Method for predicting protoporphyrinogen oxidase (PPO) inhibitor

Abstract

To provide a technique for objectively and accurately predicting the degree of PPO inhibition by using LUMO distribution as a molecular descriptor, and a technique for selecting a PPO inhibitor on the basis of the predicted degree of PPO inhibition.SOLUTION: This method for selecting a PPO inhibitor of the present application is a method for predicting PPO inhibitory activity based on the correlation between LUMO distribution and PPO inhibitory activity for each compound, predicting the degree of PPO inhibitory activity on the basis of the correlation between variation in PPO inhibitory activity among different plant species and the degree of PPO inhibitory activity, and selecting a PPO inhibitor using the predicted PPO inhibitory activity as an index.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method for predicting PPO inhibitors, and more specifically to a method for predicting PPO inhibitors using LUMO (Lowest Unoccupied Molecular Orbital) distributions as "molecular descriptors," and a method for selecting PPO inhibitors using the prediction method. [Background technology]

[0002] In recent years, in the research and development of herbicides, it has become extremely expensive to identify promising lead compounds that have excellent herbicidal activity, reduced human toxicity and crop damage, and ensure safety for the natural environment, and then to further optimize the lead compounds and bring them to market as new herbicides.

[0003] One method for predicting the herbicidal activity of unmeasured compounds is to statistically process the measurement data of numerous measured compounds (reference compounds) and their structural information using in silico methods, and then predict the biological activity of the unmeasured compound based on the degree of structural similarity between the reference compounds and the unmeasured compound. This inductive method is based on the hypothesis that "structural similarity between compounds should lead to similar biological activity, and therefore biological activity can be predicted by displaying the structural 'closeness' of compounds." Compound structural information uses "molecular descriptors," which are quantified versions of a compound's structural features and physicochemical properties (e.g., hydrophobicity and steric parameters) for ease of computerization. This method, based on the Hansh-Fujita method (Non-Patent Document 1), has served as the starting point for various methods for quantitatively analyzing the relationship between chemical structure and physiological activity. Molecular descriptors include hydrophobicity (LogP, π) and steric parameters (MR, STERIMOL, etc.).

[0004] The inductive method described above can use various measurements, such as cell-based measurements, enzyme-based measurements, and animal tests, from databases such as PubChem (https: / / pubchem.ncbi.nlm.nih.gov / ), for herbicide research. However, it is extremely difficult to prepare a quantitative database of similar compounds containing various measurements for studying the correlation between the structure of the required compound and its herbicidal activity in a short period of time. Therefore, objective prediction methods are still insufficient, and the development of such technology has been strongly desired.

[0005] Therefore, in order to efficiently and effectively research and develop candidate herbicide compounds, it is necessary to create significant "molecular descriptors" that predict the structural and electronic complementarity between target enzymes such as PPO, whose three-dimensional structures are known, and each inhibitor compound, and to use these in a quantitative prediction method for enzyme inhibitors.

[0006] Plant PPO inhibitors, also known as "photobleaching herbicides," require light for their herbicidal activity. Research into the mechanism of action of "photobleaching herbicides" has been ongoing for over half a century (Non-Patent Document 2), and they are inhibitors with a long history. Subsequent enzyme-level research has revealed that plant PPO is an enzyme in the pathway that synthesizes porphyrin from aminolevulinic acid (ALA) and is located in plant chloroplasts. When plant PPO is inhibited, protoporphyrinogen IX leaks from the chloroplast into the cytoplasm, where it undergoes autoxidation to become protoporphyrin IX, which accumulates intracellularly (Non-Patent Document 3). In the presence of light and oxygen, protoporphyrin IX generates reactive oxygen species, which then cause light-induced peroxidative damage to biomembranes, resulting in rapid cell death and plant withering (Non-Patent Document 4).

[0007] Whether or not a plant PPO is the site of action is experimentally detected by a method using isolated plant PPO, and it is preferable to obtain the enzyme material from chloroplasts (etioplasts) that are not exposed to light.

[0008] For example, the PPO inhibitory activity of commercially available herbicides is measured as the pI50 (the logarithm of the reciprocal of the molar concentration of a compound that inhibits PPO enzyme activity by 50%) in corn etioplasts, and examples reported include the phenylpyrazole herbicide Pyraflufen Ethyl (ethyl 2-chloro-5-(4-chloro-5-difluoromethoxy-1-methylpyrazol-3-yl)-4-fluorophenoxyacetate), represented by the following structural formula; the diphenyl ether herbicide Oxyfluorofen (2-chloro-4-(trifluoromethyl)phenyl(3-ethoxy-4-nitrophenyl)ether); and the cyclic imide herbicide Chlorophthalim (N-(4-chlorophenyl)-1-cyclohexene-1,2-dicarboximide) (Non-Patent Document 5).

[0009] [ka]

[0010] [ka]

[0011] [ka]

[0012] Other examples of pI50 using corn etioplasts include examples of various cyclic imide compounds including chlorophthalim (Non-Patent Document 6).

[0013] On the other hand, in other plant species, examples of pI50 using barley etioplasts have been reported for various diphenyl ethers including oxyfluorofen (Non-Patent Document 7).

[0014] On the other hand, a pyrazole compound B (1-(5-hydroxy-1,3-dimethyl-1H-pyrazol-4-yl)ethanone) represented by the following structural formula has been reported as a control compound that shows no herbicidal activity (Non-Patent Document 8).

[0015] [ka]

[0016] Crystal structure data for PPO derived from tobacco plants (Nicotiana tabacum) has been reported to contain a three-dimensional structure containing a phenylpyrazole PPO inhibitor A (4-bromo-3-(5'-carboxy-4'-chloro-2'-fluorophenyl)-1-methyl-5-trifluoromethyl-pyrazole) shown in the following structural formula (Non-Patent Document 9), and the crystal structure data can be obtained from the Protein Data Bank (PDB) under the accession number 1SEZ.

[0017] [ka]

[0018] The crystal structure data of PPO derived from myxobacterium (Myxococcus xanthus) (Non-Patent Document 10) and human (Homo sapiens) (Non-Patent Document 11), which contain the diphenyl ether PPO inhibitor acifluorfen (5-[2-chloro-4-(trifluoromethyl)phenoxy]-2-nitrobenzoic acid), shown by the structural formula below, can be obtained from the PDB under accession numbers 12IVD and 3NKS, respectively.

[0019] [ka]

[0020] First, to create a "molecular descriptor" that quantifies the PPO enzyme inhibition reaction, we focused on oxidized flavin adenine dinucleotide (FAD), a PPO coenzyme represented by the following structural formula: Specifically, we hypothesized that oxidized FAD, which normally functions as an electrophilic electron acceptor, has its electrophilicity inhibited by PPO inhibitors.

[0021] [ka]

[0022] However, there have been no previous studies that have demonstrated in detail, based on the three-dimensional structure, how PPO controls the electron transfer reaction using oxidized FAD as an electron acceptor. Therefore, we used frontier orbital theory (Non-Patent Document 12) to predict the chemical reaction based on the interaction between the highest occupied molecular orbital (HOMO) of the electron donor molecule and the lowest unoccupied molecular orbital (LUMO) of the electron acceptor molecule. Specifically, electrons localized in the HOMO of the PPO inhibitor interact with oxidized FAD, resulting in delocalization and mixing with the LUMO of the oxidized FAD molecule. We hypothesized that a correlation with PPO inhibitor activity could be established by quantifying and displaying this change in the LUMO distribution of oxidized FAD as a "molecular descriptor."

[0023] It was not known at all that the LUMO distribution of a bimolecular complex of oxidized FAD and a PPO inhibitor in the PPO inhibitory active site could be used as a "molecular descriptor" to accurately predict the level of PPO inhibition, nor was it known at all that a method for selecting PPO inhibitors could be provided based on the level of PPO inhibition predicted in this way. [Prior art documents] [Non-patent literature]

[0024] [Non-Patent Document 1] C. Hansch and T. Fujita, J. Am. Chem. Soc., (1964) 86, 1616-1626 [Non-licensed document 2] S. Matsunaka, J. Agric. Food Chem, (1969) 17(2), 171-175 [Non-licensed document 3] M. Matringe et al., The Biochemical Journal, (1989) 60, 231-235

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Non-licensed literature 9

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[0025] An objective of the present invention is to provide a technique for predicting the level of PPO inhibition objectively, accurately, and precisely using LUMO distribution as a "molecular descriptor," and a technique for selecting a PPO inhibitor based on the predicted level of PPO inhibition. [Means for solving the problem]

[0026] In view of these circumstances, the present inventors have conducted extensive research in search of a technique for objectively, accurately, and precisely predicting the level of PPO inhibition, and as a result, have discovered that the level of PPO inhibition can be predicted objectively and accurately based on the correlation between the LUMO distribution and the level of PPO inhibition for each compound, thereby completing the present invention. That is, the present invention relates to the following techniques. (1) A method for predicting PPO inhibitors, characterized in that the LUMO distribution is used as a "molecular descriptor" to predict the degree of PPO inhibition. (2) The method for predicting a PPO inhibitor according to claim 1, wherein the PPO inhibitory activity of each compound is predicted based on the correlation between the LUMO distribution and the PPO inhibitory activity. (3) The method for predicting a PPO inhibitor according to claim 1 or 2, wherein the prediction of PPO inhibitor activity based on the correlation is calculated using the following formula in corn and barley: <Corn> PPO inhibitory activity = 0.662 * LUMO distribution index + 5.795 <Barley> PPO inhibitory activity = 0.987 * LUMO distribution index + 2.363 (4) The method for predicting a PPO inhibitor according to claim 1, wherein the level of PPO inhibitory activity is predicted based on a correlation between the difference in variation in PPO inhibitory activity among different plant species and the level of PPO inhibitory activity. (5) A method for selecting a PPO inhibitor, characterized in that the PPO inhibitory activity predicted by any one of (1) to (4) above is used as an index. (6) A PPO inhibitor predicted and selected by a method according to one of (1) to (5). [Effects of the Invention]

[0027] According to the present invention, a technique for predicting the level of PPO inhibition objectively and with high accuracy can be provided. BEST MODE FOR CARRYING OUT THE INVENTION

[0028] (1) Method for predicting PPO inhibitors according to the present invention The method for predicting a PPO inhibitor of the present invention is characterized by using LUMO distribution as a "molecular descriptor" to predict the level of PPO inhibition. To make this prediction, the relationship between the level of PPO inhibition and the LUMO distribution is clarified, and a regression equation or the like showing this relationship is prepared and used for the prediction. Details of this method are described below.

[0029] The general inhibitory activity of PPO inhibitors is measured by pI50, with a higher value indicating stronger activity. The pI50s for pyraflufen ethyl were obtained from Non-Patent Document 5, for cyclic imide compounds from Non-Patent Document 6, for corn from Non-Patent Documents 5 and 6, for chlorophthalim, and for barley from Non-Patent Document 7, and were used for analysis. The pI50 for corn of oxyfluorofen was obtained from Non-Patent Document 5, and the pI50 for barley was obtained from Non-Patent Document 7, and were used for analysis.

[0030] The LUMO of the conformation of the bimolecular complex of oxidized FAD and the inhibitor to be predicted is calculated using the ab initio molecular orbital / density functional theory calculation program GAMESS, and it is desirable to perform the calculation using the 6-31G(2d,p) basis set with the B3LYP functional of the DFT (Density Functional Theory) method.

[0031] The LUMO distribution can be expressed as a "molecular descriptor" according to the following qualitative standard method: 5 = 75% or more to 100% loss, 4 = 50% or more to less than 75% loss, 3 = 25% or more to less than 50% loss, 2 = 1% or more to less than 25% loss, and 1 = no effect, compared to the LUMO distribution of oxidized FAD alone.

[0032] To clarify this relationship, correlation analysis and regression analysis of corn PPO inhibitory activity and LUMO distribution were performed on the corn pI50 of pyraflufen ethyl and oxyfluorofen (Non-Patent Document 5) and the corn pI50 of 41 compounds, including chlorophthalim extracted from cyclic imide systems (Non-Patent Document 6). A significant correlation (correlation coefficient = 0.90) was observed (see Figure 1). It was found that by using the following regression equation calculated in this way, corn PPO inhibitory activity can be predicted with high accuracy from the LUMO distribution. <Corn> pI50=0.662*LUMO distribution+5.795 (Correlation coefficient = 0.90)

[0033] Furthermore, when correlation analysis and regression analysis of barley PPO inhibitory activity and LUMO distribution were performed by extracting 16 diphenyl ether compounds including oxyfluorophen and performing correlation analysis and regression analysis of barley pI50 (Non-Patent Document 7) and LUMO distribution, a significant correlation (correlation coefficient = 0.96) was observed (see Figure 2). It was found that by using the regression equation calculated in this way, PPO inhibitory activity can be predicted with high accuracy from the LUMO distribution. <Barley> pI50=0.987*LUMO distribution+2.363 (Correlation coefficient = 0.96)

[0034] The regression equation for the difference in pI50 variation between the different plant species, corn and barley, and the LUMO distribution, also showed a significant correlation (see Figure 3) when a dummy variable (I [barley]) that assigns a value of 1 to the pI50 of barley was added. It can be seen that the level of PPO inhibitory activity between different plant species can be predicted with high accuracy using the following regression equation calculated in this way. pI50=0.768*LUMO distribution-2.238*I[barley]+5.465 (Correlation coefficient = 0.94)

[0035] The correlation analysis, regression analysis, etc. were performed using MS Office Excel, but can also be performed using free software or commercially available general-purpose multivariate analysis software.

[0036] As described above, it is clear that the use of LUMO distribution as a "molecular descriptor" enables the level of PPO inhibitory activity to be predicted with high accuracy. However, other characteristic values ​​related to PPO inhibitors, such as hydrophobicity (LogP) and steric parameters (MR, STERIMOL, etc.), can also be appropriately added as "molecular descriptors." That is, as with the "molecular descriptor" of LUMO distribution, incorporating these into "molecular descriptors" to create a multiple regression analysis formula can contribute to improving the accuracy of predicting PPO inhibitory activity. Such a range also falls within the technical scope of the present invention.

[0037] (2) Method for selecting a PPO inhibitor according to the present invention The method for selecting a PPO inhibitor of the present invention is characterized by predicting a PPO inhibitor based on the degree of PPO inhibitory activity predicted as described above. The rank of the LUMO distribution is not particularly limited, but 4 or 5 ranks are preferred.

[0038] The present invention will be described in more detail below with reference to examples, but it goes without saying that the present invention is not limited to these examples. [Example] Example 1

[0039] <LUMO calculation of oxidized FAD alone> The PPO crystal structure data, identified by the accession number 1SEZ, was obtained from the PDB. Only the conformation of oxidized FAD was extracted from this conformation data, and hydrogen atoms were added to this conformation using the open-source modeling software Molby. This was designated as oxidized FAD alone. The input file for this oxidized FAD alone in GAMESS was created using Molby. First, a structural optimization of all interatomic distances, bond angles, and dihedral angles was performed using the semi-empirical molecular orbital calculation method PM3 in GAMESS. After this, using the optimized structure, further structural optimization of all interatomic distances, bond angles, and dihedral angles was performed using the Hartree Fock (HF) method with a 3-21G basis set.

[0040] Using the optimized conformation, single-point calculations were performed using the 6-31G(2d,p) basis set calculation with the B3LYP functional of the DFT method to determine the LUMO.

[0041] The calculation results were obtained using the open-source modeling software Avogadro, with the isosuraface value set to 0.05, and the LUMO of oxidized FAD alone was calculated. Figure 4 shows the region within the molecular structure where the LUMO is distributed on the isoalloxazine ring. At the same time, the region where the LUMO exists indicates that no electrons are present, meaning that no electrons are present on the isoalloxazine ring and that an electrophilic reaction can occur. This is considered to be the LUMO of oxidized FAD alone, acting as an electron acceptor when PPO is normal and not inhibited by PPO inhibitors. Example 2

[0042] <LUMO calculation of inhibitor A complex> The PPO crystal structure data with accession number 1SEZ is obtained from the PDB in the same manner as in Example 1. From this conformational data, only the conformation of the bimolecular complex of oxidized FAD and inhibitor A is extracted, and this conformation is designated as the inhibitor A complex.

[0043] The LUMO of the inhibitor A complex was calculated in the same manner as in Example 1 and is shown in FIG. 5. In the inhibitor A complex, the LUMO existing on the isoalloxazine ring, which was present as the oxidized FAD monomer, almost disappeared. This means that the electrons localized in the HOMO of inhibitor A were mixed through the interaction with oxidized FAD, and the electrons were delocalized to the oxidized FAD molecule, resulting in the inhibition of the electrophilic reaction of oxidized FAD.

Example 3

[0044] <Calculation of the LUMO of the Compound B Complex> As a control compound with no herbicidal activity, for the compound B complex composed of a 2-molecule complex of compound B and oxidized FAD, using the molecular modeling software Winmostar64Bit (FREE) V11.6.1, structural changes such as substituents were made to inhibitor A of the inhibitor A complex in Example 2 to create the compound B complex.

[0045] The LUMO was calculated in the same manner as in Examples 1 and 2 and is shown in FIG. 6. The region where the LUMO is distributed on the isoalloxazine ring in the compound B complex was consistent with the LUMO of the oxidized FAD monomer in Example 1. This was considered that compound B did not change the LUMO on the isoalloxazine ring of oxidized FAD, and a normal electrophilic reaction similar to that of the oxidized FAD monomer in the normal state could occur, so it did not cause PPO inhibitory activity.

Example 4

[0046] <Calculation of the LUMO of the Pyraflufen Ethyl Complex> The LUMO of the 2-molecule complex of Pyraflufen Ethyl and oxidized FAD (Pyraflufen Ethyl complex) was calculated in the same manner as in Examples 1 to 3 and is shown in FIG. 7.

[0047] Compared with the normal LUMO distribution shown in Examples 1 and 3, the LUMO on the isoalloxazine ring of the Pyraflufen Ethyl complex disappeared by 100%, and the electrons localized on the HOMO of Pyraflufen Ethyl were mixed with the oxidized FAD due to the interaction with the oxidized FAD, resulting in the delocalization of electrons to the oxidized FAD molecules, which means that the electrophilic reaction of the oxidized FAD is inhibited.

Example 5

[0048] <Calculation method of LUMO distribution of Acifluorfen complex> PPO derived from myxobacteria of Acifluorfen was obtained from PDB accession number 2IVD. Only the conformation of the two-molecule complex of oxidized FAD and the PPO inhibitor Acifluorfen was extracted from this conformational data, and hydrogen was added using Molby. The conformation was used as the 2IVD complex.

[0049] The inhibitor A complex obtained in Example 2 and the 2IVD complex were superimposed by Winmostar on the isoalloxazine rings of oxidized FAD. The inhibitor A of the inhibitor A complex was replaced with Aciflyorfen of the 2IVD complex to create an Acifluorfen complex composed of two molecules of oxidized FAD of the inhibitor A complex and Acifluorfen of the 2IVD complex. The LUMO of the Acifluorfen complex was calculated in the same manner as in Examples 1 to 4 and is shown in Fig. 8. <00​​​​​​​​​​Using Winmostar, structural modifications such as substituents were made to the acifluorfen of the acifluorfen complex of Example 5 to prepare an oxyfluorofen complex.

[0052] The LUMO of the oxyfluorofen conjugate was calculated in the same manner as in Example 5 and is shown in Figure 9. As with the pyraflufen ethyl conjugate in Example 5, the LUMO on the isoalloxazine ring disappeared 100%, and as with inhibitor A, the electrons localized in the HOMO of oxyfluorofen became mixed through interaction with oxidized FAD, resulting in delocalization of the electrons in the oxidized FAD molecule, which means that the electrophilic reaction of oxidized FAD is inhibited. Example 7

[0053] <LUMO distribution calculation in correlation analysis of corn> In addition to the Pyraflufen Ethyl complex of Example 4 and the Oxyfluorofen complex of Example 5, the LUMOs of the complexes of oxidized FAD and chlorophthalimide compounds No. 1 to No. 40, which specify the substituents in the following general formula (I), were determined by the methods of Examples 1 to 6, respectively, and the LUMO distributions for each complex No. were ranked as follows and listed in Table 1 below. Compared to the LUMO distribution of oxidized FAD alone, 5 = 75% or more to 100% loss, 4 = 50% or more to less than 75% loss, 3 = 25% or more to less than 50% loss, 2 = 1% or more to less than 25% loss, 1 = no effect

[0054] [ka] [Table 1] Example 8

[0055] <Calculation of LUMO distribution in correlation analysis of barley> In addition to the Acifluorfen complex of Example 5 and the Oxyfluorofen complex of Example 6, the LUMO distributions of the complexes with oxidized FAD Nos. 44 to 57, which specify the substituents in the following general formula (II), were calculated in the same manner as in Examples 5 to 7, and the LUMO distributions for each complex No. are listed in Table 2.

[0056] [ka] [Table 2] [Industrial Applicability]

[0057] The present invention provides a technique for objectively and highly accurately predicting PPO inhibitory activity using LUMO distributions as "molecular descriptors." As a result, synthetic organic chemists can use this technique in herbicide research to predict the basic skeletons and substituent selection of compounds that inhibit PPO. [Brief explanation of the drawings] [Figure 1] FIG. 1 shows changes in LUMO distribution at pI50 of maize. [Figure 2] FIG. 1 shows changes in LUMO distribution at pI50 of barley. [Figure 3] FIG. 1 shows the correlation between the difference in variation in PPO inhibitory activity among different plant species and the level of PPO inhibitory activity. [Figure 4] FIG. 1 shows the LUMO of oxidized FAD alone. [Figure 5] FIG. 1 shows the LUMO of the inhibitor A complex. [Figure 6] FIG. 1 shows the LUMO of the compound B complex. [Figure 7] FIG. 1 shows the LUMO of the pyraflufen ethyl complex. [Figure 8] FIG. 1 shows the LUMO of Acifluorfen complexes. [Figure 9]FIG. 1 shows the LUMO of oxyfluorophenone conjugates.

Claims

1. A method for predicting a PPO inhibitor, characterized in that the LUMO distribution is used as a "molecular descriptor" to predict the degree of PPO inhibitory activity.

2. The method for predicting a PPO inhibitor according to claim 1, characterized in that the PPO inhibitory activity is predicted based on the correlation between LUMO distribution and PPO inhibitory activity for each compound.

3. 3. The method for predicting a PPO inhibitor according to claim 1 or 2, characterized in that the prediction of PPO inhibitor activity based on the correlation is calculated in corn and barley using the following formula: <Corn> PPO inhibitory activity = 0.662 * LUMO distribution index + 5.795 <Barley> PPO inhibitory activity = 0.987 * LUMO distribution index + 2.363

4. A method for predicting a PPO inhibitor as described in claim 1, characterized in that the level of PPO inhibitory activity is predicted based on the correlation between the difference in variation in PPO inhibitory activity between different plant species and the level of PPO inhibitory activity.

5. A method for selecting a PPO inhibitor, characterized by using the PPO inhibitory activity predicted by any one of claims 1 to 4 as an index.

6. A PPO inhibitor predicted and selected by the method according to one of claims 1 to 5.

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