-selective GCE. Next, we tested several experimental solutions and developed a new chimeric phenylalanyl-RS/tRNA pair that enables ncAA incorporation in OTOs in a site-specific and protein-selective manner. Our work reveals unaccounted design constraints in the spatial engineering of enzyme functions using designer organelles and presents a strategy to overcome those in vivo. We then discuss current limitations and future directions of in-cell engineering in general and protein engineering using GCE specifically., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: “E.A.L. holds patents related to OTOs. M.E.S. and M.J. declare no competing interests.”., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Poly(butylene adipate-co-terephthalate) (PBAT) waste gradually accumulates in the environment, posing ecological risks. Enzymatic hydrolysis holds great potential in the end-of-life management of PBAT, but reported enzymes require high reaction temperatures, limiting their practical industrial applications. In this study, we discovered that the marine fungus Alternaria alternata FB1 can efficiently degrade PBAT at 28 °C. Two cutinases designated as AaCut4 and AaCut10, were identified and verified as key enzymes responsible for this degradation process. Notably, the recombinant AaCut10 was able to depolymerize 82.14 % PBAT within 24 h and fully decompose it within 48 h at 37 °C. Through protein engineering, the yield of terephthalic acid monomer was increased to 96.01 %, highlighting its potential for facilitating PBAT upcycling. Furthermore, based on the investigation of the distribution patterns of PBAT hydrolases, novel degradative agents have been identified within unique ecological niches, leading to the establishment of a comprehensive screening repository of PBAT hydrolases. Overall, our study provides new candidates for enzymatic PBAT recycling with low energy consumption and offers insights into the PBAT degradation manner in ecosystems., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In vivo molecular imaging tools hold immense potential to drive transformative breakthroughs by enabling researchers to visualize cellular and molecular interactions in real-time and/or at high resolution. These advancements will facilitate a deeper understanding of fundamental biological processes and their dysregulation in disease states. Here, we develop and characterize a self-assembling protein nanomicelle called collagen type I binding - thermoresponsive assembled protein (Col1-TRAP) that binds tightly to type I collagen in vitro with nanomolar affinity. For ex vivo visualization, Col1-TRAP is labeled with a near-infrared fluorescent dye (NIR-Col1-TRAP). Both Col1-TRAP and NIR-Col1-TRAP display approximately a 3.8-fold greater binding to type I collagen compared to TRAP when measured by surface plasmon resonance (SPR). We present a proof-of-concept study using NIR-Col1-TRAP to detect fibrotic type I collagen deposition ex vivo in the livers of mice with non-alcoholic steatohepatitis (NASH). We show that NIR-Col1-TRAP demonstrates significantly decreased plasma recirculation time as well as increased liver accumulation in the NASH mice compared to mice without disease over 4 hours. As a result, NIR-Col1-TRAP shows potential as an imaging probe for NASH with in vivo targeting performance after injection in mice. STATEMENT OF SIGNIFICANCE: Direct molecular imaging of fibrosis in NASH patients enables the diagnosis and monitoring of disease progression with greater specificity and resolution than do elastography-based methods or blood tests. In addition, protein-based imaging probes are more advantageous than alternatives due to their biodegradability and scalable biosynthesis. With the aid of computational modeling, we have designed a self-assembled protein micelle that binds to fibrillar and monomeric collagen in vitro. After the protein was labeled with near-infrared fluorescent dye, we injected the compound into mice fed on a NASH diet. NIR-Col1-TRAP clears from the serum faster in these mice compared to control mice, and accumulates significantly more in fibrotic livers.This work advances the development of targeted protein probes for in vivo fibrosis imaging., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jin Kim Montclare reports financial support was provided by National Institutes of Health. Edward Fisher reports financial support was provided by National Institutes of Health. Ann Marie Schmidt reports financial support was provided by National Institutes of Health. Youssef Wadghiri reports financial support was provided by National Institutes of Health. Andrew Wang reports financial support was provided by National Institutes of Health. Jin Kim Montclare reports financial support was provided by National Science Foundation. Jin Kim Montclare has patent A novel collagen-binding protein micelle for the non-invasive imaging of non-alcoholic steatohepatitis (NASH) pending to Jin Kim Montclare, Andrew Wang. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Transaminases (EC 2.6.1.X, TAs) are important biocatalysts in the synthesis of chiral amines, and have significant value in the field of medicine. However, TAs suffer from low enzyme activity and poor catalytic efficiency in the synthesis of chiral amines or non-natural amino acids, which hinders their industrial applications. In this study, a novel TA derived from Paracoccus pantotrophus (ppTA) that was investigated in our previous study was employed with a semi-rational design strategy to improve its enzyme activity to 2-ketobutyrate. By using homology modeling and molecular docking, four surrounding sites in the substrate-binding S pocket were selected as potential mutational sites. Through alanine scanning and saturation mutagenesis, the optimal mutant V153A with significantly improved enzyme activity was finally obtained, which was 578 % higher than that of the wild-type ppTA (WT). Furthermore, the mutant enzyme ppTA-V153A also exhibited slightly improved temperature and pH stability compared to WT. Subsequently, the mutant was used to convert 2-ketobutyrate for the preparation of L-2-aminobutyric acid (L-ABA). The mutant can tolerate 300 mM 2-ketobutyrate with a conversion rate of 74 %, which lays a solid foundation for the preparation of chiral amines., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

(S)-equol, the most influential metabolite of daidzein in vivo, has aroused great attention due to the excellent biological activities. Although existing studies have accomplished the construction of its heterologous synthetic pathway in the context of anaerobicity and inefficiency of natural strains, the low productivity of (S)-equol limits its industrial application. Here, rational design strategies based on decreasing the pocket steric hindrance and fine-tuning the pocket microenvironment to systematically redesign the binding pocket of enzyme were developed and processed to the rate-limiting enzyme dihydrodaidzein reductase in (S)-equol synthesis. After iterative combinatorial mutagenesis, an effective mutant S118G/T169A capable of significantly increasing (S)-equol yield was obtained. Computational analyses illustrated that the main reason of the increased activity relied on the decreased critical distance and more stable interacting conformation. Then, the reaction optimization was performed, and the recombinant Escherichia coli whole-cell biocatalyst harboring S118G/T169A enabled the efficient conversion of 2 mM daidzein to (S)-equol, achieving conversion rate of 84.5 %, which was 2.9 times higher than that of the parental strain expressing wide type dihydrodaidzein reductase. This study provides an effective idea and a feasible method for enzyme modification and whole-cell catalytic synthesis of (S)-equol, and will greatly accelerate the process of industrial production., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Transduced MSCs that express engineered ACE2 could be highly beneficial to combat COVID-19. Engineered ACE2 can act as decoy targets for the virus, preventing its entry into healthy lung cells. To this end, genetic engineering techniques were used to integrate the ACE2 gene into the MSCs genome. The MSCs were evaluated for proper expression and functionality. The mutated form of ACE2 was characterized using various techniques such as protein expression analysis, binding affinity against spike protein, thermal stability assessment, and enzymatic activity assays. The functionality of the mACE2 was assessed on SARS-CoV-2 using the virus-neutralizing test. The obtained results indicated that by introducing specific mutations in the ACE2 gene, the resulting mutant ACE2 had enhanced interaction with viral spike protein, its thermal stability was increased, and its enzymatic function was inhibited as a decoy receptor. Moreover, the mACE2 protein showed higher efficacy in the neutralization of the SARS-CoV-2. In conclusion, this study proposes a novel approach with potential benefits such as targeted drug delivery and reduced side effects on healthy tissues. These transduced MSCs can also be used in combination with other anti-COVID-19 treatments. Design of similar engineered biomolecules with desired properties could also be used to target other diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The continuously increasing level of atmospheric CO 2 in the atmosphere has led to global warming. Converting CO 2 into other carbon compounds could mitigate its atmospheric levels and produce valuable products, as CO 2 also serves as a plentiful and inexpensive carbon feedstock. However, the inert nature of CO 2 poses a major challenge for its reduction. To meet the challenge, nature has evolved metalloenzymes using transition metal ions like Fe, Ni, Mo, and W, as well as electron-transfer partners for their functions. Mimicking these enzymes, artificial metalloenzymes (ArMs) have been designed using alternative protein scaffolds and various metallocofactors like Ni, Co, Re, Rh, and FeS clusters. Both the catalytic efficiency and the scope of CO 2 -reduction product of these ArMs have been improved over the past decade. This review first focuses on the natural metalloenzymes that directly reduce CO 2 by discussing their structures and active sites, as well as the proposed reaction mechanisms. It then introduces the common strategies for electrochemical, photochemical, or photoelectrochemical utilization of these native enzymes for CO 2 reduction and highlights the most recent advancements from the past five years. We also summarize principles of protein design for bio-inspired ArMs, comparing them with native enzymatic systems and outlining challenges and opportunities in enzymatic CO 2 reduction., Competing Interests: Declaration of competing interest We declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Perillyl alcohol (POH) is a secondary metabolite of plants. POH and its derivatives are known to be effective as an anticancer treatment. In this study, oxidative derivatives of POH, which are difficult to synthesize chemically, were synthesized using the engineered bacterial cytochrome P450 BM3 (CYP102A1) as a biocatalyst. The activity of wild-type (WT) CYP102A1 and 29 engineered enzymes toward POH was screened using a high-performance liquid chromatography. They produced one major product. Among them, the engineered CYP102A1 M601 mutant with seven mutations (R47L/F81I/F87V/E143G/L150F/L188Q/E267V) showed the highest conversion, 6.4-fold higher than the WT. Structure modeling using AlphFold2 and PyMoL suggests that mutations near the water channel may be responsible for the increased catalytic activity of the M601 mutant. The major product was identified as a POH-8,9-epoxide by gas chromatography-mass spectrometry and nuclear magnetic resonance analysis. The optimal temperature and pH for the product formation were 35 °C and pH 7.4, respectively. The k cat and K m of M601 were 540 min -1 and 2.77 mM, respectively. To improve POH-8,9-epoxide production, substrate concentration and reaction time were optimized. The optimal condition for POH-8,9-epoxide production by M601 was 5.0 mM POH, pH 7.4, 35 ℃, and 6 h reaction, which produced the highest concentration of 1.72 mM. Therefore, the biosynthesis of POH-8,9-epoxide using M601 as a biocatalyst is suggested to be an efficient and sustainable synthetic process that can be applied to chemical and pharmaceutical industries., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Keratin is one of the major components of solid waste, and the degradation products have extensive applications in various commercial industries. Due to the complexity of the structure of keratin, especially the disulfide bonds between keratin polypeptides, keratinolytic activity is efficient with a mixture of proteins with proteases, peptidases, and oxidoreductase activity. The present work aimed to create an engineered chimeric protein with a disulfide reductase domain and a protease domain connected with a flexible linker. The structure, stability, and substrate interaction were analyzed using the protein modeling tools and codon-optimized synthetic gene cloned, expressed, and purified using Ni 2+ -NTA chromatography. The keratinolytic activity of the protein was at its maximum at 70 °C. The suitable pH for the enzyme activity was pH 8. While Ni 2+ , Mg 2+ , and Na + inhibited the keratinolytic activity, Cu 2+ , Ca 2+ , and Mn 2+ enhanced it significantly. Biochemical characterization of the protease domain indicated significant keratinolytic activity at 70 °C at pH 10.0 but was less efficient than the chimeric protein. Experiments using feathers as the substrate showed a clear degradation pattern in the SEM analysis. The samples collected from the degradation experiments indicated the release of proteins (2-fold) and amino acids (8.4-fold) in a time-dependent manner. Thus, the protease with an added disulfide reductase domain showed excellent keratin degradation activity and has the potential to be utilized in the commercial industries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Ethyl carbamate (EC) is classified as a Class 2A carcinogen, and is present in various fermented foods, posing a threat to human health. Urethanase (EC 3.5.1.75) can catalyze EC to produce ethanol, CO 2 and NH 3 . The urethanase (cpUH) from Candida parapsilosis can hydrolyze EC, but its low affinity and poor stability hinder its application. Here, the structure of cpUH from Candida parapsilosis was determined with a resolution of 2.66 Å. Through sequence alignment and site-directed mutagenesis, it was confirmed that cpUH contained the catalytic triad Ser-cisSer-Lys of the amidase family. Then, the structure-oriented engineering mutant N194V of urethanase was obtained. Its urethanase activity increased by 6.12 %, the catalytic efficiency (k cat /Km) increased by 21.04 %, and the enzyme stability was also enhanced. Modeling and molecular docking analysis showed that the variant N194V changed the number of hydrogen bonds between the substrate and the catalytic residue, resulting in enhanced catalytic ability. MD simulation also demonstrated that the introduction of hydrophobic amino acid Val reduced the RMSD value and increased protein stability. The findings of this study suggest that the N194V variant exhibits significant potential for industrial applications due to its enhanced affinity for substrate binding, improved catalytic efficiency, and increased enzyme stability., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Lijuan Yang, Xian Zhang, Zhiping Feng, JunLiu has patent #ZL202111205058.6 licensed to Lijuan Yang, Xian Zhang, Zhiping Feng, JunLiu. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Zearalenone (ZEN) is a fungal toxin produced by Fusarium exospore, which poses a significant threat to both animal and human health due to its reproductive toxicity. Removing ZEN through ZEN lactonase is currently the most effective method reported, however, all published ZEN lactonases suffer from the poor thermal stability, losing almost all activity after 10 min of treatment at 55℃. In this study, we heterologously expressed ZHD11A from Phialophora macrospora and engineered it via semi-rational design. A mutant I160Y-G242S that can retain about 40 % residual activity at 55℃ for 10 min was obtained, which is the most heat-tolerant ZEN hydrolase reported to date. Moreover, the specific activity of the I160Y-G242S was also elevated 2-fold compared to ZHD11A from 220 U/mg to 450 U/mg, which is one of the most active ZEN lactonses reported. Dynamics analysis revealed that the decreased flexibility of the main-chain carbons contributes to increased thermal stability and the improved substrate binding affinity and catalytic turnover contribute to enhanced activity of variant I160Y-G242S. In all, the mutant I160Y-G242S is an excellent candidate for the industrial application of ZEN degradation., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Enzyme-driven recycling of PET has now become a fully developed industrial process. With the right pre-treatment, PET can be completely depolymerized within workable timeframes. This has been realized due to extensive research conducted over the past decade, resulting in a large set of engineered PET hydrolases. Among various engineering strategies to enhance PET hydrolases, fusion with binding domains has been used to tune affinity and boost activity of the enzymes. While fusion enzymes have demonstrated higher activity in many cases, these results are primarily observed under conditions that would not be economically viable at scale. Furthermore, the wide variation in PET substrates, conditions, and combinations of PET hydrolases and binding domains complicates direct comparisons. Here, we present a self-consistent and thorough analysis of two leading PET hydrolases, LCC ICCG and PHL7. Both enzymes were evaluated both without and with a substrate-binding domain across a range of industrially relevant PET substrates. We demonstrate that the presence of a substrate-binding module does not significantly affect the affinity of LCC ICCG and PHL7 for PET. However, significant differences exist in how the fusion enzymes act on different PET substrates and solid substrate loading, ranging from a 3-fold increase in activity to a 6-fold decrease. These findings could inform the tailoring of enzyme choice to different industrial scenarios., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing financial or personal relationships that would influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Enhancing the thermostability of enzymes is crucial for industrial applications. Methods such as directed evolution are often limited by the huge sequence space and combinatorial explosion, making it difficult to obtain optimal mutants. In recent years, machine learning (ML)-guided protein engineering has become an attractive tool because of its ability to comprehensively explore the sequence space of enzymes and discover superior mutants. This study employed ML to perform combinatorial mutation design on the pectin lyase PMGL-Ba from Bacillus licheniformis, aiming to improve its thermostability. First, 18 single-point mutants with enhanced thermostability were identified through semi-rational design. Subsequently, the initial library containing a small number of low-order mutants was utilized to construct an ML model to explore the combinatorial sequence space (theoretically 196,608 mutants) of single-point mutants. The results showed that the ML-predicted second library was successfully enriched with highly thermostable combinatorial mutants. After one iteration of learning, the best-performing combinatorial mutant in the third library, P36, showed a 67-fold and 39-fold increase in half-life at 75 °C and 80 °C, respectively, as well as a 2.1-fold increase in activity. Structural analysis and molecular dynamics simulations provided insights into the improved performance of the engineered enzyme., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Nature has developed extremozymes that catalyze complex reaction processes in extreme environmental conditions. Accordingly, a combined approach consisting of extremozyme screening, ancestral sequence resurrection (ASR), and molecular dynamic simulation was utilized to construct a developed endoglucanase. The primary experimental and in-silico data led to the prediction of a hypothetical sequence of endoglucanase (EG5-G131) using Bacillus sp. G131 confirmed by amplification and sequencing. EG5-G131 exhibited noticeable stability in a broad-pH range, several detergents, organic solvents, and temperatures up to 80 °C. The molecular weight, V max , and K m of the purified endoglucanase were estimated to be 36 kDa, 4.32 μmol/min, and 23.62 mg/ml, respectively. The calculated thermodynamic parameters for EG5-G131 confirmed its intrinsic thermostability. Computational analysis revealed Glu142 and Glu230 as active-site residues of the enzyme. Furthermore, the enzyme remained bound to cellotetraose at 298 K, 333 K, 343 K, and 353 K for 300 ns, consistent with our experimental data. ASR of EG5-G131 led to the introduction of ancestral ANC204 and ANC205, which show similar thermodynamic characteristics with the last Firmicute common ancestor. Finally, truncating loops from the N-terminal of two sequences created two variants with desirable thermal stability, suggesting the evolutionary deciphering of the functional domain of the GH5 family in Bacillus sp. G131., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests in this communication., (Copyright © 2024. Published by Elsevier B.V.)

There has been ongoing interest in improving the efficiency of glycoside hydrolase for synthesizing glycoside compounds through protein engineering, given the potential applications of glycoside compounds. In this study, a strategy of modifying the substrate access tunnel was proposed to enhance the efficiency of reverse hydrolysis catalyzed by Aspergillus niger α-L-rhamnosidase. Analysis of the tunnel dynamics identified Tyr299 as a key modifiable residue in the substrate access tunnel. The location of Tyr299 was near the enzyme surface and at the outermost end of the substrate access tunnel, suggested its role in substrate recognition and throughput. Based on the properties of side chains, six mutants were designed and expressed by Pichia pastoris. Compared to WT, the reverse hydrolysis efficiencies of mutants Y299P and Y299W were increased by 21.3 % and 11.1 %, respectively. The calculation results of binding free energy showed that the binding free energy was inversely proportional to the reverse hydrolysis efficiency. Further, when binding free energy levels were comparable, the mutants with shorter side chains displayed a higher reverse hydrolysis efficiency. These results proved that substrate access tunnel modification was an effective method to improve the reverse hydrolysis efficacy of α-L-rhamnosidase and also provided new insights for modifying other glycoside hydrolases., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The present work reports on two approaches to enhance catalase (CAT) activity and its stability by using two simple, green processes. In the first procedure, CAT was transiently exposed to an ionic liquid (IL) in the presence of redox molecules related to CAT structure which resulted in partial denaturation. The other method, which uses high hydraulic pressure (HHP) to partially denature CAT (in the presence of redox molecules), has the advantage of being completely reagentless. In both cases, partial denaturation was followed by dialysis, hence refolding and entrapment of redox molecules within the modified 3-D CAT structure (affording a "wired" enzyme). The two approaches to enzyme "wiring" are discussed comparatively from the point of view of the parameters used during the procedure, residual enzyme activity, nature of the modifier, interaction between CAT and the redox molecules, antioxidant activity, and stability over time of the modified protein. Samples of CAT modified in the presence of iron sulfate heptahydrate from each series, respectively, were used to make enzyme electrodes which were tested as amperometric biosensors for hydrogen peroxide detection. Both showed catalytic effect and linear behavior and have potential for applications in the food industry, pharmaceuticals and the textile industry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Lipases play a vital role in various biological processes, from lipid metabolism to industrial applications. However, the ever-evolving challenges and diverse substrates necessitate the continual exploration of novel high-performance lipases. In this study, we employed an in silico mining approach to search for lipases with potential high sn-1,3 selectivity and catalytic activity. The identified novel lipase, PLL, from Paenibacillus larvae subsp. larvae B-3650 exhibited a specific activity of 111.2 ± 5.5 U/mg towards the substrate p-nitrophenyl palmitate (pNPP) and 6.9 ± 0.8 U/mg towards the substrate olive oil when expressed in Escherichia coli (E. coli). Computational design of cysteine mutations was employed to enhance the catalytic performance of PLL. Superior stability was achieved with the mutant K7C/A386C/H159C/K108C (2M3/2M4), showing an increase in melting temperature (T m ) by 1.9°C, a 2.05-fold prolonged half-life at 45°C, and no decrease in enzyme activity. Another mutant, K7C/A386C/A174C/A243C (2M1/2M3), showed a 4.9-fold enhancement in specific activity without compromising stability. Molecular dynamics simulations were conducted to explore the mechanisms of these two mutants. Mutant 2M3/2M4 forms putative disulfide bonds in the loop region, connecting the N- and C-termini of PLL, thus enhancing overall structural rigidity without impacting catalytic activity. The cysteines introduced in mutant 2M1/2M3 not only form new intramolecular hydrogen bonds but also alter the polarity and volume of the substrate-binding pocket, facilitating the entry of large substrate pNPP. These results highlight an efficient in silico exploration approach for novel lipases, offering a rapid and efficient method for enhancing catalytic performance through rational protein design., Competing Interests: Declaration of Competing Interest The authors declare that there are no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Xylanases have broad applications in the food industry to decompose the complex carbohydrate xylan. This is applicable to enhance juice clarity, improve dough softness, or reduce beer turbidity. It can also be used to produce prebiotics and increase the nutritional value in foodstuff. However, the low yield and poor stability of most natural xylanases hinders their further applications. Therefore, it is imperative to explore higher-quality xylanases to address the potential challenges that appear in the food industry and to comprehensively improve the production, modification, and utilization of xylanases. Xylanases, due to their various sources, exhibit diverse characteristics that affect production and activity. Most fungi are suitable for solid-state fermentation to produce xylanases, but in liquid fermentation, microbial metabolism is more vigorous, resulting in higher yield. Fungi produce higher xylanase activity, but bacterial xylanases perform better than fungal ones under certain extreme conditions (high temperature, extreme pH). Gene and protein engineering technology helps to improve the production efficiency of xylanases and enhances their thermal stability and catalytic properties., (Copyright © 2024 Elsevier Inc. All rights reserved.)