A method for improving substrate specificity of aldehyde ketone reductase

Abstract

The present application belongs to the technical field of biotechnology and enzyme engineering, and relates to a molecular modification method for improving substrate specificity of aldehyde ketone reductase, which is achieved by constructing a substrate library of aldehyde ketone reductase AKR13B3 and analyzing kinetic parameters, determining a mutation site by performing loop structure analysis and amino acid sequence alignment on a complex structure of aldehyde ketone reductase AKR13B3, coenzyme NADPH and substrate 3-keto-DON, and screening a mutant with increased substrate specificity, the present application designs the geometric shape of the entrance loop region of the substrate binding pocket of AKR13B3 to change substrate preference and realize the increase of catalytic activity of the enzyme on specific substrates, in addition, the present application provides a feasible scheme for designing aldehyde ketone reductase with good substrate specificity, and provides great hope for developing high-efficiency enzyme preparations.

Description

Technical Field

[0001] This invention belongs to the field of aldehyde-ketone reductase technology, specifically relating to a molecular modification method for improving the substrate specificity of aldehyde-ketone reductase. Background Technology

[0002] Among the various mycotoxins that contaminate crops, deoxynivalenol (DON) is the most frequently detected mycotoxin from Fusarium infections. Therefore, for public health and feed / food safety, it is necessary to adopt effective strategies to reduce DON toxicity. Compared with physical and chemical detoxification methods, the enzyme cascade catalysis of dehydrogenases and aldehyde-ketone reductases is the most promising strategy for DON biodegradation.

[0003] Recently, two DON-degrading enzymes (DADH and AKR13B3) were discovered in Devosi strain A6-2-2. DADH degrades DON to the less toxic 3-keto-DON, while AKR13B3 degrades DON to the less toxic 3-keto-DON. AKR13B3 degrades 3-keto-DON to the relatively non-toxic 3-epi-DON. However, its substrate heterozygosity is a concern. AKR13B3 not only degrades 3-keto-DON to 3-epi-DON, but also exhibits higher catalytic activity for certain aldehyde substrates. MTT analysis showed that the IC50 values ​​for 3-epi-DON, 3-keto-DON, and DON... 50 The values ​​were 146, 1.24, and 0.409 μg / mL, respectively. Enzymatic hydrolysis is an environmentally friendly and efficient method for reducing 3-keto-DON contamination in food or feed; however, the limited catalytic efficiency and specificity of enzymes hinder their widespread industrial application. Identifying mutants with stronger substrate specificity and catalytic activity using protein engineering strategies would be of great significance for their application in the food and feed industries. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a molecular modification method to improve the substrate specificity of aldehyde-ketone reductase.

[0005] To achieve the objectives of this invention, the following technical solutions will be adopted.

[0006] This method was applied to analyze the composition and kinetic parameters of the substrate library of aldehyde-ketone reductase AKR13B3, determine the structure of aldehyde-ketone reductase AKR13B3, and perform molecular docking with substrate 3-keto-DON(1a) to determine the complex structure of enzyme and substrate. Through loop structure analysis and amino acid sequence alignment, mutation sites were determined, and combinatorial mutants with increased substrate specificity were screened.

[0007] A molecular modification method to improve the substrate specificity of aldehyde-ketone reductases includes the following steps:

[0008] S1. Construct a substrate library for aldehyde-ketone reductase AKR13B3;

[0009] S2. By measuring the reaction rate at different substrate concentrations, the kinetic parameters of aldehyde-ketone reductase AKR13B3 with different substrates were analyzed.

[0010] S3. Determine the protein structure of the aldehyde-ketone reductase AKR13B3 and coenzyme NADPH complex, and perform molecular docking with the substrate 3-keto-DON to construct the complex structure of aldehyde-ketone reductase AKR13B3, coenzyme NADPH and substrate 3-keto-DON.

[0011] S4. Perform loop structure analysis on the composite structure to identify all loop structures around the binding pocket of substrate 3-keto-DON. Use the alanine scanning method to find potential mutation sites in loop A, loop B, and loop C. Select potential mutation sites that can reduce the steric hindrance effect and mutate them to valine and glycine. In addition, use amino acid sequence alignment to select non-conserved residues from loop D as mutation sites.

[0012] S5. Combine all the mutation sites obtained in step S4 to induce mutagenesis, so as to obtain mutants that can improve the substrate specificity and catalytic efficiency of aldehyde reductase.

[0013] As a preferred embodiment of the present invention, the substrate library includes 1a: 3-keto-DON, 1b: propionaldehyde, 1c: butyraldehyde, 1d: furfural, 1e: glutaraldehyde, and 1f: benzaldehyde.

[0014] As a preferred embodiment of the present invention, the dynamic parameters include K m k cat k cat / K m .

[0015] As a preferred embodiment of the present invention, the analysis of the dynamic parameters is completed by fitting the Michaelis equations using GraphPad Prism 8 software.

[0016] As a preferred embodiment of the present invention, the protein structure is obtained by prediction using the AlphaFold server.

[0017] As a preferred embodiment of the present invention, the three-dimensional structure of the substrate 3-keto-DON is obtained by Chem3D 20.0 drawing software or the ZINC database.

[0018] As a preferred embodiment of the present invention, the molecular docking is performed using AutoDock Vina 1.2.3 software.

[0019] As a preferred embodiment of the present invention, the potential mutation sites include F207, F211, I208, P212, P209, L213, W210, M251, L255, P253, I254, P255, T257, S258, K259, F25, M28, R29, L30, T31, D33, I35, W36, P38, P39, T95, S97, Q101, P103, P104, and L105.

[0020] As a preferred embodiment of the present invention, the amino acid sequence alignment is performed using the sequence of aldehyde-ketone reductase AKR13B3 and the sequence of AKR13B2 of Devosia sp. D6-9.

[0021] As a preferred embodiment of the present invention, the mutant is T31V / Q101A / P103G.

[0022] As a preferred embodiment of the present invention, the method for quantitatively determining the specificity of the aldehyde-ketone reductase AKR13B3 mutant to substrate A1 / A2 is as follows:

[0023] S A1 / A2 = ×100;

[0024] Where: A1 is 3-keto-DON, and A2 is benzaldehyde.

[0025] Beneficial effects

[0026] This invention provides a molecular modification method to improve the substrate specificity of aldehyde-ketone reductase. This method was applied to analyze the composition and kinetic parameters of an aldehyde-ketone reductase AKR13B3 substrate library, determining the structure of AKR13B3 and performing molecular docking with the substrate 3-keto-DON(1a) to determine the enzyme-substrate complex structure. Through loop structure analysis and amino acid sequence alignment, mutation sites were identified, and combined mutants with increased substrate specificity were screened. Ultimately, an optimal combined mutant, T31V / Q101A / P103G, was determined, exhibiting a 31.94-fold increase in substrate specificity and catalytic activity. The aldehyde-ketone reductase mutant designed in this invention can improve the specificity and catalytic efficiency for the substrate 3-keto-DON(1a), and it has broad development prospects in the industrial application of enzyme detoxification agents. Attached Figure Description

[0027] Figure 1Figure 1 shows the composition and kinetic parameters of the AKR13B3 substrate library described in this invention; wherein: (A) Figure 2 shows the process of AKR13B3 catalyzing the formation of 2a-f products from 1a-f substrates; (B) Figure 3 shows the k values ​​for each substrate. cat and K m Values; (C) The figure shows k for each substrate. cat / K m value;

[0028] Figure 2 The structural model of AKR13B3 and the selected key residues are shown below; (A) The figure shows the structure of AKR13B3 bound to NADPH and substrate 1a, where NADPH and substrate 1a are represented by rod-like structures; (B) The figure uses blue, green, yellow and magenta to represent loop A, loop B, loop C and loop D, respectively; (C) The figure shows the amino acid sequence alignment of AKR13B3 and AKR13B2; (D) The figure shows the screening of key mutation sites.

[0029] Figure 3 The construction of the mutant library and substrate preference evolution described in this invention; wherein: (A) Figure shows the site-directed mutant library construction to reduce spatial obstacles; (B) Figure shows the evolutionary path of AKR13B3;

[0030] Figure 4 S for AKR13B3 and its variants as described in this invention A1 / A2 Values; where: (A) Figure shows the S values ​​of variants obtained from alanine scanning. 1a / 1f Value; (B) The figure shows the S values ​​of variants mutated to glycine and valine. 1a / 1f Value; (C) Figure shows the S of the combined variants 1a / 1f value. Detailed Implementation

[0031] The present invention will be further described in conjunction with the accompanying drawings and embodiments.

[0032] As an embodiment of the present invention, the composition and kinetic parameters of the AKR13B3 substrate library are analyzed.

[0033] (1) The substrate libraries used include 1a: 3-keto-DON, 1b: propionaldehyde, 1c: butyraldehyde, 1d: furfural, 1e: glutaraldehyde, and 1f: benzaldehyde, such as Figure 1 As shown in (A).

[0034] (2) The kinetic parameters (KL) of wild-type AKR13B3 for different substrates were evaluated by measuring the reaction rate at different substrate concentrations (from 1 to 500 µM). m k cat k cat / K mThe Michaelis equations were fitted using GraphPad Prism 8 software, and then the dynamic parameters were evaluated, such as... Figure 1 As shown in (B).

[0035] As an embodiment of the present invention, the structural model of AKR13B3 and the selected key residues are described.

[0036] (1) The AKR13B3 / NADPH complex was predicted using the AlphaFold server (https: / / alphafoldserver.com / ); the three-dimensional structure of the substrate 3-keto-DON was obtained using Chem3D 20.0 plotting software or the ZINC database (http: / / zinc.docking.org). The amino acid sequences were aligned using Jalview (https: / / www.jalview.org / ). In this invention, AutoDock Vina 1.2.3 software was used for molecular docking, such as... Figure 2 As shown in (A); PyMol 2.5.5 software is used to process and visualize the receptor protein before docking.

[0037] (2) By analyzing the enzyme / substrate / coenzyme complex structure, the loop around the substrate binding pocket was determined. The three-dimensional structure showed that four loops A, B, C, and D were located at the entrance of the active center. Then, the key amino acid residues on the loop were identified as key amino acid residues, such as... Figure 2 (B) shows the sequence alignment. Furthermore, sequence alignment of AKR13B3 with AKR13B2 (PDB: 8HNQ) of Devosia sp. D6-9 was also completed, as shown in (B). Figure 2 As shown in (C). Predicting active sites that reduce steric hindrance is one of the important steps in altering substrate specificity. Potential mutation sites within ring A (residues 206-216), ring B (residues 251-259), and ring C (residues 25-39) were searched using an alanine scanning method. Furthermore, considering steric hindrance, glycine was excluded (glycine has the least steric hindrance, allowing only steric hindrance-enhancing mutations). Through structural analysis of the AKR13B3 / NADPH / 1a complex, 25 key residues in rings A, B, and C were selected, such as... Figure 2 As shown in (D). Furthermore, amino acid sequence alignment revealed that six non-conserved residues in ring D were selected as suitable mutation sites.

[0038] As an embodiment of the present invention, the construction of mutant libraries and substrate preference evolution are discussed.

[0039] Using alanine scanning to identify favorable mutation sites is a common and effective method. However, altering the geometry of the ring surrounding the active site may require other strategies to change the substrate preference of AKR13B3. Studies have shown that bulky substrates with polycyclic structures, such as 1a, are more stable in hydrophobic active pockets. Two principles also apply to the selection of the target mutagenesis module: (a) avoiding interactions with polar molecules, excluding polar and charged amino acids; and (b) reducing steric hindrance by replacing mutation sites with smaller amino acid letters. Based on these principles, we first used alanine scanning to select potentially favorable residues. Ten residues were selected to be mutated to two additional hydrophobic amino acids, valine (V) and glycine (G), such as... Figure 3 As shown in (A). The superior single-point variants identified by the above method were subjected to combined mutagenesis, such as... Figure 3 As shown in (B), mutants with stronger substrate specificity and catalytic activity are obtained.

[0040] As an embodiment of the present invention, AKR13B3 and its variants of S A1 / A2 value.

[0041] To accurately describe the substrate preference of AKR13B3 and its variants, a parameter (S) was used. A1 / A2 This parameter is derived from the ratio of the catalytic activity of substrate A1 to that of substrate A2. A1 / A2 A higher value indicates that A1 is more favored than A2. Unsurprisingly, the loop near the substrate-binding pouch provided some favorable mutagenic sites. Based on the alanine scanning strategy, ten single-site variants (F25A, T31A, P39A, S97A, Q101A, P103A, P104A, L105A, F211A, M251A) were obtained, all of which were superior to wild-type AKR13B3, such as... Figure 4 As shown in (A). Subsequently, using a substrate-walking strategy, nine unit variants (T31V, Q101V, Q101G, P103V, P103G, P104V, P104G, L105V, M251V) were found to outperform the wild-type AKR13B3, as shown in (A). Figure 4 As shown in (B). Finally, according to S 1a / 1f Six variants superior to wild-type AKR13B3 (T31V, Q101A, Q101G, P103V, P103A, P103G) were selected as candidate variants for combined mutations, such as... Figure 3 (B) shows the S values ​​of T31V (55.71%), Q101A (51.35%), Q101G (37.80%), P103V (44.41%), P103A (52.57%), and P103G (68.81%). 1a / 1fThe values ​​were higher than those of wild-type AKR13B3 (7.22%), such as... Figure 4 As shown in (A). Based on the initial modification of AKR13B3, the synergistic effect among these six superior unit variants was further explored, resulting in 11 double mutants. The S of the double variants... 1a / 1f The value was significantly higher than that of the single variant, especially the superior dual variant T31V / P103G (167.34%), which was 2.4 times higher than that of variant P103G. Figure 4 As shown in (B), a significant synergistic enhancement effect is observed. In the third round of mutagenesis, S was further designed... 1a / 1f The highest value of T31V / P103G was used to explore the possibility of improving substrate 1a preference. According to S... 1a / 1f The values ​​determined two superior triple variants, T31V / Q101A / P103G and T31V / Q101G / P103G. The S values ​​of T31V / Q101A / P103G (230.58%) and T31V / Q101G / P103G (187.59%) were... 1a / 1f The values ​​are 1.4 times and 1.1 times that of T31V / P103G (167.34%), respectively. Figure 4 As shown in (C). Therefore, this method of designing residues in a loop near the active site may be a feasible option for improving specific substrate preference.

[0042] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A molecular modification method for improving the substrate specificity of aldehyde-ketone reductase, characterized in that: Includes the following steps: S1. Construct a substrate library for aldehyde-ketone reductase AKR13B3, which contains 3-keto-DON, propionaldehyde, butyraldehyde, furfural, glutaraldehyde, and benzaldehyde. S2. The reaction rate was determined at substrate concentrations ranging from 1 to 500 μM. The Michaelis-Menten equation was fitted using GraphPad Prism 8 software to analyze the kinetic parameters of aldehyde-ketone reductase AKR13B3 with different substrates. , , ; S3. The protein structure of the aldehyde-ketone reductase AKR13B3 and the coenzyme NADPH complex was determined by AlphaFold server. The three-dimensional structure of the substrate 3-keto-DON was obtained by Chem3D 20.0 drawing software or ZINC database. The aldehyde-ketone reductase AKR13B3 and the substrate 3-keto-DON were molecularly docked using AutoDockVina 1.2.3 software to construct the complex structure of aldehyde-ketone reductase AKR13B3, coenzyme NADPH and substrate 3-keto-DON. S4. Loop structure analysis was performed on the complex structure to determine the loop A, loop B, loop C, and loop D structures surrounding the substrate 3-keto-DON binding pocket. Alanine scanning was used to identify potential mutation sites within loop A, loop B, and loop C structures. Mutation sites that could reduce steric hindrance effects were screened: F25, T31, P39, S97, Q101, P103, P104, L105, F211, and M251, and these were mutated to valine or glycine. Furthermore, the amino acid sequence of the aldehyde-ketone reductase AKR13B3 was compared with that of AKR13B2 from Devosia sp. D6-9, and non-conserved residues were selected from loop D as mutation sites. S5. Combined mutagenesis was performed on the selected mutation sites that could reduce the steric hindrance effect to obtain the mutant T31V / Q101A / P103G, so as to improve the specificity and catalytic efficiency of aldehyde reductase for 3-keto-DON substrate.

2. The molecular modification method for improving the substrate specificity of aldehyde-ketone reductase according to claim 1, characterized in that: The potential mutation sites include F207, F211, I208, P212, P209, L213, W210, M251, L255, P253, I254, P255, T257, S258, K259, F25, M28, R29, L30, T31, D33, I35, W36, P38, P39, T95, S97, Q101, P103, P104, and L105.

3. The molecular modification method for improving the substrate specificity of aldehyde-ketone reductase according to claim 1, characterized in that: The quantitative determination method for the specificity of the aldehyde-ketone reductase AKR13B3 mutant to substrate A1 / A2 is as follows: S A1 / A2 = ； Where: A1 is 3-keto-DON, and A2 is benzaldehyde.

Images