CN113140266A - Screening method of xanthine oxidase inhibitor for reducing uric acid - Google Patents
Screening method of xanthine oxidase inhibitor for reducing uric acid Download PDFInfo
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- 239000003064 xanthine oxidase inhibitor Substances 0.000 title claims abstract description 32
- LEHOTFFKMJEONL-UHFFFAOYSA-N Uric Acid Chemical compound N1C(=O)NC(=O)C2=C1NC(=O)N2 LEHOTFFKMJEONL-UHFFFAOYSA-N 0.000 title claims abstract description 21
- TVWHNULVHGKJHS-UHFFFAOYSA-N Uric acid Natural products N1C(=O)NC(=O)C2NC(=O)NC21 TVWHNULVHGKJHS-UHFFFAOYSA-N 0.000 title claims abstract description 21
- 229940116269 uric acid Drugs 0.000 title claims abstract description 21
- 229940123769 Xanthine oxidase inhibitor Drugs 0.000 title claims abstract description 20
- 238000012216 screening Methods 0.000 title claims description 12
- 238000000034 method Methods 0.000 title claims description 8
- 108010093894 Xanthine oxidase Proteins 0.000 claims description 29
- 102100033220 Xanthine oxidase Human genes 0.000 claims description 29
- 150000001875 compounds Chemical class 0.000 claims description 12
- 239000013078 crystal Substances 0.000 claims description 12
- 230000002401 inhibitory effect Effects 0.000 claims description 12
- 239000013641 positive control Substances 0.000 claims description 9
- LRFVTYWOQMYALW-UHFFFAOYSA-N 9H-xanthine Chemical compound O=C1NC(=O)NC2=C1NC=N2 LRFVTYWOQMYALW-UHFFFAOYSA-N 0.000 claims description 8
- 229960003459 allopurinol Drugs 0.000 claims description 7
- OFCNXPDARWKPPY-UHFFFAOYSA-N allopurinol Chemical compound OC1=NC=NC2=C1C=NN2 OFCNXPDARWKPPY-UHFFFAOYSA-N 0.000 claims description 7
- YQUVCSBJEUQKSH-UHFFFAOYSA-N protochatechuic acid Natural products OC(=O)C1=CC=C(O)C(O)=C1 YQUVCSBJEUQKSH-UHFFFAOYSA-N 0.000 claims description 7
- WKOLLVMJNQIZCI-UHFFFAOYSA-N vanillic acid Chemical group COC1=CC(C(O)=O)=CC=C1O WKOLLVMJNQIZCI-UHFFFAOYSA-N 0.000 claims description 7
- TUUBOHWZSQXCSW-UHFFFAOYSA-N vanillic acid Natural products COC1=CC(O)=CC(C(O)=O)=C1 TUUBOHWZSQXCSW-UHFFFAOYSA-N 0.000 claims description 7
- 238000002835 absorbance Methods 0.000 claims description 6
- 102000004169 proteins and genes Human genes 0.000 claims description 6
- 108090000623 proteins and genes Proteins 0.000 claims description 6
- 238000007637 random forest analysis Methods 0.000 claims description 6
- 238000002798 spectrophotometry method Methods 0.000 claims description 6
- 238000004617 QSAR study Methods 0.000 claims description 5
- 238000012795 verification Methods 0.000 claims description 5
- 229940075420 xanthine Drugs 0.000 claims description 4
- 238000010801 machine learning Methods 0.000 claims description 3
- 239000013642 negative control Substances 0.000 claims description 3
- 239000000523 sample Substances 0.000 claims description 3
- 239000012488 sample solution Substances 0.000 claims description 3
- 239000000243 solution Substances 0.000 claims description 3
- 239000011550 stock solution Substances 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
- 230000001629 suppression Effects 0.000 claims description 3
- 239000008363 phosphate buffer Substances 0.000 claims 1
- 239000000126 substance Substances 0.000 claims 1
- 238000000926 separation method Methods 0.000 abstract description 2
- 201000005569 Gout Diseases 0.000 description 8
- 230000000694 effects Effects 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000001965 increasing effect Effects 0.000 description 3
- 238000003032 molecular docking Methods 0.000 description 3
- KDCGOANMDULRCW-UHFFFAOYSA-N 7H-purine Chemical compound N1=CNC2=NC=NC2=C1 KDCGOANMDULRCW-UHFFFAOYSA-N 0.000 description 2
- 239000003814 drug Substances 0.000 description 2
- 229940079593 drug Drugs 0.000 description 2
- 230000029142 excretion Effects 0.000 description 2
- 238000011534 incubation Methods 0.000 description 2
- 239000008055 phosphate buffer solution Substances 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 230000004144 purine metabolism Effects 0.000 description 2
- 206010067484 Adverse reaction Diseases 0.000 description 1
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 208000010201 Exanthema Diseases 0.000 description 1
- 238000012404 In vitro experiment Methods 0.000 description 1
- 208000001145 Metabolic Syndrome Diseases 0.000 description 1
- 206010037660 Pyrexia Diseases 0.000 description 1
- 206010042033 Stevens-Johnson syndrome Diseases 0.000 description 1
- 231100000168 Stevens-Johnson syndrome Toxicity 0.000 description 1
- 201000000690 abdominal obesity-metabolic syndrome Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000006838 adverse reaction Effects 0.000 description 1
- 229940045686 antimetabolites antineoplastic purine analogs Drugs 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 201000005884 exanthem Diseases 0.000 description 1
- 229960005101 febuxostat Drugs 0.000 description 1
- BQSJTQLCZDPROO-UHFFFAOYSA-N febuxostat Chemical compound C1=C(C#N)C(OCC(C)C)=CC=C1C1=NC(C)=C(C(O)=O)S1 BQSJTQLCZDPROO-UHFFFAOYSA-N 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 230000037406 food intake Effects 0.000 description 1
- 235000012631 food intake Nutrition 0.000 description 1
- 238000000338 in vitro Methods 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 208000027866 inflammatory disease Diseases 0.000 description 1
- 208000017169 kidney disease Diseases 0.000 description 1
- 230000003907 kidney function Effects 0.000 description 1
- 229930014626 natural product Natural products 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 150000003212 purines Chemical class 0.000 description 1
- 206010037844 rash Diseases 0.000 description 1
- 230000002829 reductive effect Effects 0.000 description 1
- 108091008146 restriction endonucleases Proteins 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
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Abstract
The invention belongs to the technical field of functional component separation, and particularly relates to a xanthine oxidase inhibitor for reducing uric acid.
Description
Technical Field
The invention belongs to the technical field of functional component separation, and particularly relates to a screening method of a xanthine oxidase inhibitor for reducing uric acid.
Background
Gout is an inflammatory disease caused by increased purine metabolism or abnormal uric acid excretion, and causes kidney diseases, cardiovascular diseases, metabolic syndrome, and the like. In recent decades, the incidence of gout has been increasing and is in a trend of youthfulness, both increased uric acid synthesis and decreased uric acid excretion can cause the increase of uric acid level in blood, thereby inducing gout, the uric acid in human bodies is derived from food intake at least in part, about 80% of uric acid is a product of purine metabolism catalyzed by xanthine oxidase in human bodies, the xanthine oxidase is a key restriction enzyme for producing uric acid in human bodies, and is also a drug action target point for treating gout, the activity of the xanthine oxidase is inhibited, the conversion of xanthine to uric acid is reduced, and the method becomes a main way for clinically treating gout.
Xanthine oxidase inhibitors have become the main drugs for treating gout, which are mainly classified into purine and non-purine analogues, however, some xanthine oxidase inhibitors such as allopurinol and febuxostat are accompanied by adverse reactions in gout treatment, including fever, rash, renal function deterioration and Stevens-Johnson syndrome, and some natural compounds from plant sources can effectively inhibit xanthine oxidase and can be used for gout treatment, so that the search for the xanthine oxidase inhibitors with high activity and small toxic and side effects from natural plants is particularly urgent and important.
The invention screens potential xanthine oxidase inhibitor candidates by combining a quantitative structure-activity relationship model and molecular docking through establishing a xanthine oxidase inhibitor molecular database, and obtains the xanthine oxidase inhibitor for reducing uric acid through in vitro experiment verification.
Disclosure of Invention
The invention aims to establish a xanthine oxidase inhibitor molecular database, combine a quantitative structure-activity relationship model with molecular docking to screen potential xanthine oxidase inhibitor candidates, and obtain the xanthine oxidase inhibitor for reducing uric acid through in vitro experimental verification. The product and the preparation method of the invention are as follows:
a screening method of a xanthine oxidase inhibitor for reducing uric acid is characterized by comprising the following steps of: (1) establishing a database of xanthine oxidase inhibitors of plant origin, the database comprising 150 compounds that inhibit xanthine oxidase; (2) calculating smile of the molecule in the step (1), generating a molecular descriptor for capturing molecular structure and property, and comparing; (3) the four machine learning methods comprise random forests, support vector machines, k nearest neighbor and linear discriminant analysis, a quantitative structure-activity relationship model capable of screening xanthine oxidase inhibitors is established according to the descriptors generated in the step (2), and an optimal model is selected by comparing the accuracy of the model; (4) taking allopurinol as a positive control, obtaining a crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify a model prediction result, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry; (5) the potential xanthine oxidase inhibitor is discovered through model screening and experimental verification.
The MOE descriptor has the best modeling effect.
The optimal model is a random forest model with the accuracy of 0.9605.
The experimental conditions are that 50 mu L of sample solution, 50 mu L of xanthine oxidase solution (0.02U/mL) and phosphate buffer solution (0.075mol/L and pH 7.5) are sequentially added on a 96-well plate, incubation is carried out for 5min in a 25 ℃ microplate reader, then 50 mu L of xanthine stock solution (0.001mol/L) is added, reaction is carried out for 15min at 25 ℃, zero adjustment is carried out by a blank group at 295nm, and the absorbance A of the sample is measured0(ii) a Then, the negative control group is used for zero setting, and the absorbance A of the positive control group is measured1The XO suppression ratio (IR) is calculated by the following formula: IR (%) - (a)1-A0)/A1]×100％。
The characteristics of the contents of the final product of the invention are as follows: the candidate with xanthine oxidase inhibitory activity is vanillic acid, IC50It was 0.593. mu.g/mL.
Drawings
FIG. 1 is a process flow diagram of the present invention;
FIG. 2 is an importance diagram of MOE descriptors;
FIG. 3 is a graph of accuracy of the RF model;
FIG. 4 is a molecular docking diagram of vanillic acid and xanthine oxidase.
Detailed Description
Specific embodiments are further described below in conjunction with the appended drawings.
A screening method of a xanthine oxidase inhibitor for reducing uric acid is characterized by comprising the following steps of: (1) establishing a database of xanthine oxidase inhibitors of plant origin, the database comprising 150 compounds that inhibit xanthine oxidase; (2) calculating smile of the molecule in the step (1), generating a molecular descriptor for capturing molecular structure and property, and comparing; (3) the four machine learning methods comprise random forests, support vector machines, k nearest neighbor and linear discriminant analysis, a quantitative structure-activity relationship model capable of screening xanthine oxidase inhibitors is established according to the descriptors generated in the step (2), and an optimal model is selected by comparing the accuracy of the model; (4) taking allopurinol as a positive control, obtaining a crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify a model prediction result, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry; (5) the potential xanthine oxidase inhibitor is discovered through model screening and experimental verification.
The MOE descriptor has the best modeling effect.
The optimal model is a random forest model with the accuracy of 0.9605.
The experimental conditions are that 50 mu L of sample solution, 50 mu L of xanthine oxidase solution (0.02U/mL) and phosphate buffer solution (0.075mol/L and pH 7.5) are sequentially added on a 96-well plate, incubation is carried out for 5min in a 25 ℃ microplate reader, then 50 mu L of xanthine stock solution (0.001mol/L) is added, reaction is carried out for 15min at 25 ℃, zero adjustment is carried out by a blank group at 295nm, and the absorbance A of the sample is measured0(ii) a Then, the negative control group is used for zero setting, and the absorbance A of the positive control group is measured1The XO suppression ratio (IR) is calculated by the following formula: IR (%) - (a)1-A0)/A1]×100％。
The candidate with xanthine oxidase inhibitory activity is vanillic acid, IC50It was 0.593. mu.g/mL.
Example 1
(1) A database of plant-derived xanthine oxidase inhibitors is established.
(2) Calculating the MOE descriptor of the compound collected in step (1).
(3) And (3) establishing comparison accuracy of the RF model, the SVM model, the kNN model and the LDA model according to the descriptor generated in the step (2).
(4) Taking allopurinol as a positive control, obtaining the crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify the result of model prediction, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry.
(5) A candidate having xanthine oxidase inhibitory activity was found to be vanillic acid, IC50It was 0.593. mu.g/mL.
Example 2
(1) A database of plant-derived xanthine oxidase inhibitors is established.
(2) Calculating the Mordred descriptor of the compound collected in step (1).
(3) And (3) establishing comparison accuracy of the RF model, the SVM model, the kNN model and the LDA model according to the descriptor generated in the step (2).
(4) Taking allopurinol as a positive control, obtaining the crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify the result of model prediction, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry.
(5) A candidate having xanthine oxidase inhibitory activity was found to be vanillic acid, IC50It was 0.593. mu.g/mL.
Example 3
(1) A database of plant-derived xanthine oxidase inhibitors is established.
(2) Calculating the ChemoPy descriptor of the compound collected in step (1).
(3) And (3) establishing comparison accuracy of the RF model, the SVM model, the kNN model and the LDA model according to the descriptor generated in the step (2).
(4) Taking allopurinol as a positive control, obtaining the crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify the result of model prediction, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry.
(5) A candidate having xanthine oxidase inhibitory activity was found to be vanillic acid, IC50It was 0.593. mu.g/mL.
Claims (5)
1. A screening method of a xanthine oxidase inhibitor for reducing uric acid is characterized by comprising the following steps of: (1) establishing a database of xanthine oxidase inhibitors of plant origin, the database comprising 150 compounds that inhibit xanthine oxidase; (2) calculating smile of the molecule in the step (1), generating a molecular descriptor for capturing molecular structure and property, and comparing; (3) the four machine learning methods comprise random forests, support vector machines, k nearest neighbor and linear discriminant analysis, a quantitative structure-activity relationship model capable of screening xanthine oxidase inhibitors is established according to the descriptors generated in the step (2), and an optimal model is selected by comparing the accuracy of the model; (4) taking allopurinol as a positive control, obtaining a crystal structure of xanthine oxidase, taking the crystal structure as a protein target, performing molecular pairing to verify a model prediction result, and further determining the xanthine oxidase inhibitory activity of the compound by using an ultraviolet spectrophotometry; (5) the potential xanthine oxidase inhibitor is discovered through model screening and experimental verification.
2. The xanthine oxidase inhibitor for reducing uric acid according to claim 1, wherein the MOE descriptor is modeled best.
3. The xanthine oxidase inhibitor for reducing uric acid according to claim 1, wherein the optimal model is a random forest model with an accuracy of 0.9605.
4. The xanthine oxidase inhibitor for reducing uric acid according to claim 1, wherein the experimental conditions are that 50 μ L of sample solution, 50 μ L of xanthine oxidase solution (0.02U/mL), and phosphate buffer (0.075mol/L, pH 7.5) are sequentially added to a 96-well plate, incubated in a 25 ℃ microplate reader for 5min, and thenAdding 50 μ L xanthine stock solution (0.001mol/L) to react at 25 deg.C for 15min, zeroing with blank set at 295nm, and measuring absorbance A of sample0(ii) a Then, the negative control group is used for zero setting, and the absorbance A of the positive control group is measured1The XO suppression ratio (IR) is calculated by the following formula: IR (%) - (a)1-A0)/A1]×100％。
5. The xanthine oxidase inhibitor for reducing uric acid according to claim 1, wherein the candidate substance having xanthine oxidase inhibitory activity is vanillic acid, IC50It was 0.593. mu.g/mL.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115232855A (en) * | 2022-07-08 | 2022-10-25 | 华南农业大学 | Method for screening drugs influencing xanthine oxidase activity by targeting intestinal flora |
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| CN104598772A (en) * | 2014-12-25 | 2015-05-06 | 南昌大学 | Construction method for gout drug effect enzyme target model |
| CN109524064A (en) * | 2018-11-12 | 2019-03-26 | 云南省烟草农业科学研究院 | A kind of virtual screening method of polyphenol oxidase enzyme inhibitor |
| CN111627493A (en) * | 2020-05-29 | 2020-09-04 | 北京晶派科技有限公司 | Selective prediction method and computing device for kinase inhibitor |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102222178A (en) * | 2011-03-31 | 2011-10-19 | 清华大学深圳研究生院 | Method for screening and/or designing medicines aiming at multiple targets |
| CN104598772A (en) * | 2014-12-25 | 2015-05-06 | 南昌大学 | Construction method for gout drug effect enzyme target model |
| CN109524064A (en) * | 2018-11-12 | 2019-03-26 | 云南省烟草农业科学研究院 | A kind of virtual screening method of polyphenol oxidase enzyme inhibitor |
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| CN115232855A (en) * | 2022-07-08 | 2022-10-25 | 华南农业大学 | Method for screening drugs influencing xanthine oxidase activity by targeting intestinal flora |
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