Method and system for evaluating bactericidal performance of a bactericide

Abstract

The present application relates to a kind of bactericide bactericidal performance evaluation method and evaluation system, belong to the field of oil engineering application technology.The bactericide bactericidal performance evaluation method of the present application, the basic skeleton of bacterial membrane is constructed by coarse-grained molecular dynamics method in nanometer space scale with phospholipid bilayer, and the choline group and phosphate group of head group make the surface of bacteria positive and negative, bactericide is adsorbed to the surface of bacteria by interacting with the charged group on the surface of bacteria, by comparing the binding energy of bactericide and bacteria, whether bactericide can be stably adsorbed on the surface of bacteria and hinder the normal metabolism of bacteria, and finally kill bacteria can be evaluated.The bactericide bactericidal performance evaluation method of the present application does not need to pass through traditional experiment, and is evaluated using computer "virtual experiment", is not limited by experimental condition, is high in efficiency, is strong in repeatability, result is reliable, is conducive to the rapid design and research and development of bactericide for oil field chemical.

Description

Technical Field

[0001] This invention relates to a method and system for evaluating the bactericidal performance of a bactericide, belonging to the field of petroleum engineering application technology. Background Technology

[0002] Excessive bacterial levels pose significant risks to oilfield development: they corrode equipment and pipelines; deteriorate reinjection water quality, clogging formations; and cause deterioration of various substances, such as guar gum, sesquiterpene, and phytosols. As a water-based fracturing fluid additive, bactericides have a substantial impact on fracturing fluid performance. Suitable bactericides can halt the growth of anaerobic bacteria in the formation and eliminate surface degradation of polymers in storage tanks. Research indicates that sulfate-reducing bacteria, iron bacteria, and acid-producing bacteria have the greatest impact on oil and gas resource development; therefore, adding appropriate bactericides to reinjection water can effectively reduce economic losses. Chemical bactericides used in oilfields include oxidizing, adsorbing, and penetrating types. Traditional bactericide screening processes require first analyzing bacterial species, then culturing bacteria, and finally screening the bactericide. This process is cumbersome, time-consuming, requires stringent culture conditions, and is significantly influenced by human factors.

[0003] In recent years, research has begun on methods for evaluating the bactericidal performance of chemical bactericides used in oilfields. For example, Chinese patent document CN104198543A discloses a method for rapidly evaluating the biofilm stripping ability of bactericides. This method includes the following steps: preparing the bactericide to be tested; preparing multiple test pieces with biofilms; preparing multiple sets of three-electrode batteries for electrochemical impedance spectroscopy (EIS), with each set using the biofilm-bearing test piece as the working electrode, a saturated calomel electrode as the reference electrode, and a platinum electrode as the auxiliary electrode; placing one set of the above-mentioned three-electrode batteries in each bactericide solution and obtaining the corresponding electrochemical impedance values ​​for each bactericide solution; obtaining the impedance or capacitive reactance value of each bactericide solution from each set of EIS values ​​to evaluate the effect of the bactericide solution concentration on biofilm stripping ability. This method simulates the field and assists in determining the bacterial content within the biofilm, thereby obtaining the stripping effect of different bactericides and the same bactericide at different concentrations. This provides a basis for determining the dosage and application cycle of bactericides in the field and improving the application effect of bactericides in the field. Although this method significantly improves the evaluation efficiency of bactericides in oilfield reinjection water, it still requires a cumbersome operation process, and the efficiency needs to be further improved. Summary of the Invention

[0004] The purpose of this invention is to provide a method for evaluating the bactericidal performance of a bactericide, which can solve the problem of cumbersome operation in the current evaluation of the bactericidal performance of bactericides.

[0005] Another objective of this invention is to provide an evaluation system for the bactericidal performance of a bactericide, which can solve the problems of low efficiency and poor repeatability in the current evaluation of the bactericidal performance of bactericides.

[0006] To achieve the above objectives, the technical solution adopted in the method for evaluating the bactericidal performance of the bactericide of the present invention is as follows:

[0007] A method for evaluating the bactericidal performance of a bactericide includes the following steps:

[0008] (1) Establish coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules, and set the force field parameters of each coarse-grained model; construct a spherical phospholipid bilayer model based on the coarse-grained model of phospholipid molecules to simulate bacterial biofilms.

[0009] (2) Construct a water-bacteria-bactericide mixed model box that includes a water molecule coarse-grained model, a bactericide coarse-grained model, and a globular phospholipid bilayer model;

[0010] (3) Optimize the structure of the hybrid model box to obtain the minimum energy structure of the hybrid model box. Then, perform dynamic calculations on the minimum energy structure of the hybrid model box under isothermal and isobaric ensembles and canonical ensembles respectively to obtain the trajectory file of the water-bacteria-bactericide hybrid model box.

[0011] (4) Analyze the trajectory file to obtain the radial distribution function of the bacterial centroid and the bactericide, and the radial distribution function of the bacterial centroid and the water molecule; compare the peak position of the radial distribution function curve of the bacterial centroid and the bactericide with the peak position of the radial distribution function curve of the bacterial centroid and the water molecule to obtain the deviation value, and then compare the deviation value with the preset threshold. If the deviation value is not less than the preset threshold, the simulated bactericide is determined to be an ineffective bactericide; if the deviation value is less than the preset threshold, the simulated bactericide is determined to be an effective bactericide, and proceed to the next step.

[0012] (5) Obtain the hybrid model box of the last frame in the trajectory file, then calculate the binding energy between the bactericide and bacteria in the hybrid model box of the last frame, and then compare the calculated binding energy with the preset value of binding energy to obtain the deviation value. Then compare the deviation value with the preset threshold. If the deviation value is not less than the preset threshold, the simulated bactericide is determined to be an inefficient bactericide; if the deviation value is less than the preset threshold, the simulated bactericide is determined to be an efficient bactericide.

[0013] The method for evaluating the bactericidal performance of the bactericide of this invention utilizes coarse-grained molecular dynamics to construct the basic framework of a bacterial membrane at the nanoscale using a phospholipid bilayer. The choline and phosphate groups in the head groups impart positive and negative charges to the bacterial surface, respectively. The bactericide adsorbs onto the bacterial surface through interactions with these charged groups. The bactericidal performance is determined by analyzing the radial distribution function of the bacterial centroid and the bactericide in the simulated trajectory file, as well as the binding energy between the bacteria and the bactericide. By comparing the binding energy between the bactericide and bacteria, it is possible to evaluate whether the bactericide can stably adsorb onto the bacterial surface, thereby hindering normal bacterial metabolism and ultimately killing the bacteria. This method for evaluating the bactericidal performance of the bactericide of this invention eliminates the need for traditional experiments, utilizing a computer-based "virtual experiment." It is not limited by experimental conditions, is highly efficient, reproducible, and provides reliable results, which is beneficial for the rapid design and development of bactericides for oilfield chemical applications.

[0014] Preferably, the method for establishing coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules includes the following steps: first, constructing structural models of water molecules, bactericide molecules, and phospholipid molecules, and optimizing the structures to obtain the minimum energy conformational structures of each structural model, and then constructing coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules.

[0015] Bacteria can be considered to be mainly composed of a cell membrane and a cellular matrix that is surrounded by the cell membrane. Modeling the cell membrane is the most important part of molecular dynamics modeling of cell structure. The cell membrane is a complex system, mainly composed of phospholipid molecules, carbohydrates, and proteins. Phospholipid molecules are the most abundant. The heads of phospholipid molecules are hydrophilic, while the tails are hydrophobic. Multiple phospholipid molecules form a phospholipid bilayer, which constitutes the "skeleton" of the cell membrane, while carbohydrates and proteins are embedded in this skeleton. The common practice in current research on cell membrane modeling is to ignore carbohydrates and proteins and mainly consider modeling the phospholipid bilayer, using the phospholipid bilayer model as the bacterial model.

[0016] For different types of bacteria, such as sulfate-reducing bacteria, iron bacteria, and acid-producing bacteria, since the surface charges of different types of bacteria are slightly different, it is necessary to construct different phospholipid bilayers using different types and proportions of phospholipid molecules to reflect the differences in bacterial models.

[0017] The phospholipid molecular model includes five types of coarse-grained particles: choline, phosphate, glycerol, ester, and hydrocarbon.

[0018] When the fungicide is a quaternary ammonium salt fungicide, the fungicide molecular model includes two types of coarse particles: quaternary ammonium salt and hydrocarbons.

[0019] Preferably, the bactericide is a quaternary ammonium salt bactericide. More preferably, the quaternary ammonium salt bactericide is a phosphate betaine, metronidazole quaternary ammonium salt, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, or dodecyl trimethyl ammonium chloride.

[0020] Preferably, the bactericide is an adsorption-type bactericide. The bacterial surface is composed of a cell wall and cell membrane, containing various components such as mannan, dextran, teichoic acid, proteins, and lipids. The exposed functional groups on the bacterial surface include phosphate groups, carboxyl groups, and amino groups. The main bactericidal principle of adsorption-type bactericides is as follows: the bactericide molecules first combine with the functional groups on the bacterial surface and adsorb onto the bacterial surface, preventing normal bacterial metabolism, disrupting the bacterial redox reaction, and inhibiting spore formation.

[0021] When setting the force field parameters for each coarse-grained model, parameter settings in existing technologies can be referenced. For example, the coarse-grained force field type for choline coarse-grained particles in phospholipid molecules is Q0, with a charge of 1.0; the coarse-grained force field type for phosphate coarse-grained particles in phospholipid molecules is Qa, with a charge of -1.0; the coarse-grained force field type for glycerol coarse-grained particles in phospholipid molecules is Na, with a charge of 0; the coarse-grained force field type for hydrocarbon coarse-grained particles in phospholipid molecules is C1, with a charge of 0; the coarse-grained force field type for sulfonate coarse-grained particles in bactericide molecules is Qa, with a charge of -1.0; the coarse-grained force field type for quaternary ammonium salt coarse-grained particles in bactericide molecules is Q0, with a charge of 1.0; the coarse-grained force field type for hydrocarbon coarse-grained particles in bactericide molecules is C1, with a charge of 0; and the coarse-grained force field type for water molecules is P4, with a charge of 0.

[0022] Preferably, in the water-bacteria-bactericide mixed model box, the ratio of the coarse-grained model of water molecules to the coarse-grained model of bactericide molecules is 200:1. The ratio of the coarse-grained model of water molecules to the coarse-grained model of bactericide molecules does not affect the final judgment result. This invention studies the interaction between a single bactericide and the phospholipid bilayer in this mixed model box, and is independent of the bactericide concentration.

[0023] To simplify the model system and facilitate calculation, preferably, the dimensions of the water-bacteria-bactericide mixture model box are as follows: The density of both the coarse-grained model of water molecules and the coarse-grained model of globular phospholipid bilayers is 1 g / cm³. 3 The number of coarse-grained models for bactericide molecules is 1, and the number of bacterial models is 1.

[0024] Preferably, when optimizing the structure of the hybrid model box, the optimization endpoint is determined according to the following method: the energy change gradient of the optimized model box is compared with the preset value of the energy change gradient to obtain the deviation value, and then the deviation value is compared with the preset threshold. If the deviation value is not less than the preset threshold, the structure is optimized again until the deviation value corresponding to the last structure optimization is less than the preset threshold. If the deviation value is less than the preset threshold, the optimization endpoint is reached, and the optimized model box is the minimum energy structure of the water-bacteria-bactericide hybrid model box.

[0025] It is understood that the energy change gradient in this invention refers to the rate of change of energy density in the box.

[0026] In this invention, the preset value of the energy change gradient is greatly affected by the temperature of the structurally optimized model box, the density of the coarse-grained model of water molecules and the coarse-grained model of the globular phospholipid bilayer, the coarse-grained model of the bactericide molecules, and the number of bacterial models. The energy change gradient of the structurally optimized model box composed of a bactericide with good performance and the corresponding bacteria can be calculated first, and the calculated energy change gradient can be used as the preset value of the energy change gradient.

[0027] Preferably, the preset threshold in the method for determining the optimization endpoint is 5% to 10%.

[0028] Preferably, the preset threshold in step (4) is 5-10%.

[0029] In this invention, in step (5), the preset value of binding energy is determined according to the following method: calculate the binding energy between the bactericide and bacteria in the water-bacteria-bactericide mixture model box composed of the existing bactericide with better performance and the corresponding bacteria, and use the calculated binding energy as the preset value of binding energy.

[0030] The lower the binding energy between the bactericide and bacteria in the hybrid model box in the last frame, the more stable the system tends to be. Numerous experimental results show that, preferably, the preset threshold in step (5) is 5-10%.

[0031] Preferably, in step (5), the method for calculating the binding energy between the bactericide and bacteria is as follows:

[0032] E binding =-E interact

[0033] Among them, E binding E represents the binding energy between the disinfectant and bacteria in the blended model box at the last frame. interact =E total -(E Bacteria +E bactericide )+E sol E interactE represents the interaction energy between the bactericide and bacteria in the blended model box at the last frame. total E represents the total energy of the blended model box in the last frame. Bacteria E represents the total energy of the bacterial model within the blended model box at the last frame. bactericide E represents the total energy of the disinfectant in the blended model box at the last frame. sol This represents the total energy of the water in the blended model box at the last frame.

[0034] Experimental results show that the preset threshold in step (4), the preset binding energy in step (5), the simulated temperature, the size of the water-bacteria-bactericide mixed model box, the density of the coarse-grained model of water molecules and the coarse-grained model of the globular phospholipid bilayer, and the accuracy of the simulation calculation all affect the final judgment result.

[0035] The technical solution adopted in the evaluation system for the bactericidal performance of the bactericide of the present invention is as follows:

[0036] A system for evaluating the bactericidal performance of a bactericide includes a processor and a memory. The processor executes instructions stored in the memory to implement the bactericidal performance evaluation method of the bactericide as described above.

[0037] The bactericide bactericidal performance evaluation system of the present invention has the advantages of high efficiency, fast speed, strong repeatability and reliable results when used to evaluate the bactericidal performance of bactericides. Attached Figure Description

[0038] Figure 1 This is a schematic flowchart of the method for evaluating the bactericidal performance of the bactericide in Example 1 of the present invention. Detailed Implementation

[0039] The technical solution of the present invention will be further described below with reference to specific embodiments.

[0040] I. Specific embodiments of the method for evaluating the bactericidal performance of the bactericide of the present invention are as follows:

[0041] Example 1

[0042] The method for evaluating the bactericidal performance of the bactericide in this embodiment, such as... Figure 1 As shown, the specific steps include:

[0043] (1) Construct structural models of water molecules, bactericide molecules, and phospholipid molecules, and optimize their structures.

[0044] The three-dimensional molecular structure models of water molecules, bactericide molecules, and phospholipid molecules were drawn using the Sketch tool in the Materials Studio simulation software. The structures were then optimized using the Forcite molecular dynamics calculation module to obtain the minimum energy conformation structure. The Sketch tool and the Forcite module are dedicated modeling and calculation tools in the Materials Studio simulation software, respectively.

[0045] Bacteria can be considered to be mainly composed of a cell membrane and a cellular matrix that is surrounded by the cell membrane. Modeling the cell membrane is the most important part of molecular dynamics modeling of cell structure. The cell membrane is a complex system, mainly composed of phospholipid molecules, carbohydrates, and proteins. Phospholipid molecules are the most abundant. The heads of phospholipid molecules are hydrophilic, while the tails are hydrophobic. Multiple phospholipid molecules form a phospholipid bilayer, which constitutes the "skeleton" of the cell membrane, while carbohydrates and proteins are embedded in this skeleton. The common practice in current research on cell membrane modeling is to ignore carbohydrates and proteins and mainly consider modeling the phospholipid bilayer, using the phospholipid bilayer model as the bacterial model.

[0046] (2) Establish coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules.

[0047] Using the Build Mesostructure tool in the Build toolkit, coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules can be constructed with four carbon atoms as a bead through the BeadTypeshe (setting bead type), Coarse Grain (coarsening), and Mesomolecule (building coarse-grained molecular models) functions.

[0048] The coarse-grained model of phospholipid molecules includes five types of coarse-grained particles: choline, phosphate, glycerol, ester, and hydrocarbon.

[0049] The head of the coarse-grained model of the phospholipid molecule consists of positively charged choline and negatively charged phosphate. Modeling can be achieved by embedding positive point charges inside the particles corresponding to choline and negative point charges inside the particles corresponding to phosphate. The glycerol part can be modeled by embedding dipoles inside the particles corresponding to glycerol. The tail of the phospholipid molecule model consists of two tail chains, which are composed of ester groups and hydrocarbons. The ester group part can be modeled by embedding dipoles inside the particles corresponding to ester groups, while the hydrocarbon part can be modeled by uncharged particles. All of the above particles are coarse-grained particles, and each particle represents 4 carbon atoms and several hydrogen atoms bonded to carbon atoms.

[0050] In this embodiment, the bactericide molecule is dodecyltrimethylammonium chloride. The coarse-grained model of the bactericide molecule includes two types of coarse-grained particles: quaternary ammonium salt, chloride ion, and hydrocarbon.

[0051] (3) Based on the properties of the molecules (water molecules, bactericide molecules, phospholipid molecules), set the force field parameters of each coarse-grained bead in each coarse-grained model.

[0052] The Martini force field (coarse-grained force field) built into the Materials Studio simulation software was used to manually set the force field parameters for each coarse-grained bead. The force field parameter information was viewed in the property browser. The coarse-grained force field type for choline coarse-grained particles in phospholipid molecules was Q0, with a charge of 1.0; the coarse-grained force field type for phosphate coarse-grained particles in phospholipid molecules was Qa, with a charge of -1.0; the coarse-grained force field type for glycerol ester coarse-grained particles in phospholipid molecules was Na, with a charge of 0; and the coarse-grained force field type for hydrocarbons in phospholipid molecules was... The coarse-grained force field type of the coarse particles is C1, with a charge of 0; the coarse-grained force field type of the sulfonate salt of the bactericide molecule is Qa, with a charge of -1.0; the coarse-grained force field type of the quaternary ammonium salt coarse particles in the bactericide molecule is Q0, with a charge of 1.0; the coarse-grained force field type of the hydrocarbon coarse particles in the bactericide molecule is C1, with a charge of 0; the coarse-grained force field type of the water molecule is P4, with a charge of 0; in this embodiment, the force field parameters of each coarse-grained bead are the conventional settings under the Martini force field;

[0053] (4) Construct a globular phospholipid bilayer model based on a coarse-grained model of phospholipid molecules to simulate bacterial biofilms.

[0054] Using the Mesostructure Template function of the Build Mesostructure tool in the Build toolkit, a mesoscopic structure template (a three-dimensional periodic model box) was constructed. A System box was established as the solution region, and a Shell box was added in the center of the System box as the bacterial region. First, the head and tail of phospholipid molecules were marked using the BuildMesostructure tool in the Materials Studio simulation software, and then the Mesostructure function was used to fill them into the Shell region to obtain a coarse-grained model of a globular phospholipid bilayer, which was used to simulate the bacterial surface. By manually setting the charge type and the ratio of positive and negative charges, different types and ratios of phospholipid molecules were represented to construct different phospholipid bilayers, thereby reflecting the differences in the bacterial model and distinguishing different types of bacteria.

[0055] (5) Construct a water-bacteria-bactericide hybrid model box that includes a water molecule coarse-grained model, a bactericide coarse-grained model, and a globular phospholipid bilayer model.

[0056] Using the Mesostructure function of the Build Mesostructure tool in the Build toolkit, coarse-grained models of water droplets and bactericide molecules were randomly filled into the System box (solution area) at a certain ratio (200:1). Then, the spherical phospholipid bilayer model was integrated to form a water-bacteria-bactericide mixed model box. In the water-bacteria-bactericide mixed model box, the density of the coarse-grained models of water molecules and spherical phospholipid bilayers was 1 g / cm³. 3 The number of coarse-grained models for the bactericide molecule is 1, the number of bacterial models is 1, and the dimensions of the water-bacteria-bactericide mixture model box are [dimensions to be filled in].

[0057] (6) Optimize the structure of the water-bacteria-bactericide hybrid model box to obtain the minimum energy structure of the water-bacteria-bactericide hybrid model box.

[0058] The calculation was performed in the Mesocite module, with the task being Geometry Optimization. The Smart method (smart minimizing method) was used to optimize the structure of the water-bacteria-bactericide hybrid model box. Fine accuracy was selected, and the Martini force field was chosen. Ewald and Bead Based summation methods were used to calculate the electrostatic and van der Waals interactions within the water-bacteria-bactericide hybrid model box system, respectively. The Mesocite module is a dedicated module in Materials Studio for calculating mesoscopic dynamics simulations. The Smart method is one of the more accurate structural optimization methods. The Martini force field is used for mesoscopic dynamics simulation; the force field file needs to be edited manually. Using Ewald and Bead Based summation methods to calculate the electrostatic and van der Waals interactions within the system is the most accurate method reported in the relevant literature.

[0059] The energy change gradient (energy convergence threshold) E of the optimized model box is compared with the preset energy change gradient value F to obtain the deviation value, which is calculated as |EF| / F×100%. The deviation value is then compared with the preset threshold (5%~10%). If the deviation value is not less than the preset threshold, structural optimization is performed again until the deviation value corresponding to the last structural optimization is less than the preset threshold. If the deviation value is less than the preset threshold, the process proceeds to the next step.

[0060] (7) Perform dynamic calculations on the minimum energy structure of the water-bacteria-bactericide mixture model box under isothermal and isobaric ensembles to obtain the relaxation box of the water-bacteria-bactericide mixture model box.

[0061] The calculation was performed in the Mesocite module under the Dynamics task. This was a coarse-grained dynamics calculation with a total simulation time of 200 ps, ​​a time step of 0.5 fs, and a total number of steps of 400,000, with the system placed under an isothermal and isobaric ensemble (NPT). The calculation accuracy was set to Fine, and the force field was set to Martini force field. The electrostatic interactions and van der Waals interactions within the system were calculated using Ewald and Bead Based summation methods, respectively, to obtain the relaxation box.

[0062] (8) Perform dynamic calculations on the relaxed box of the water-bacteria-bactericide mixture model box under a canonical ensemble to obtain the trajectory file of the water-bacteria-bactericide mixture model box.

[0063] The calculation was performed in the Mesocite module under the Dynamics task. This task involved coarse-grained dynamics calculations with a total simulation time of 500 ps, ​​a time step of 0.5 fs, and a total number of steps of 1,000,000, all within a canonical ensemble (NVT). The simulation temperature range was set to 35–45 °C. The calculation accuracy was set to Fine, and the force field was set to Martini force field. The electrostatic interactions and van der Waals interactions within the system were calculated using Ewald and Bead Based summation methods, respectively, to obtain the trajectory file of the water-bacteria-bactericide mixture model box.

[0064] (9) Analyze the trajectory file of the water-bacteria-bactericide mixture model box to obtain the radial distribution function (RDF) of the bacterial centroid and the bactericide, as well as the binding energy between the bactericide and bacteria.

[0065] Process the trajectory file of the water-bacteria-bactericide mixed model box, select the entire bacterial model, and use Create Centroid to create the centroid. At the same time, use Edit Sets to mark the centroid of the coarse-grained model of the globular phospholipid bilayer (bacterial centroid), water droplets, and coarse-grained model of the bactericide.

[0066] Calculate the RDF of the bacterial centroid and the disinfectant, as well as the RDF of the bacterial centroid and the water droplets, in the trajectory file of the water-bacteria-disinfectant mixture model box. Specifically, perform the analysis in the Mesocite module, selecting the Radial distribution function as the analysis method and setting the Cutoff radius to... Analyze and calculate the RDF of bacterial centroid and bactericide, as well as the RDF of bacterial centroid and water droplets; when setting the cutoff radius, ensure that the box size is greater than or equal to twice the cutoff radius.

[0067] The peak position A of the RDF curve of bacterial centroid and bactericide is compared with the peak position B of the RDF curve of bacterial centroid and water droplet (in this invention, the number of bactericide molecules and bacterial models in the water-bacteria-bactericide mixed model box is 1, therefore, there is only one peak position A of the RDF curve of bacterial centroid and bactericide and one peak position B of the RDF curve of bacterial centroid and water droplet, which can be easily calculated), and the deviation value is obtained. The deviation value = |AB| / B×100%; the deviation value is compared with a preset threshold (5%~10%). If the deviation value is not less than the preset threshold, it indicates that the bactericide cannot be effectively adsorbed on the bacterial surface and is judged as an ineffective bactericide, which is directly eliminated and the operation ends; if the deviation value is less than the preset threshold, it indicates that the bactericide can be effectively adsorbed on the bacterial surface and is judged as an effective bactericide.

[0068] Take the trajectory file of the water-bacteria-bacterium mixed model box of the effective bactericide, play it to the last frame, and directly output the XSD file to obtain the mixed model box in the last frame (the mixed model box with the lowest energy). Then calculate the binding energy of bactericide and bacteria in the mixed model box in the last frame. The formula for calculating the binding energy of bactericide and bacteria is: E interact =E total -(E Bacteria +E bactericide )+E sol E binding =-E interact E interact E represents the interaction energy between the bactericide and bacteria in the blended model box at the last frame. total E represents the total energy of the blended model box in the last frame. Bacteria E represents the total energy of the bacterial model (spherical phospholipid bilayer model) within the blending model box at the last frame. bactericide E represents the total energy of the bactericide (bactericide coarse-grained model) in the blended model box at the last frame. sol E represents the total energy of the water (coarse-grained model of water molecules) in the blended model box at the last frame. binding The binding energy between the bactericide and bacteria in the hybrid model box at the last frame;

[0069] The calculated binding energy C between the bactericide and bacteria is compared with the preset value D to obtain the deviation value, which is calculated as |CD| / D×100%. The deviation value is then compared with a preset threshold (5%~10%). If the deviation value is not less than the preset threshold, it indicates that the bactericide cannot be stably adsorbed on the bacterial surface and is judged as an inefficient bactericide, which is then eliminated and the operation ends. If the deviation value is less than the preset threshold, it indicates that the bactericide can be stably adsorbed on the bacterial surface and is judged as an efficient bactericide.

[0070] II. Specific embodiments of the bactericidal performance evaluation system of the present invention are as follows:

[0071] Example 2

[0072] The bactericide bactericidal performance evaluation system of this embodiment includes a processor and a memory. The processor is used to execute instructions stored in the memory to implement the bactericide bactericidal performance evaluation method of Embodiment 1.

[0073] Experimental Example

[0074] To evaluate the accuracy of the bactericidal performance evaluation method of the present invention, the results of the method of the present invention are compared with the experimental results. Specifically, sulfate-reducing bacteria and iron bacteria were selected as experimental subjects. Various quaternary ammonium salt bactericides (phosphate betaine, metronidazole quaternary ammonium salt bactericide, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, and dodecyl trimethyl ammonium chloride) were tested separately. Then, the method in Example 1 was used to simulate and evaluate the different quaternary ammonium salt bactericides. The bactericidal effect of each quaternary ammonium salt bactericide was evaluated according to standard SY / T 0532-2012 "Analysis Method for Bacteria in Oilfield Injection Water—Extinction Dilution Method". Taking sulfate-reducing bacteria as an example, the sterilization rate was determined using the exclusion dilution method. The principle is to inject the water sample to be tested into a sulfate-reducing bacteria test bottle using a sterilized syringe for inoculation and dilution, and then incubate it in an electric thermostatic incubator. Based on the positive reaction of the sulfate-reducing bacteria test bottle and the dilution factor, the number of sulfate-reducing bacteria in the water sample was calculated, and finally, the sterilization rate was calculated. The specific test method for sulfate quaternary ammonium salt bactericide is as follows:

[0075] (1) Place the graduated cylinder, pipette, narrow-mouth bottle, syringe, and syringe needle to be used in the experiment into an electric pressure steam sterilizer and sterilize at 0.15 MPa pressure for 0.5 h.

[0076] (2) After measuring 100 mL of the original water sample with a 100 mL graduated cylinder, pour it into a narrow-mouthed glass bottle with a capacity of 125 mL; then replace the original water sample with a water sample in which 10 mg / L of oilfield bactericide (sulfate quaternary ammonium salt) has been added. Repeat the above operation and shake the two narrow-mouthed glass bottles containing the original water sample and the water sample containing the oilfield bactericide well.

[0077] (3) Place the two water samples, one with added and one without added oil field fungicide, in an electric heating constant temperature incubator and incubate at a constant temperature (40℃±1℃) for 4 hours, then remove the two water samples from the constant temperature incubator;

[0078] (4) Arrange the sulfate-reducing bacteria test bottles in a group and number them sequentially;

[0079] (5) Use a sterilized syringe to take 1.0 mL of water sample without oilfield fungicide and inject it into bottle No. 1, then shake thoroughly;

[0080] (6) Using another sterile syringe, take 1.0 mL of water sample from bottle 1 and inject it into bottle 2, then shake thoroughly;

[0081] (7) Use a sterile syringe to take 1.0 mL of water sample from bottle 2 and inject it into bottle 3, then shake thoroughly.

[0082] (8) Continue diluting until the last bottle, and use the test bottle as a blank sample; the number of dilution bottles is determined according to the bacterial content, and it is generally diluted to bottle number 7.

[0083] (9) Dilute the water sample that has been treated with oilfield bactericide and incubated at a constant temperature for 4 hours according to the steps (4)-(8) above;

[0084] (10) Place the above sulfate-reducing bacteria test bottles into an electric thermostatic incubator (the incubation temperature is controlled at 35℃±1℃), and remove them from the electric thermostatic incubator after 7 days.

[0085] (11) If the liquid in the sulfate-reducing bacteria test bottle turns black or has a black precipitate, it indicates the presence of sulfate-reducing bacteria. Determine the number of sulfate-reducing bacteria using the double-repeat bacterial count table (Table A.2 in standard SY / T 0532-2012) based on the dilution method used, and then calculate the bactericidal rate of the bactericide against sulfate-reducing bacteria using the following formula:

[0086]

[0087] In the formula, Y is the bactericidal rate of the bactericide against sulfate-reducing bacteria, %; N0 is the amount of sulfate-reducing bacteria in the water sample without bactericide, CFU / mL; and N1 is the amount of sulfate-reducing bacteria in the water sample with bactericide, CFU / mL.

[0088] Through extensive experiments and simulations, the following conclusions were drawn: For sulfate-reducing bacteria and quaternary ammonium salt fungicides (quaternary ammonium salt fungicides include phosphate betaine, metronidazole quaternary ammonium salt fungicide, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, and dodecyl trimethyl ammonium chloride), when evaluated according to the fungicide performance evaluation method in Example 1, the energy change gradient preset value is 5 × 10⁻⁶. 7 kcal / mol ~ 6 × 10 7 The energy change gradient (energy convergence threshold) of the optimized model box was compared with a preset value of 7%. The peak position of the RDF curve between the bacterial centroid and the bactericide was compared with the peak position of the RDF curve between the bacterial centroid and the water droplet, also with a preset threshold of 7%. The preset value of the binding energy between the bactericide and bacteria was 23.00 kcal / mol. The calculated binding energy between the bactericide and bacteria was compared with the preset value of 7%. The simulation results are as follows: When the quaternary ammonium salt bactericide is phosphate betaine, metronidazole quaternary ammonium salt bactericide, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, or dodecyl trimethyl ammonium chloride, the simulation results show that the above quaternary ammonium salt bactericides are all highly effective bactericides, and the experimental results show that the above quaternary ammonium salt bactericides have a bactericidal rate of more than 99.5% against sulfate-reducing bacteria. This indicates that the simulation results of Example 1 are highly consistent with the experimental results, and the evaluation method of the bactericidal performance of the bactericide of the present invention is more accurate.

[0089] In addition, when evaluating the bactericidal performance of iron bacteria and quaternary ammonium salt bactericides (quaternary ammonium salt bactericides include phosphate betaine, metronidazole quaternary ammonium salt bactericide, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, and dodecyl trimethyl ammonium chloride) according to the evaluation method of bactericide performance in Example 1, the preset value of the energy change gradient is 5 × 10⁻⁶. 7 kcal / mol ~ 6 × 10 7The energy change gradient (energy convergence threshold) of the optimized model box was compared with the preset value of the energy change gradient, and the preset threshold was 6.7%. The peak position of the RDF curve of the bacterial centroid and the bactericide was compared with the peak position of the RDF curve of the bacterial centroid and the water droplet, and the preset threshold was 7%. The preset value of the binding energy between the bactericide and bacteria was 23.00 kcal / mol, and the preset threshold was 7 when comparing the calculated binding energy between the bactericide and bacteria with the preset value of the binding energy between the bactericide and bacteria. At 3%, the simulation results are as follows: When the quaternary ammonium salt bactericide is phosphate betaine, metronidazole quaternary ammonium salt bactericide, sulfate quaternary ammonium salt, dodecyl dimethyl benzyl ammonium chloride, dodecyl dimethyl benzyl ammonium bromide, or dodecyl trimethyl ammonium chloride, the simulation results show that the above quaternary ammonium salt bactericides are all highly effective bactericides, and the experimental results show that the above quaternary ammonium salt bactericides have a bactericidal rate of more than 99.5% against iron bacteria. This indicates that the simulation results of Example 1 are highly consistent with the experimental results, and the evaluation method of the bactericidal performance of the bactericide of the present invention is more accurate.

[0090] The structural formula of the phosphate betaine used in the experimental example is shown in Formula 1:

[0091]

[0092] The structural formula of the metronidazole quaternary ammonium salt bactericide used in the experimental example is shown in Formula 2:

[0093]

[0094] The structural formula of the sulfate quaternary ammonium salt used in the experimental example is shown in Formula 3:

[0095]

[0096] C in Equation 1-3 12 H 25 It represents dodecyl.

Claims

1. A method for evaluating the bactericidal performance of a bactericide, characterized in that, Includes the following steps: (1) Establish coarse-grained models of water molecules, bactericide molecules, and phospholipid molecules, and set the force field parameters of each coarse-grained model; construct a spherical phospholipid bilayer model based on the coarse-grained model of phospholipid molecules to simulate bacterial biofilms. (2) Construct a water-bacteria-bactericide mixed model box that includes a water molecule coarse-grained model, a bactericide coarse-grained model, and a globular phospholipid bilayer model; (3) Optimize the structure of the hybrid model box to obtain the minimum energy structure of the hybrid model box. Then, perform dynamic calculations on the minimum energy structure of the hybrid model box under isothermal and isobaric ensembles and canonical ensembles respectively to obtain the trajectory file of the water-bacteria-bactericide hybrid model box. (4) Analyze the trajectory file to obtain the radial distribution function of the bacterial centroid and the bactericide, and the radial distribution function of the bacterial centroid and the water molecule; compare the peak position of the radial distribution function curve of the bacterial centroid and the bactericide with the peak position of the radial distribution function curve of the bacterial centroid and the water molecule to obtain the deviation value, and then compare the deviation value with the preset threshold. If the deviation value is not less than the preset threshold, the simulated bactericide is determined to be an ineffective bactericide; if the deviation value is less than the preset threshold, the simulated bactericide is determined to be an effective bactericide, and proceed to the next step. (5) Obtain the hybrid model box of the last frame in the trajectory file, then calculate the binding energy between the bactericide and bacteria in the hybrid model box of the last frame, then compare the calculated binding energy with the preset value of binding energy to obtain the deviation value, and then compare the deviation value with the preset threshold. If the deviation value is not less than the preset threshold, then the simulated bactericide is determined to be an inefficient bactericide. If the deviation value is less than the preset threshold, the simulated bactericide is determined to be a highly effective bactericide.

2. The method for evaluating the bactericidal performance of a bactericide as described in claim 1, characterized in that, The bactericide is an adsorption-type bactericide.

3. The method for evaluating the bactericidal performance of the bactericide as described in claim 1, characterized in that, When optimizing the structure of the hybrid model box, the optimization endpoint is determined by the following method: the energy change gradient of the optimized model box is compared with the preset value of the energy change gradient to obtain the deviation value, and then the deviation value is compared with the preset threshold. If the deviation value is not less than the preset threshold, the structure is optimized again until the deviation value corresponding to the last structure optimization is less than the preset threshold. If the deviation value is less than the preset threshold, the optimization endpoint is reached, and the optimized model box is the minimum energy structure of the water-bacteria-bactericide hybrid model box.

4. The method for evaluating the bactericidal performance of the bactericide as described in claim 3, characterized in that, The preset threshold in the method for determining the optimization endpoint is 5% to 10%.

5. The method for evaluating the bactericidal performance of a bactericide as described in any one of claims 1-4, characterized in that, The preset threshold in step (4) is 5-10%.

6. The method for evaluating the bactericidal performance of a bactericide as described in any one of claims 1-4, characterized in that, The preset threshold in step (5) is 5-10%.

7. The method for evaluating the bactericidal performance of a bactericide as described in any one of claims 1-4, characterized in that, In step (5), the method for calculating the binding energy between the bactericide and bacteria is as follows: AND binding =-E interact Among them, E binding E represents the binding energy between the disinfectant and bacteria in the blended model box at the last frame. interact =E total -(E Bacteria +E bactericide )+E sol E interact E represents the interaction energy between the bactericide and bacteria in the blended model box at the last frame. total E represents the total energy of the blended model box in the last frame. Bacteria E represents the total energy of the bacterial model within the blended model box at the last frame. bactericide E represents the total energy of the disinfectant in the blended model box at the last frame. sol This represents the total energy of the water in the blended model box at the last frame.

8. A system for evaluating the bactericidal performance of a bactericide, characterized in that, It includes a processor and a memory, wherein the processor is used to execute instructions stored in the memory to implement the method for evaluating the bactericidal performance of the bactericide as described in any one of claims 1-7.

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