A method to predict interactions between pollutants and biofilms

Abstract

The present invention belongs to the field of environmental risk assessment and discloses a method for predicting the interaction between pollutants and biofilms. The specific implementation steps include constructing a reaction system, optimizing the structure, simulating the action process, calculating the interaction energy, and judging the reaction mechanism. The pseudo-organic phase n-octanol is introduced to replace the biofilm DPPC, and the molecular dynamics simulation method is used to analyze the transmembrane process of pollutants in n-octanol and DPPC, and the interaction energy between the systems is calculated quickly and simply to explore the adsorption mechanism. This method breaks through the possibility of conducting potential studies on the toxic effects of pollutants without using biological exposure, obtains the interaction and transmembrane information between pollutants and organic phases, helps to visualize molecular reactions, and provides strong technical support for revealing the interaction mechanism between molecules.

Description

Technical Field

[0001] The invention belongs to the field of environmental risk assessment, and in particular relates to a method for predicting the interaction between pollutants and biofilms. Background Art

[0002] As people's environmental awareness increases, they are more concerned about and value environmental pollution problems caused by diverse exposure pathways and high detection frequencies in the environment. Pollutants can directly bind to the membrane receptors and proteins of organisms, resulting in chemical losses and inducing biological toxic effects. The currently used biological toxicity testing methods include in vitro tests and in vivo tests, which are used to discover the degree of harm of poisons to organic life forms. In vivo tests require a large number of test organisms, are costly, and have a long test cycle. According to the 3R principles of environmental ethics animal experiments: reduce the number of experimental animals, replace experimental animals, and optimize experimental procedures, it is necessary to meet people's moral concerns about animals and ensure the development of science.

[0003] In the current environment, computer simulation programs have the advantages of strong predictive ability, non-biological experimentality, time saving and high accuracy compared with animal toxicity tests. Molecular dynamics (MD) simulation is a method of simulating programs in computer software. It is a virtual experiment conducted under the guidance of actual theory, and the results obtained with the experiment are often highly consistent. It has been widely recognized and applied. Dipalmitoylphosphatidylcholine (DPPC) is the basic scaffold of the cell membrane. Due to its many excellent mechanical and biological properties, it has been used as a model membrane to study the interaction between compounds and biological membranes using MD simulation. Due to the complex structure and long calculation cycle of DPPC, it has certain limitations. There is an urgent need for a simplified calculation method that not only follows environmental ethics but also quickly obtains comparable experimental results.

[0004] Octanol-Water Partition Coefficient (Kow) is an important environmental parameter that characterizes the transition of a compound from an organic phase to a biological phase. It has been widely used in the fields of pesticides, separation and purification of chemical products, ecotoxicology, etc. to predict the toxicity of pollutants in the environment. Summary of the invention

[0005] In order to overcome the shortcomings of the prior art, the present invention provides a method for predicting the interaction between pollutants and biofilms while avoiding the possibility of using biological exposure to study the potential toxic effects of pollutants. The method uses n-octanol as a pseudo-organic phase to replace DPPC to improve the prediction efficiency of the interaction between pollutants and biofilms, and realizes the rapid calculation of the interaction between pollutants and biofilms, which greatly shortens the calculation cycle and improves the calculation speed. It provides a simple and fast calculation method for researchers to analyze the transmembrane and toxic effects of pollutants, as well as an alternative test method that can be used for prediction and verification without using biological tests.

[0006] The present invention uses n-octanol to replace the phospholipid bilayer (DPPC) to perform molecular dynamics simulation to study the interaction between pollutants and n-octanol. The simulation uses Materials Studio 8.0 software to construct and optimize n-octanol (C8H 18 O) and the reaction system of pollutants, calculate the interaction energy E through MD simulation process, and use E to judge the difficulty of pollutants crossing the membrane. Combined with relevant toxicity data EC 50 The value and interaction energy E determine whether the pollutant directly reacts with the biological molecules to produce toxic effects and completes the membrane crossing, or relies on the similar dissolution principle of n-octanol distribution to cross the membrane.

[0007] The above object of the present invention is achieved through the following technical solution: a method for predicting the interaction between pollutants and biofilms, the specific implementation steps comprising:

[0008] 1. Constructing the reaction system

[0009] The system was established using Materials Studio 8.0 software through the Amorphous Cell Calculation module of Modules. The main steps were as follows: in the Setup module, select Confined Layer for Task, Medium for Quality, and the average value of the sum of the n-octanol density and the contaminant density (unit: g / m 3 ). In the Energy module, select COMPASS for Forcefield and Forcefield assigned for Charges. Click Run to complete the reaction system construction.

[0010] 2. Optimize structure

[0011] Select the Forcite Geometry Optimization module in Modulesde, select Smart for Algorithm, set Quality to Fine, set Max.iterations to 500, set External pressure to 0.0GPa, close the dialog box, click Run, close the Forcite Calculation dialog box, and complete the structure optimization.

[0012] 3. Simulation process

[0013] Select the Forcite Dynamics module in Modules. Pressure is not a critical factor in this study, so the specific operation steps in the Dynamics module are as follows: Ensemble uses NVT (canonical ensemble), Initial velocities select Random, Temperature (simulation system temperature) is set to 298.0K. Time step (step length) is set to 1.0fs, and the motion trajectory is recorded every 1.0fs. Total simulation time (total simulation time) is set to 1.0×10 4 ps (input 1.0e4), Number of steps (total step length) is 1×10 7 , Frame output every is set to 2000steps, output the image every 20000 steps, and collect data.

[0014] 4. Calculate the interaction energy

[0015] The data collected in step 3 are used to directly calculate the stable configuration of C8H 18 The interaction energy E (unit: kcal / mol) between the O-pollutant system is calculated as follows:

[0016]

[0017] Where: E 总 is the total energy of the system after simulation, E 物质 is the energy of the individual reacting species after simulation, is the energy after simulation of n-octanol. The above values ​​are from steps 1-3.

[0018] 5. Determine the reaction mechanism

[0019] The E value in step 4 is used to evaluate the difficulty of the pollutant to cross the membrane. The larger the E value, the more stable the adsorption and the easier it is for the adsorption to occur; when E is 0 or negative, the adsorption is more difficult to occur. Compare the toxicity EC50 value with the interaction energy E to determine whether the pollutant directly reacts with the biomolecule to produce toxic effects and complete the membrane crossing, or relies on the principle of similar dissolution of like by n-octanol distribution to cross the membrane.

[0020] For pollutants to interact with organisms, they must first come into contact with the membrane structure of the organism, then be adsorbed on its surface and then enter the organism across the membrane. If there is a weak adsorption effect, it means that the possibility of it crossing the biological membrane and entering the organism is low.

[0021] After crossing the membrane of an organism, pollutants will interact with active proteins or biological molecules, interfering with and destroying the body's normal physiological functions. Ultimately, environmental pollutants will exhibit corresponding toxic effects on organisms.

[0022] In aquatic ecological risk assessment, it is very important to study the toxic action mode of organic pollutants on aquatic organisms. At present, the toxic action mode of organic pollutants on aquatic organisms can be divided into two types: anesthetic type and reactive type. [1] . Reactive compounds refer to organic substances whose compounds themselves or their metabolites can react with certain structures commonly present in biological macromolecules. Anesthetic compounds refer to compounds that do not undergo biochemical reactions with various target sites of the organism during the entire toxic process. The toxicity of reactive compounds is significantly higher than that of anesthetic compounds. The anesthetic effect is achieved through a certain non-covalent interaction between the compound and the cell membrane, which reversibly changes the structure and function of the cell membrane, thereby producing a toxic effect on the organism. [2] The toxicity of narcotic compounds depends on their ability to enter organisms, so their toxic potential is completely dependent on hydrophobicity and has a good correlation with the logarithm of the n-octanol / water partition coefficient, lgKow. Identifying the toxic action mode of organic pollutants on different aquatic organisms is not only conducive to evaluating the ecological risk of organic pollutants, but also helps to explain the toxic action mechanism of organic pollutants.

[0023] Compared with the prior art, the present invention has the following beneficial effects: by introducing a pseudo-organic phase n-octanol to replace DPPC, a molecular dynamics simulation method is used to analyze the transmembrane process of pollutants in n-octanol and DPPC, the interaction energy between the systems is calculated quickly and simply, the adsorption mechanism is explored, and the calculation results that are consistent with or similar to the test results are obtained. This supercomputing method is consistent with the mutual adsorption between macromolecular substances and the way they pass through the biological membrane, which helps to visualize molecular reactions and provide strong technical support for revealing the mechanism of intermolecular interaction. The present invention proposes the possibility of avoiding the use of biological exposure to study the potential toxic effects of pollutants, and provides a simple and fast calculation method for the majority of researchers to analyze the transmembrane and toxic effects of pollutants, as well as an alternative test method that can be used for prediction and verification without using biological tests. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0025] Figure 1 It is C8H 18 O-pollutant system construction process step diagram;

[0026] Figure 2 It is C8H 18 Schematic diagram of the construction of the O-pollutant system;

[0027] Figure 3 It is C8H 18 Specific procedure diagram for optimizing the structure of O-pollutant system;

[0028] Figure 4 It is C8H 18 Schematic diagram of the optimized structure of the O-pollutant system;

[0029] Figure 5 It is C8H 18 Specific procedure diagram for simulation of O-pollutant system;

[0030] Figure 6 It is C8H 18 Schematic diagram of the simulation effect of the O-pollutant system. DETAILED DESCRIPTION

[0031] The following is combined with Figure 1-6 The present invention is described in detail by specific examples, but the protection scope of the present invention is not limited. Unless otherwise specified, the experimental methods used in the present invention are conventional methods, and the experimental equipment, materials, reagents, etc. used can be obtained from commercial channels.

[0032] Example 1

[0033] (1) The basic data of organophosphates, such as names, chemical formulas, and abbreviations, were obtained according to reference 3 and summarized in Tables 1 and 2;

[0034] (2) Using the T3 subspecies of Photorhabdus luminescens as the test organism, the half-maximal effect concentration (EC) of organophosphates on Photorhabdus luminescens was measured using a DXY-2 biological toxicity tester. 50 Toxicity data, the method is as follows:

[0035] ① Preparation of solid slant culture medium and culture fluid;

[0036] ②Resuscitation of luminescent bacteria freeze-dried powder: use 3% NaCl solution;

[0037] ③ Cultivation of slant bacteria: Use an inoculation stick to transfer to the slant of a test tube for subculture, and culture at a constant temperature of 20°C;

[0038] ④ Cultivation of shake flask culture: transfer the third generation slant culture of luminescent bacteria into 50 ml culture solution, and culture at 20℃ with shaking until the logarithmic growth phase for later use;

[0039] ⑤ Preparation of working bacterial solution: Pipette a certain amount of cultured shake flask bacterial solution into 3% NaCl solution, stir thoroughly, and dilute to a degree that controls the blank luminescence intensity at 700-800mV;

[0040] ⑥Toxicity (15min-EC 50 ) Determination: Prepare the compound to be tested into 7 concentration gradients, take 2.0 mL of each and add them to the stoppered ground-mouth colorimetric tube, and use 2.0 mL of 3% NaCl solution as a blank control (set up 3 groups in parallel). After the cultured bacterial solution is magnetically stirred evenly, take 0.5 mL and mix it in each colorimetric tube. After exposure for 15 minutes, use the DXY-2 biological toxicity tester to measure the luminescence intensity and calculate the relative inhibition rate. The calculation formula is as follows:

[0041]

[0042] The inhibition rate and the concentration of the tested compound were regressed to establish a dose-effect curve, and the corresponding effect concentration EC at 50% inhibition was calculated according to the regression equation. 50 , where the horizontal axis of the regression equation is concentration and the vertical axis is inhibition rate.

[0043] (3) Materials Studio 8.0 software was used to perform molecular dynamics simulations of the total system energy, individual material energy, and interaction energy of octanol and phospholipid bilayers.

[0044] Using tri(2-chloroethyl) phosphate (TCEP) and triethyl phosphate (TEP) as target pollutants, molecular dynamics modeling was used to characterize the carbonylation of CH 18O-TCEP, DPPC-TCEP, C8H 18 The four systems of O-TEP and DPPC-TEP were used to build and optimize the model, simulate the action process and calculate the interaction energy. The magnitude of the interaction energy reflects the spontaneity of the adsorption process and the stability after adsorption. The luminescent bacteria EC of TCEP and TEP was measured using a DXY-2 biological toxicity tester. 50 Values, using toxicity data (Photobacterium EC 50 ) to verify the rationality of the replacement results. Detailed data are shown in Table 1.

[0045] Table 1 Parameters of TCEP and TEP

[0046]

[0047] According to the luminescent bacteria EC 50 The smaller it is, the greater the toxicity. It is concluded that the toxicity of TCEP is greater than that of TEP. The toxic action mode of TCEP and TEP is judged. According to the fact that the toxicity of reactive compounds is significantly higher than that of anesthetic compounds, it is shown that TCEP is a typical reactive compound. TCEP itself or its metabolites react biochemically with biological macromolecules existing in organisms and produce toxic effects on luminous bacteria. On the contrary, TEP is an anesthetic compound that produces toxicity through distribution. The interaction energy data of the four systems in Table 1 show that the interaction energy E of TCEP and TEP is negative and E DPPC-TCEP <E DPPC-TEP Regardless of whether the biofilm is n-octanol or DPPC, the interaction energy of the TCEP system is always smaller than that of the TEP system. The results show that the adsorption capacity between TCEP and n-octanol and DPPC molecules is unstable, and transmembrane behavior is difficult to occur. TCEP directly reacts with biological molecules to produce toxicity and then crosses the membrane. TEP is more likely to cross the membrane and enter the organism directly through the distribution of n-octanol.

[0048] The following conclusions were drawn by combining the judgment of toxic mechanism with the interaction energy E: the greater the toxicity of TCEP, the smaller the interaction energy E. The molecule is dominated by the reaction to produce toxic effects and completes the transmembrane, showing a reactive compound, and the toxicity is negatively correlated with the interaction energy. TEP is dominated by the distribution effect to produce toxic effects and completes the transmembrane, showing an anesthetic compound. Therefore, the experimental results obtained by calculation are consistent with the laboratory test results, and n-octanol can be used to replace DPPC to study the interaction between pollutants and biofilms.

[0049] Using tris(1,3-dichloro-2-propyl) phosphate (TDCP) and tris(butyloxyethyl) phosphate (TBEP) as target pollutants, the molecular dynamics simulation of the pollutants and C8H 18 O and DPPC were used to construct a reaction model system and calculate the interaction energy. The luminescent bacteria EC of TDCP and TBEP was measured using a toxicity tester. 50 Detailed pollutant parameters are shown in Table 2.

[0050] Table 2 Parameters of TDCP and TBEP

[0051]

[0052] Table 2 Photobacteria EC 50 The data show that the toxicity of TDCP is greater than that of TBEP. Therefore, TDCP behaves as a reactive compound that directly reacts with biological molecules to produce toxicity; TBEP behaves as an anesthetic compound. During the entire toxic process, it does not undergo biochemical reactions with the various target sites of the organism. Instead, it changes the structure and function of the cell membrane through a certain non-covalent interaction between the compound and the cell membrane, thereby producing a toxic effect on the organism.

[0053] The comparison of the interaction energy E in the four complex systems of n-octanol and DPPC membranes shows that the interaction energy of TDCP and TBEP is negative. and E DPPC-TDCP >E DPPC-TBEP The results show that TBEP is difficult to cross the membrane and crosses the membrane through the distribution effect of n-octanol; TDCP crosses the membrane more easily and completes the cross-membrane by biochemical reactions with biological molecules to produce toxic effects.

[0054] Consistent conclusions can be drawn from the comprehensive analysis of toxicity and interaction energy. When TDCP is highly toxic, the interaction energy E also increases. Compared with TBEP, TDCP has a stable adsorption capacity and is more likely to cross the biomembrane and react with the organism to produce toxic effects, showing a reactive compound, and the toxicity is positively correlated with the interaction energy. Therefore, n-octanol can be used as a pseudo-organic phase to replace DPPC, providing a quick and easy method for the subsequent study of the transmembrane interaction and toxicity mechanism between pollutants and biomembranes.

[0055] The present invention proposes an alternative method to improve the prediction efficiency of the interaction between pollutants and biofilms, based on the possibility of avoiding the use of biological exposure to conduct potential studies on the toxic effects of pollutants. By introducing the pseudo-organic phase n-octanol, the molecular dynamics simulation algorithm is used to calculate the interaction energy and analyze the adsorption transmembrane behavior between the pollutant and n-octanol. Compared with the complex structure of the model membrane DPPC, the complexity of the system algorithm can be effectively reduced, and the predicted effect of the interaction between the pollutant and the biofilm can be quickly calculated in a short time. The present invention provides a simple and fast calculation method for the majority of researchers to analyze the transmembrane and toxic effects of pollutants, as well as an alternative test method that can be used for prediction and verification without using biological tests.

[0056] The above-described embodiments are only preferred embodiments of the present invention, but not all feasible embodiments of the present invention. For those skilled in the art, any obvious changes made thereto without departing from the principles and spirit of the present invention should be considered to be included in the scope of protection of the claims of the present invention.

[0057] References

[0058] [1] Feng Xiaona, Yang Zhi, Sun Jie, et al. Study on the toxicity correlation of organic pollutants to luminous bacteria and fish [J]. Journal of Ecological Independence, 2017, 12(03): 687-694.

[0059] [2] Li Jinjie, Zhang Xujia, Zhao Yuanhui. Identification of the toxicity mechanism of organic pollutants on aquatic organisms and influencing factors [J]. Environmental Chemistry, 2013, 32(07): 1236-1245.

[0060] [3] Liao Zicong, Li Huiru, Yang Yuanyuan, et al. Research progress on environmental pollution characteristics, toxicity and analytical methods of organophosphate esters (OPEs) [J]. Environmental Chemistry, 2022, 41(4): 1-23.

[0061] [4] Xu Hengpu, Meng Yiming, Li Aotang, et al. Determination and evaluation of biological toxicity of heavy metal contaminated soil by luminescent bacteria[J]. Chemical Industry and Environmental Protection, 2019, 39(05): 538-544.

Claims

1. A method for predicting the interaction between a pollutant and a biofilm, characterized in that: The specific implementation steps include: S1. Construction of reaction system The system was established using Materials Studio 8.0 software through the Amorphous Cell Calculation module of Modules. The steps were as follows: in the Setup module, select Confined Layer for Task, Medium for Quality, and the average value of the sum of the n-octanol density and the contaminant density for Density, in g / m 3 ; Under the Energy module, select COMPASS for Forcefield and Forcefieldassigned for Charges, click Run, and the reaction system is built; S2. Optimize structure Select the Forcite Geometry Optimization module in Modules, select Smart for Algorithm, set Quality to Fine, set Max.iterations to 500, set External pressure to 0.0GPa, close the dialog box, click Run, close the Forcite Calculation dialog box, and complete the structure optimization; S3. Simulation process Select the Forcite Dynamics module in Modulesde. The specific operation steps in this module are as follows: Ensemble uses NVT, Initial velocities select Random, Temperature is set to 298.0K; Time step is set to 1.0fs, the motion trajectory is recorded every 1.0fs, and Total simulation time is set to 1.0×10 4 p.s. Numberofsteps is 1×10 7 , Frame output every is set to 2000steps, output the image every 20000 steps, and collect data; S4. Calculation of interaction energy The data collected in step S3 are used to directly calculate the stable configuration of C8H 18 The interaction energy E between the O-pollutant system is expressed in kcal / mol and is calculated as follows: E=E 总 -(AND 物质 +E C8H18O ) (1) Where: E 总 is the total energy of the system after simulation, E 物质 is the energy of the individual reacting substances after simulation, E C8H18O is the energy after simulation of n-octanol, and the above values ​​are from steps S1-S3; S5. Determine the reaction mechanism The E value in step S4 is used to evaluate the difficulty of pollutants crossing the membrane; the larger the E value, the more stable the adsorption and the easier the adsorption behavior occurs; when E is 0 or negative, the adsorption is more difficult to occur; the toxicity EC 50 The value and interaction energy E are used to determine the transmembrane form of the pollutant.

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