Method for predicting protoporphyrinogen oxidase (PPO) inhibitor

Abstract

Provided are: a technique for objectively and highly accurately predicting the amount of a PPO inhibitor by using a LUMO distribution as a molecular descriptor; and a technique for selecting a PPO inhibitor on the basis of the predicted amount of the PPO inhibitor. This method for selecting a PPO inhibitor comprises: predicting PPO inhibitory activity on the basis of the correlation between the LUMO distribution and the PPO inhibitory activity of compounds; predicting the amount of PPO inhibitory activity on the basis of the correlation between the amount of PPO inhibitory activity and the variation difference in PPO inhibitory activity between different plant species; and using the predicted PPO inhibitory activity as an index.

Description

Method for predicting protoporphyrinogen oxidase (PPO) inhibitors

[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) distribution as a "molecular descriptor," and a method for selecting PPO inhibitors using the prediction method.

[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) using in silico methods and their structural information, 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 "if compounds have similar structures, their biological activity should also be similar, and therefore biological activity can be predicted by displaying the structural 'closeness' of compounds." The structural information of a compound uses "molecular descriptors," which are quantified to facilitate computer-based handling of the compound's structural features and physicochemical properties (e.g., hydrophobicity and steric parameters). This method originates from the Hansh-Fujita method (Non-Patent Document 1), which 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, which require light for their herbicidal activity and are also called "photobleaching herbicides," have been studied for over half a century (Non-Patent Document 2), and 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, and that 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). Protoporphyrin IX generates reactive oxygen species in the presence of light and oxygen, and light causes peroxidative damage to biomembranes, resulting in the rapid death of plant cells and the withering of the plant (Non-Patent Document 4).

[0007] Whether or not 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 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), a 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), which are represented by the following structural formulas (Non-Patent Document 5).

[0009]

[0010]

[0011]

[0012] Other examples of pI50 using maize 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]

[0016] Crystal structure data of PPO derived from tobacco plants (Nicotiana tabacum) has been reported to have a three-dimensional structure containing a phenylpyrazole-based 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 entry number 1SEZ.

[0017]

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

[0019]

[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]

[0022] However, there have been no examples 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, mixing with the LUMO of the oxidized FAD molecule and delocalizing the electrons. We hypothesized that if we could quantify and display this change in the LUMO distribution of oxidized FAD as a "molecular descriptor," we could establish a correlation with PPO inhibitor activity.

[0023] It was not known at all that the LUMO distribution of the 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 a PPO inhibitor could be provided based on the level of PPO inhibition predicted in this way.

[0024] C. Hansch and T. Fujita, J. Am. Chem. Soc., (1964) 86, 1616-1626S. Matsunaka, J. Agric. Food Chem, (1969) 17(2), 171-175M. Matringe et al., The Biochemical Journal, (1989) 60, 231-235H. J. Lee et al. al., Plant Physiol., (1993) 102, 881-889S. Ishida et al., J. Pesticide Sci., (2000), 25, 18-23T. Fujita and A. Nakayama, Peroxidizing Herbicide, Eds. P. Boeger and K. Wakabayashi, Springer, Berlin Heidelberg, (1999), 91-139U. B. Nandihalli et al., Pesticide Biochemistry and Physiology, (1992), 43, 193-211M. Nakagawa et al., J. Pesticide. Sci., (1988) 13, 363-374M. Koch et al., The EMBO Journal, (2004), 23, 1720-1728H. R. Corradi et al., J BiolChem., (2006), 281(50), 38625-38633X. Qin et al., FASEB J., (2011), 25, 653-664 Kenichi Fukui "Chemical Reactions and Orbits of Electrons" Maruzen 1976

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

[0026] In light of these circumstances, the present inventors have conducted extensive research and development in search of a technique for objectively, accurately, and precisely predicting the level of PPO inhibitory activity. As a result, they have discovered that the level of PPO inhibitory activity can be predicted objectively and accurately based on the correlation between the LUMO distribution and the level of PPO inhibitory activity for each compound, and have completed the invention. Specifically, the present invention relates to the following techniques: (1) A method for predicting a PPO inhibitor, which uses LUMO distribution as a "molecular descriptor" to predict the level of PPO inhibitory activity. (2) The method for predicting a PPO inhibitor according to claim 1, which predicts PPO inhibitory activity based on the correlation between the LUMO distribution and PPO inhibitory activity for each compound. (3) The method for predicting a PPO inhibitor according to claim 1 or 2, which predicts PPO inhibitory activity based on the correlation 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) 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 between different plant species and the level of PPO inhibitory activity. (5) A method for selecting a PPO inhibitor, wherein the PPO inhibitory activity predicted by (1) to (4) is used as an index. (6) A PPO inhibitor predicted and selected by the method according to one of (1) to (5).

[0027] According to the present invention, a technique for predicting the level of a PPO inhibitor objectively and with high accuracy can be provided.

[0028] 1 is a diagram showing changes in LUMO distribution at the pI50 of corn. 2 is a diagram showing changes in LUMO distribution at the pI50 of barley. 3 is a diagram showing the correlation between the difference in variation in PPO inhibitor activity between different plant species and the degree of PPO inhibitor activity. 4 is a diagram showing the LUMO of oxidized FAD alone. 5 is a diagram showing the LUMO of inhibitor A complex. 6 is a diagram showing the LUMO of compound B complex. 7 is a diagram showing the LUMO of pyraflufen ethyl complex. 8 is a diagram showing the LUMO of acifluorfen complex. 9 is a diagram showing the LUMO of oxyfluorfen complex.

[0029] (1) Method for Predicting PPO Inhibitors of the Present Invention The method for predicting PPO inhibitors of the present invention is characterized by using LUMO distribution as a "molecular descriptor" to predict the level of PPO inhibitory activity. To make this prediction, the relationship between the level of PPO inhibitory activity and 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.

[0030] The general inhibitory activity of PPO inhibitors is expressed as 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 for chlorophthalim from Non-Patent Documents 5 and 6, and for barley for diphenyl ether compounds from Non-Patent Document 7, and were all used for analysis. The pI50 for corn for oxyfluorofen was obtained from Non-Patent Document 5, and the pI50 for barley was obtained from Non-Patent Document 7, and were all used for analysis.

[0031] The LUMO of the conformation of a bimolecular complex of oxidized FAD and the inhibitor to be predicted is calculated using the ab initio molecular orbital method / density functional theory calculation program GAMESS, and it is preferable that the calculation be performed using the 6-31G (2d, p) basis set with the B3LYP functional of the DFT (Density Functional Theory) method.

[0032] The LUMO distribution can be displayed as a "molecular descriptor" according to the following qualitative standard method, and is ranked according to the following criteria, comparing it with 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.

[0033] 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 chlorophthalims extracted from cyclic imides (Non-Patent Document 6). The results showed a significant correlation (correlation coefficient = 0.90) (see Figure 1). It can be seen that the corn PPO inhibitory activity can be predicted with high accuracy from the LUMO distribution by using the following regression equation calculated in this way: <Corn> pI50 = 0.662 * LUMO distribution + 5.795 (correlation coefficient = 0.90)

[0034] Furthermore, correlation analysis and regression analysis of barley PPO inhibitory activity and LUMO distribution were performed by extracting 16 diphenyl ether compounds, including oxyfluorofen, 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 can be seen that the PPO inhibitory activity can be predicted with high accuracy from the LUMO distribution by using the following regression equation calculated in this way: <Barley> pI50 = 0.987 * LUMO distribution + 2.363 (correlation coefficient = 0.96)

[0035] When the regression equation for the difference in pI50 variation between the different plant species, corn and barley, and the LUMO distribution was analyzed by adding a dummy variable (I [barley]) that assigns 1 to the pI50 of barley, a significant correlation was also shown (see Figure 3). 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)

[0036] 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.

[0037] As described above, it can be seen that the use of LUMO distribution as a "molecular descriptor" makes it possible to predict the level of PPO inhibitory activity with high accuracy. Furthermore, other characteristic values ​​related to PPO inhibitors, such as hydrophobicity (LogP) and steric parameters (MR, STERIMOL, etc.), can also be added as appropriate 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.

[0038] (2) Method for selecting a PPO inhibitor of the present invention The method for selecting a PPO inhibitor of the present invention is characterized in that a PPO inhibitor is predicted 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 is preferred.

[0039] 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.

[0040] Example 1 LUMO Calculation of Oxidized FAD Only PPO crystal structure data with entry number 1SEZ was obtained from the PDB, and only the conformation of oxidized FAD was extracted from this conformation data. Hydrogen was added to this conformation using the open-source modeling software Molby. This was designated as oxidized FAD only. A GAMESS input file for this oxidized FAD only was created using Molby. First, structural optimization of all interatomic distances, bond angles, and dihedral angles was performed using the semi-empirical molecular orbital calculation method PM3 in GAMESS. Then, using this optimized structure, structural optimization of all interatomic distances, bond angles, and dihedral angles was performed using the Hartree Fock (HF) method with 3-21G basis functions.

[0041] Using the optimized conformation, single-point calculations were carried out by 6-31G (2d, p) basis set calculations using the B3LYP functional of the DFT method to determine the LUMO.

[0042] The calculation results were obtained using the open-source modeling software Avogadro, with the isosurface value set to 0.05, and the LUMO of oxidized FAD alone was calculated and shown in Figure 4. This shows the region within the molecular structure where the LUMO present on the isoalloxazine ring is distributed, and at the same time, it indicates that no electrons are present in the region where the LUMO exists, meaning that there are no electrons on the isoalloxazine ring and an electrophilic reaction can occur. This is considered to be the LUMO of oxidized FAD alone as an electron acceptor when PPO is normal and not inhibited by PPO inhibitors.

[0043] <Example 2> <LUMO calculation of inhibitor A complex> PPO crystal structure data with entry 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.

[0044] The LUMO of the inhibitor A complex was calculated in the same manner as in Example 1 and is shown in Figure 5. In the inhibitor A complex, the LUMO on the isoalloxazine ring that was present in oxidized FAD alone almost disappeared. This means that the electrons that were localized in the HOMO of inhibitor A interacted with oxidized FAD and became mixed, resulting in delocalization of the electrons in the oxidized FAD molecule, which may inhibit the electrophilic reaction of oxidized FAD.

[0045] Example 3 LUMO Calculation of Compound B Complex A compound B complex consisting of a bimolecular complex of compound B and oxidized FAD was used as a control compound having absolutely no herbicidal activity. Using molecular modeling software Winmostar 64Bit (FREE) V11.6.1, structural modifications such as substituents were made to inhibitor A of the inhibitor A complex of Example 2 to create a compound B complex.

[0046] The LUMO was calculated in the same manner as in Examples 1 and 2 and is shown in Figure 6. The region in which the LUMO on the isoalloxazine ring in the compound B complex was distributed matched the LUMO of the oxidized FAD alone in Example 1. This was thought to be because compound B did not change the LUMO on the isoalloxazine ring of oxidized FAD and was able to undergo a normal electrophilic reaction similar to that of normal oxidized FAD alone, and therefore did not induce PPO inhibitory activity.

[0047] Example 4 LUMO Calculation of Pyrflufen Ethyl Complex The LUMO of the bimolecular 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.

[0048] Compared with the normal LUMO distributions shown in Examples 1 and 3, the LUMO on the isoalloxazine ring of the Pyrflufen Ethyl complex is 100% lost, and the electrons that were localized in the HOMO of Pyrflufen Ethyl are mixed together 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.

[0049] Example 5 Method for Calculating LUMO Distribution of Acifluorfen Complex Acifluorfen-derived PPO derived from myxobacteria was obtained from PDB reference number 2IVD. From this conformational data, only the conformation of the bimolecular complex of oxidized FAD and the PPO inhibitor acifluorfen was extracted, and hydrogen atoms were added using Molby. This conformation was designated the 2IVD complex.

[0050] The inhibitor A complex and the 2IVD complex obtained in Example 2 were superimposed with the isoalloxazine rings of oxidized FAD using Winmostar, and the inhibitor A in the inhibitor A complex was replaced with aciflyorfen in the 2IVD complex to prepare an aciflyorfen complex consisting of two molecules of oxidized FAD in the inhibitor A complex and aciflyorfen in the 2IVD complex. The LUMO of the aciflyorfen complex was calculated in the same manner as in Examples 1 to 4, and the results shown in Figure 8 were obtained.

[0051] As with the inhibitor A complex in Example 2, in the acifluorfen complex, the LUMO present on the isoalloxazine ring that was present in oxidized FAD alone almost completely disappears, and the electrons that were localized on the HOMO of acifluorfen become 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 by the electronic reaction with acifluorfen.

[0052] Example 6 LUMO Calculation of Oxyfluorofen Complex An oxyfluorofen complex was prepared by modifying the structure of the acifluorfen in the acifluorfen complex of Example 5, such as by changing the substituents, using Winmostar.

[0053] The LUMO of the oxyfluorofen complex was calculated in the same manner as in Example 5 and is shown in Figure 9. As with the pyraflufen ethyl complex 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.

[0054] <Example 7> <Calculation of LUMO distribution in correlation analysis of corn> In addition to the Pyrflufen Ethyl complex of Example 4 and the Oxyfluorofen complex of Example 5, the LUMOs of complexes of oxidized FAD with chlorophthalim and cyclic imide 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, and the LUMO distribution for each complex No. was 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, and 1 = no effect

[0055]

[0056] <Example 8> <LUMO distribution calculation in correlation analysis of barley> In addition to the Acifluorfen complex of Example 5 and the Oxyfluorfen complex of Example 6, the LUMO distributions were calculated in the same manner as in Examples 5 to 7 for complexes with oxidized FAD Nos. 44 to 57, which specify the substituent in the following general formula (II), and the LUMO distribution for each complex No. is shown in Table 2.

[0057]

[0058] 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 skeleton of compounds that inhibit PPO and the selection of their substituents.

Claims

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

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

3. The method for predicting a PPO inhibitor according to claim 1 or 2, wherein the PPO inhibitory activity is predicted based on the correlation 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 degree of PPO inhibitory activity is predicted based on the correlation between the variation difference in PPO inhibitory activity between different plant species and the degree of PPO inhibitory activity.

5. A method for selecting a PPO inhibitor, characterized in that the PPO inhibitory activity predicted by claims 1 to 4 is used 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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