Alteration of Chain-Length Selectivity and Thermostability of Rhizopus oryzae Lipase via Virtual Saturation Mutagenesis Coupled with Disulfide Bond Design

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

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.

Navigating the landscape of enzyme design: from molecular simulations to machine learning

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

Enhancement of thermostability and expression level of Rasamsonia emersonii lipase in Pichia pastoris and its application in biodiesel production in a continuous flow reactor

The acidic lipase from Rasamsonia emersonii named LIPR has great potential for biodiesel synthesis due to its strong methanol tolerance. Nonetheless, the limited thermostability of LIPR and low expression level in Escherichia coli remain major obstacles to its use in biodiesel synthesis. To enhance the thermostability, the mutant LIPR harboring mutations A126C-P238C for the formation of a new disulfide bond and amino acid substitution D214L was obtained through rational design. To our delight, the thermostability of LIPR mutant was greatly improved. Moreover, a comprehensive optimization strategy, such as employing the Mss signal peptide, co-expressing the molecular chaperone protein disulfide isomerase (PDI), knocking out the vacuolar sorting receptor gene VPS10-01, and overexpressing the dihydroxyacetone synthase gene DAS2, was adopted to obtain the combination-optimized mutant Pichia pastoris strain GS54. Furthermore, the biodiesel synthetic capability with the mutant GS54-LIPR was verified and the production yield was 52.2 % after 24 h in a shake flask. Subsequently, a continuous flow system was adopted to increase the biodiesel yield to 73.6 % within 3 h, demonstrating its efficacy in enhancing enzyme biocatalysis. The engineered GS54-LIPR mutant lipase is an efficient and reusable biocatalyst for the sustained production of biodiesel in a continuous flow reaction.

Solvent Tolerance Improvement of Lipases Enhanced Their Applications: State of the Art

Lipases, crucial catalysts in biochemical synthesis, find extensive applications across industries such as food, medicine, and cosmetics. The efficiency of lipase-catalyzed reactions is significantly influenced by the choice of solvents. Polar organic solvents often result in a decrease, or even loss, of lipase activity. Conversely, nonpolar organic solvents induce excessive rigidity in lipases, thereby affecting their activity. While the advent of new solvents like ionic liquids and deep eutectic solvents has somewhat improved the activity and stability of lipases, it fails to address the fundamental issue of lipases' poor solvent tolerance. Hence, the rational design of lipases for enhanced solvent tolerance can significantly boost their industrial performance. This review provides a comprehensive summary of the structural characteristics and properties of lipases in various solvent systems and emphasizes various strategies of protein engineering for non-aqueous media to improve lipases' solvent tolerance. This study provides a theoretical foundation for further enhancing the solvent tolerance and industrial properties of lipases.

In silico design of multipoint mutants for enhanced performance of Thermomyces lanuginosus lipase for efficient biodiesel production

BACKGROUND

Biodiesel, an emerging sustainable and renewable clean energy, has garnered considerable attention as an alternative to fossil fuels. Although lipases are promising catalysts for biodiesel production, their efficiency in industrial-scale application still requires improvement.

RESULTS

In this study, a novel strategy for multi-site mutagenesis in the binding pocket was developed via FuncLib (for mutant enzyme design) and Rosetta Cartesian_ddg (for free energy calculation) to improve the reaction rate and yield of lipase-catalyzed biodiesel production. Thermomyces lanuginosus lipase (TLL) with high activity and thermostability was obtained using the Pichia pastoris expression system. The specific activities of the mutants M11 and M21 (each with 5 and 4 mutations) were 1.50- and 3.10-fold higher, respectively, than those of the wild-type (wt-TLL). Their corresponding melting temperature profiles increased by 10.53 and 6.01 °C, [Formula: see text] (the temperature at which the activity is reduced to 50% after 15 min incubation) increased from 60.88 to 68.46 °C and 66.30 °C, and the optimum temperatures shifted from 45 to 50 °C. After incubation in 60% methanol for 1 h, the mutants M11 and M21 retained more than 60% activity, and 45% higher activity than that of wt-TLL. Molecular dynamics simulations indicated that the increase in thermostability could be explained by reduced atomic fluctuation, and the improved catalytic properties were attributed to a reduced binding free energy and newly formed hydrophobic interaction. Yields of biodiesel production catalyzed by mutants M11 and M21 for 48 h at an elevated temperature (50 °C) were 94.03% and 98.56%, respectively, markedly higher than that of the wt-TLL (88.56%) at its optimal temperature (45 °C) by transesterification of soybean oil.

CONCLUSIONS

An integrating strategy was first adopted to realize the co-evolution of catalytic efficiency and thermostability of lipase. Two promising mutants M11 and M21 with excellent properties exhibited great potential for practical applications for in biodiesel production.

Role of the C-Terminal β Sandwich of Thermoanaerobacter tengcongensis Thermophilic Esterase in Hydrolysis of Long-Chain Acyl Substrates

To search for a novel thermostable esterase for optimized industrial applications, esterase from a thermophilic eubacterium species, Thermoanaerobacter tengcongensis MB4, was purified and characterized in this work. Sequence analysis of T. tengcongensis esterase with other homologous esterases of the same family revealed an apparent tail at the C-terminal that is not conserved across the esterase family. Hence, it was hypothesized that the tail is unlikely to have an essential structural or catalytic role. However, there is no documented report of any role for this tail region. We probed the role of the C-terminal domain on the catalytic activity and substrate preference of T. tengcongensis esterase EstA3 with a view to see how it could be engineered for enhanced properties. To achieve this, we cloned, expressed, and purified the wild-type and the truncated versions of the enzyme. In addition, a naturally occurring member of the family (from Brevibacillus brevis) that lacks the C-terminal tail was also made. In vitro characterization of the purified enzymes showed that the C-terminal domain contributes significantly to the catalytic activity and distinct substrate preference of T. tengcongensis esterase EstA3. All three recombinant enzymes showed the highest preference for paranitrophenyl butyrate (pNPC4), which suggests they are true esterases, not lipases. Kinetic data revealed that truncation had a slight effect on the substrate-binding affinity. Thus, the drop in preference towards long-chain substrates might not be a result of substrate binding affinity alone. The findings from this work could form the basis for future protein engineering allowing the modification of esterase catalytic properties through domain swapping or by attaching a modular protein domain.

Enzyme engineering for functional lipids synthesis: recent advance and perspective

Functional lipids, primarily derived through the modification of natural lipids by various processes, are widely acknowledged for their potential to impart health benefits. In contrast to chemical methods for lipid modification, enzymatic catalysis offers distinct advantages, including high selectivity, mild operating conditions, and reduced byproduct formation. Nevertheless, enzymes face challenges in industrial applications, such as low activity, stability, and undesired selectivity. To address these challenges, protein engineering techniques have been implemented to enhance enzyme performance in functional lipid synthesis. This article aims to review recent advances in protein engineering, encompassing approaches from directed evolution to rational design, with the goal of improving the properties of lipid-modifying enzymes. Furthermore, the article explores the future prospects and challenges associated with enzyme-catalyzed functional lipid synthesis.

Improving the Thermostability of Thermomyces lanuginosus Lipase by Restricting the Flexibility of N-Terminus and C-Terminus Simultaneously via the 25-Loop Substitutions

(1) Lipases are catalysts widely applied in industrial fields. To sustain the harsh treatments in industries, optimizing lipase activities and thermal stability is necessary to reduce production loss. (2) The thermostability of Thermomyces lanuginosus lipase (TLL) was evaluated via B-factor analysis and consensus-sequence substitutions. Five single-point variants (K24S, D27N, D27R, P29S, and A30P) with improved thermostability were constructed via site-directed mutagenesis. (3) The optimal reaction temperatures of all the five variants displayed 5 °C improvement compared with TLL. Four variants, except D27N, showed enhanced residual activities at 80 °C. The melting temperatures of three variants (D27R, P29S, and A30P) were significantly increased. The molecular dynamics simulations indicated that the 25-loop (residues 24-30) in the N-terminus of the five variants generated more hydrogen bonds with surrounding amino acids; hydrogen bond pair D254-I255 preserved in the C-terminus of the variants also contributes to the improved thermostability. Furthermore, the newly formed salt-bridge interaction (R27…E56) in D27R was identified as a crucial determinant for thermostability. (4) Our study discovered that substituting residues from the 25-loop will enhance the stability of the N-terminus and C-terminus simultaneously, restrict the most flexible regions of TLL, and result in improved thermostability.

Study on the Properties and Synergistic Antioxidant Effects of Novel Bifunctional Fusion Proteins Expressed Using the UTuT6 System

Important antioxidant enzymes, glutathione peroxidase (GPx) and superoxide dismutase (SOD), are involved in maintaining redox balance. They can protect each other and result in more efficiently removing excessive reactive oxygen species (ROS), protecting cells against injury, and maintaining the normal metabolism of ROS. In this study, human cytosolic GPx (hGPx1) and human phospholipid hydroperoxide GPx (hGPx4) genes were integrated into the same open reading frame with human extracellular SOD active site (SOD3-72P) genes, respectively, and several novel fusion proteins were obtained by using the UTuT6 expression system for the first time. Among them, Se-hGPx1UAG-L4-SOD3-72P is the bifunctional fusion protein with the highest GPx activity and the best anti-hydrogen peroxide inactivation ability thus far. The Se-hGPx4UAG-L3-SOD3-72P fusion protein exhibits the strongest alkali and high temperature resistance and a greater protective effect against lipoprotein peroxidation damage. Se-hGPx1UAG-L4-SOD3-72P and Se-hGPx4UAG-L3-SOD3-72P fusion proteins both have good synergistic and antioxidant abilities in H2O2-induced RBCs and liver damage models. We believe that this research will help with the development of novel bifunctional fusion proteins and the investigation of the synergistic and catalytic mechanisms of GPx and SOD, which are important in creating novel protein therapeutics.

Tuning Thermostability and Catalytic Efficiency of Aflatoxin-Degrading Enzyme by Error-prone PCR

In our previous work, a recombinant aflatoxin-degrading enzyme derived from Myxococcus fulvus (MADE) was reported. However, the low thermal stability of the enzyme had limitations for its use in industrial applications. In this study, we obtained an improved variant of recombinant MADE (rMADE) with enhanced thermostability and catalytic activity using error-prone PCR. Firstly, we constructed a mutant library containing over 5000 individual mutants. Three mutants with T₅₀ values higher than the wild-type rMADE by 16.5 °C (rMADE-1124), 6.5 °C (rMADE-1795), and 9.8 °C (rMADE-2848) were screened by a high-throughput screening method. Additionally, the catalytic activity of rMADE-1795 and rMADE-2848 was improved by 81.5% and 67.7%, respectively, compared to the wild-type. Moreover, structural analysis revealed that replacement of acidic amino acids with basic amino acids by a mutation (D114H) in rMADE-2848 increased the polar interactions with surrounding residues and resulted in a threefold increase in the t_1/2 value of the enzyme and made it more thermaltolerate. KEY POINTS: • Mutant libraries construction of a new aflatoxins degrading enzyme by error-prone PCR. • D114H/N295D mutant improved enzyme activity and thermostability. • The first reported enhanced thermostability of aflatoxins degrading enzyme better for its application.

De Novo Computational Design of a Lipase with Hydrolysis Activity towards Middle-Chained Fatty Acid Esters

Innovations in biocatalysts provide great prospects for intolerant environments or novel reactions. Due to the limited catalytic capacity and the long-term and labor-intensive characteristics of mining enzymes with the desired functions, de novo enzyme design was developed to obtain industrial application candidates in a rapid and convenient way. Here, based on the catalytic mechanisms and the known structures of proteins, we proposed a computational protein design strategy combining de novo enzyme design and laboratory-directed evolution. Starting with the theozyme constructed using a quantum-mechanical approach, the theoretical enzyme-skeleton combinations were assembled and optimized via the Rosetta "inside-out" protocol. A small number of designed sequences were experimentally screened using SDS-PAGE, mass spectrometry and a qualitative activity assay in which the designed enzyme 1a8uD₁ exhibited a measurable hydrolysis activity of 24.25 ± 0.57 U/g towards p-nitrophenyl octanoate. To improve the activity of the designed enzyme, molecular dynamics simulations and the RosettaDesign application were utilized to further optimize the substrate binding mode and amino acid sequence, thus keeping the residues of theozyme intact. The redesigned lipase 1a8uD₁-M8 displayed enhanced hydrolysis activity towards p-nitrophenyl octanoate-3.34 times higher than that of 1a8uD₁. Meanwhile, the natural skeleton protein (PDB entry 1a8u) did not display any hydrolysis activity, confirming that the hydrolysis abilities of the designed 1a8uD₁ and the redesigned 1a8uD₁-M8 were devised from scratch. More importantly, the designed 1a8uD₁-M8 was also able to hydrolyze the natural middle-chained substrate (glycerol trioctanoate), for which the activity was 27.67 ± 0.69 U/g. This study indicates that the strategy employed here has great potential to generate novel enzymes exhibiting the desired reactions.