Small molecule transmembrane permeation free energy calculation method and data set establishment method

Abstract

The invention provides a small molecule transmembrane permeation free energy calculation method and a data set establishment method, and belongs to the technical field of free energy calculation. According to the small molecule transmembrane permeation free energy calculation method, coarse graining parameterization processing is carried out on small molecules through a molecular bond network algorithm, a water-membrane system is constructed, and stretching dynamics simulation and umbrella-shaped sampling simulation are carried out through molecular dynamics simulation software. Therefore, a free energy change curve and water-membrane distribution free energy in the compound permeation transmembrane process are obtained. Not only is the experiment time remarkably saved, but also large-batch and high-quality transmembrane infiltration capacity data can be generated. According to the small molecule transmembrane permeation free energy data set establishment method, molecular screening is performed through a chemical characteristic space, so that the data set is wide in application range and high in representativeness. A drug transmembrane free energy prediction model trained by using the data set can more accurately predict the transmembrane capability of the drug, and a scientific basis is provided for drug research and development.

Description

Technical Field

[0001] The present invention relates to a method for calculating the free energy of small molecule transmembrane permeation and a method for establishing a data set, and belongs to the technical field of free energy calculation. Background Art

[0002] In the field of drug development, the transmembrane permeability of small molecule compounds is a key factor in assessing their druggability. As the fundamental structural unit of living organisms, the human cell membrane not only maintains the stability of the intracellular environment but also regulates the flow of substances into and out of cells. Therefore, small molecule compounds must penetrate at least one cell membrane in the human body to reach their target and exert their therapeutic effects. However, accurately and efficiently assessing the transmembrane permeability of small molecule compounds is a key factor in determining their druggability.

[0003] Currently, the determination of the transmembrane permeability of small molecule compounds relies primarily on experimental methods. These methods typically assess transmembrane permeability by simulating a water-membrane environment in vitro and measuring the distribution of the drug on both sides of the membrane after a certain period of time. Although these experimental methods can provide relatively accurate data, they have significant limitations: they are time-consuming, costly, have limited data sets, and have poor reproducibility.

[0004] With the rapid development of computer technology and computational chemistry, computational simulation-based methods are becoming increasingly widely used in drug development. Through computational simulation, we can deeply understand the interaction mechanisms of small molecules with cell membranes at the molecular level, thereby accurately predicting their transmembrane permeability. This approach not only saves time and costs but also generates large quantities of high-quality transmembrane permeability data, providing strong support for drug development.

[0005] However, existing computational simulation methods still have some shortcomings. For example, while traditional all-atom simulations offer high accuracy, they are computationally intensive, making them difficult to apply to large-scale compound screening. While coarse-grained simulation methods can significantly reduce computational complexity, their accuracy and reliability when dealing with complex molecular systems still need to be improved. Therefore, developing efficient and accurate computational simulation methods is crucial for advancing drug discovery. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for calculating the free energy of small molecule transmembrane permeation and a method for establishing a data set, which not only significantly saves experimental time but also can generate large quantities of high-quality transmembrane permeation capacity data; at the same time, a corresponding data set is established, and the drug transmembrane free energy prediction model trained with this data set can more accurately predict the transmembrane capacity of the drug, providing a scientific basis for drug research and development.

[0007] To achieve the above-mentioned purpose, the present invention is implemented through the following technical solutions: In a first aspect, a method for calculating the free energy of small molecule transmembrane permeation is provided, comprising the following steps: Get the SMILES format description of the target small molecule; The molecular bond network algorithm based on graph is used to perform coarse-grained parameterization on the molecules to generate a coarse-grained molecular model; Construct a coarse-grained water-membrane system, and dynamically assemble the coarse-grained molecular model with the water-membrane system to position the molecules to the preset positions; Perform stretching dynamics simulations to pull small molecules across the membrane using center-of-mass pulling to generate transmembrane reaction coordinate trajectories. Sampling windows were drawn at fixed intervals along the reaction coordinate trajectory to perform umbrella sampling simulation; The WHAM algorithm was used to perform weighted histogram analysis on the umbrella sampling results, and the transmembrane free energy change curve and water-membrane partition free energy were output.

[0008] Preferably, the molecular bond network algorithm includes: Mapping atoms to coarse-grained beads; parameterize non-bonded interactions between atoms; Parameterize interatomic bonding interactions; Generate the initial three-dimensional structure of the molecule and optimize it based on the MMFF94 force field; Generate molecular structure and parameter files based on atom-bead mapping.

[0009] Preferably, the dynamic assembly comprises: Define the small molecule simulation box and center; Insert small molecules 1 nm above the membrane system and replace water molecules at that position; Calculate the number of replaced water molecules and add 0.1M NaCl solution; Perform energy optimization and multi-stage equilibrium simulations.

[0010] Preferably, the equilibrium simulation process uses a v-rescale temperature coupling algorithm to control the system equilibrium temperature to 303.15K, and uses the Berendsen method to control the system pressure to 1 bar.

[0011] Preferably, the specific method of performing umbrella sampling simulation is as follows: The sampling window is extracted with a pitch of 0.1 nm along the Z axis; 60 windows were extracted from each system, and the simulation time of each window was 100 ns.

[0012] In a second aspect, a method for establishing a small molecule transmembrane permeation free energy dataset is provided, comprising: Neutral small molecules were screened from the database, and molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds and polar surface area were extracted to form a high-dimensional feature space; The t-SNE algorithm is used to reduce the high-dimensional feature space to a two-dimensional plane; A preset number of small molecules are randomly selected until the distribution uniformity condition is met; Calculating the transmembrane permeation free energy of the selected small molecule using the small molecule transmembrane permeation free energy calculation method; The molecular SMILES format description is associated with the calculated transmembrane permeation free energy to generate a structured data set.

[0013] Preferably, the distribution uniformity condition is: the difference in two-dimensional spatial distribution density is less than or equal to 20% and the full-area coverage is greater than or equal to 95%.

[0014] In a third aspect, a system for calculating the free energy of small molecule transmembrane permeation is provided, comprising: Molecular coarse-graining module: configured to receive SMILES input, perform coarse-graining parameterization on molecules based on the graph-based molecular bond network algorithm, and generate a coarse-grained molecular model; Membrane environment building module: configured to generate a coarse-grained water-membrane system; Dynamic assembly engine: configured to dynamically assemble the coarse-grained molecular model with the water-membrane system and position the molecules to pre-set locations; Transmembrane trajectory generator: configured to drive molecules to move along the membrane normal according to the stretching dynamics model and generate transmembrane reaction coordinate trajectories; Free energy calculation unit: It is configured to extract sampling windows at fixed intervals along the reaction coordinate trajectory, perform umbrella sampling simulation, and output free energy curves and water-membrane partition free energy through the WHAM algorithm.

[0015] In a fourth aspect, a system for establishing a small molecule transmembrane permeation free energy dataset is provided, comprising: Chemical feature extractor: configured to screen neutral small molecules and extract molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, and polar surface area to form a high-dimensional feature space; Feature space dimensionality reducer: configured to use the t-SNE algorithm to map high-dimensional features to a two-dimensional plane; Molecular screening engine: configured to randomly select a preset number of small molecules until the distribution uniformity condition is met; Data synthesis terminal: configured to calculate the transmembrane permeation free energy using the small molecule transmembrane permeation free energy calculation method, and associate the molecular SMILES with the transmembrane free energy calculation results to generate a structured data set.

[0016] In a fifth aspect, a device for calculating the free energy of small molecule transmembrane permeation is provided, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the method for calculating the free energy of small molecule transmembrane permeation when running the program instructions.

[0017] The advantages of the present invention are: This paper proposes a method for calculating the free energy of small molecule transmembrane permeation. This method uses a molecular bond network algorithm to perform coarse-grained parameterization of small molecules, construct a water-membrane system, and then uses molecular dynamics simulation software to perform stretching dynamics and umbrella sampling simulations. This method then generates a free energy curve and water-membrane partition free energy for the compound's transmembrane permeation process. This method not only significantly reduces experimental time but also generates large quantities of high-quality transmembrane permeation data, providing strong support for drug development.

[0018] The present invention also relates to a method for establishing a small molecule transmembrane permeation free energy dataset. This method uses chemical feature space to screen molecules, resulting in a dataset with broad applicability and strong representativeness. A drug transmembrane free energy prediction model trained using this dataset can more accurately predict a drug's transmembrane capacity, providing a scientific basis for drug research and development.

[0019] In summary, the small molecule transmembrane permeation free energy calculation method and data set establishment method proposed in the present invention based on the molecular bond network algorithm have broad application prospects and important scientific value in the field of drug research and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0021] Figure 1 Schematic diagram of a process for calculating the free energy of small molecule transmembrane permeation according to an embodiment of the present application.

[0022] Figure 2 Schematic diagram of the process of establishing a small molecule transmembrane permeation free energy dataset according to an embodiment of the present application.

[0023] Figure 3 Schematic diagram of the structure of a small molecule transmembrane permeation free energy calculation system according to an embodiment of the present application.

[0024] Figure 4 Schematic diagram of the system for establishing a dataset for calculating the free energy of transmembrane permeation of small molecules according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0026] Example 1 like Figure 1 As shown, a method for calculating the free energy of small molecule transmembrane permeation comprises the following steps: S1: Obtain the SMILES format description of the target small molecule; S2: Use graph-based molecular bond network algorithm to perform coarse-grained parameterization on molecules and generate coarse-grained molecular models; S3: Construct a coarse-grained water-membrane system, and dynamically assemble the coarse-grained molecular model with the water-membrane system to position the molecules to the preset positions; S4: Perform stretching dynamics simulations to pull small molecules across the membrane in a center-of-mass pulling manner to generate transmembrane reaction coordinate trajectories; S5: Extract sampling windows at fixed intervals along the reaction coordinate trajectory to perform umbrella sampling simulation; S6: The WHAM algorithm is used to perform weighted histogram analysis on the umbrella sampling results, and the transmembrane free energy change curve and water-membrane partition free energy are output.

[0027] The above scheme covers all steps from obtaining small molecule information to the final output of free energy change curve and water-membrane distribution free energy, providing a systematic solution for related research.

[0028] As a refinement of the above embodiment, in step S1, the SMILES (Simplified Molecular Input Line Entry System) format description of the molecule is obtained through the PubChem website; wherein, the SMILES format, that is, the simplified molecular linear input specification, is a specification that clearly describes the molecular structure using an ASCII character string. This character string can accurately describe the chemical structure of a molecule and can be recognized by most molecular editing software and converted into a two-dimensional or three-dimensional model of the molecule, so as to facilitate compatibility with more software and improve the compatibility of input data.

[0029] As a refinement of the above-mentioned embodiment, the graph-based molecular bond network algorithm in step S2 is a fast, universal, and symmetry-preserving system for coarse-grained mapping and parameterization of small molecules. Its coarse-grained modeling of small molecules primarily proceeds through three stages: 1. Mapping atoms onto coarse-grained beads; 2. Parameterization of non-bonded interactions between atoms; 3. Parameterization of bonded interactions between atoms; 4. To achieve a more accurate molecular conformation, in this embodiment, the RDKit package is used to generate initial three-dimensional structures of 1,000 molecules using the MMFF94 force field, followed by screening and optimization; 5. Finally, the molecular structure and parameter files are generated based on the atom-bead mapping.

[0030] The graph-based molecular bond network algorithm is used to perform coarse-grained parameterization of molecules. Through operations such as atomic mapping, interaction parameterization and structure optimization, coarse-grained molecular models can be generated more accurately and the calculation accuracy can be improved.

[0031] As a refinement of the above embodiment, the coarse-grained water-membrane system is produced using the CHARMM-GUI online tool in step S3; wherein, CHARMM-GUI is an online tool that can quickly construct a lipid membrane simulation system, and the coarse-grained water-membrane system can be constructed using the PACECGBuilder module it provides.

[0032] Molecular dynamics simulation software is used to assemble the coarse-grained model of the molecule and the water-membrane system, and the molecules are placed in preset positions in the system.

[0033] Specifically, in order to conduct molecular simulation experiments of coarse-grained drug molecules crossing membranes, the system needs to be assembled and preprocessed. The molecular dynamics simulation software gromacs is used in this step, and all force fields involved in molecular dynamics simulation use the Martini2.2 coarse-grained force field. (1) Use the gmxeditconf tool to redefine the coarse-grained drug molecule box and center to facilitate the subsequent insertion steps. (2) Use the gmxinsert-molecules tool to insert the drug into a position about 1nm above the coarse-grained DOPC membrane system and replace the water molecules at the corresponding positions in the system. In order to calculate the number of replaced water molecules, the Linux command sed is used to extract the number of particles in the drug molecule structure file, the coarse-grained membrane system structure file, and the assembled system structure file, and assign them to the variables "lignum", "martininum", and "complexnum". The number of replaced water molecules can be obtained by adding the number of molecular particles to the number of membrane system particles and subtracting the number of assembled system particles, thereby changing the system topology file of the molecular simulation. (3) After the topology file was modified, NaCl was added to the system at a concentration of 0.1 M using the gmxgenion tool. (4) The assembled system was subjected to energy optimization using the steepest descent method, and six consecutive system equilibrium simulations were performed, gradually reducing the confinement of the lipid coarse-grained beads in the system. During the equilibrium process, the v-rescale temperature coupling algorithm was used to maintain the system equilibrium temperature at 303.15 K, which is close to the experimental temperature in most laboratories. The Berendsen method was used to control the system pressure at 1 bar.

[0034] This step constructs a coarse-grained water-membrane system and implements dynamic assembly with a coarse-grained molecular model. It details operations such as small molecule positioning, water molecule replacement, solution addition, energy optimization, and equilibrium simulation to ensure a rational system construction and lay the foundation for subsequent simulations. During the equilibrium simulation process, a specific algorithm is used to precisely control the system's temperature and pressure, ensuring the stability of the simulation environment and making the simulation results more reliable.

[0035] As a refinement of the above embodiment, in steps S4 and S5, the molecular dynamics simulation software gromacs is used to perform energy optimization and system balance on the simulation system, and stretching dynamics simulation and umbrella sampling simulation are performed to obtain the free energy change curve of the compound's transmembrane penetration process and the water-membrane distribution free energy.

[0036] Specifically, the umbrella sampling simulation is performed as follows: The sampling window is extracted with a pitch of 0.1 nm along the Z axis; 60 windows were extracted from each system, and the simulation time of each window was 100 ns.

[0037] This step clarifies the specific method of umbrella sampling simulation, including the sampling interval and number of sampling windows and the simulation time of each window, to ensure the comprehensiveness and accuracy of sampling, thereby making the output free energy change curve and water-membrane distribution free energy more valuable for reference.

[0038] In this example, the phospholipid bilayer model is used as an example for specific description: (1) First, obtain the SMILES format description of the molecule through the PubChem website.

[0039] (2) Then use the graph-based molecular bond network algorithm to perform coarse-grained modeling on the molecular structure and generate the molecular structure and parameter files.

[0040] (3) In the coarse-grained model of the water-membrane system, the inner and outer leaflets of the phospholipid bilayer model are composed of 144 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) molecules, respectively. A water layer with a thickness of 6.0 nm is set inside and outside the phospholipid bilayer. The phospholipid bilayer model is perpendicular to the z-axis of the system and is located at the center of the system, with an initial thickness of approximately 4.0 nm. Molecular dynamics simulation software is used to assemble the molecular coarse-grained model and the water-membrane system, and the molecules are placed in the preset positions in the system.

[0041] (4) In the molecular dynamics simulation software, the small molecule is pulled through the lipid bilayer membrane by center-of-mass traction to complete the stretching dynamics simulation and form the reaction coordinate trajectory.

[0042] Specifically, in a stretching dynamics simulation, it is assumed that one side of the spring is connected to a virtual atom and the other side is connected to a drug molecule. The virtual atom then moves in a specified direction at a constant velocity v, thereby pulling the drug molecule across the membrane. In this example, the hypothetical elastic constant is selected to be 1000 kJ / (mol·nm(2)), the movement velocity of the virtual atom is 0.001 nm / ps, and the simulation duration is 6000 ps. Therefore, the distance the drug molecule moves due to the force is approximately 6 nm.

[0043] (5) The molecular reaction coordinate trajectory was extracted at a fixed interval and umbrella sampling simulation was performed. Based on the output drug coordinate information, corresponding windows were extracted along the Z axis at intervals of 0.1 nm for umbrella sampling simulation. Approximately 60 windows were extracted for each system. Each window was simulated for 100 ns, and the total umbrella sampling simulation time was approximately 6 ms.

[0044] (6) Finally, the WHAM method is used to perform weighted histogram analysis on the output of the umbrella sampling simulation to obtain the free energy change curve of the molecule during the transmembrane process and the water-membrane transfer free energy of the molecule.

[0045] Example 2 like Figure 2 As shown, a method for establishing a small molecule transmembrane permeation free energy dataset includes: S1: Screening of neutral small molecules from the database, extracting molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds and polar surface area to construct a high-dimensional feature space; S2: Use the t-SNE algorithm to reduce the high-dimensional feature space to a two-dimensional plane; S3: Randomly select a preset number of small molecules until the distribution uniformity condition is met; S4: calculating the transmembrane permeation free energy of the selected small molecule using the small molecule transmembrane permeation free energy calculation method; S5: The molecular SMILES format description is associated with the calculated transmembrane permeation free energy to generate a structured dataset.

[0046] As a refinement of the above embodiment, in step S1, all neutral small molecule compounds with a molecular weight less than 500 are selected from the PubChem database, and the molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, and polar area of ​​each small molecule are combined to form a high-dimensional feature space of the molecule.

[0047] PubChem, the Organic Small Molecule Bioactivity Database, is a database of organic small molecule chemical modules, storing compound structural information, biochemical experimental data, and other related information. Molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, and polar area are all characteristics that may affect the ability of small molecules to transmembrane. Therefore, these features are selected to form a high-dimensional feature space of molecular characteristics.

[0048] As a refinement of the above-described embodiment, the step S2 utilizes the t-SNE method to reduce the dimension of the chemical feature space to form a two-dimensional mapping of molecular features, and now the chemical feature space of the molecule can be visualized by a scatter plot. Wherein, the t-SNE method is a nonlinear dimensionality reduction method for mapping high-dimensional data into two-dimensional or three-dimensional space for the purpose of visualization and analysis. The method is a commonly used dimensionality reduction method and is widely used in data mining, machine learning and visualization fields. The method can retain the local structure of the data, and can also mine the global structure of the data by separating clusters. In this step, the t-SNE method is mainly used in converting the chemical feature space of high latitude into two dimensions, so as to facilitate intuitive perception and description of the chemical feature space, and facilitate the selection of representative molecules in subsequent steps.

[0049] As a refinement of the above embodiment, step S3 randomly selects a preset number of molecules from the molecules, repeats the process multiple times, and uses a visualization tool to check until the features of the selected molecules are evenly distributed in the two-dimensional map of molecular features.

[0050] Specifically, the selected molecules should have the following characteristics in chemical space: 1. There is no obvious feature aggregation phenomenon; 2. They are basically evenly distributed in the chemical space; 3. There is no obvious lack of coverage of the chemical space. At this point, the selected molecules are considered to be able to represent this chemical space relatively well.

[0051] In this embodiment, the following thresholds are set: when the difference in two-dimensional spatial distribution density is less than or equal to 20%, it is determined that the selected molecules are basically evenly distributed in the chemical space; when the global coverage is greater than or equal to 95%, it is determined that there is no obvious lack of coverage of the chemical space region.

[0052] As a refinement of the above embodiment, step S4 uses the small molecule transmembrane permeation free energy calculation method described in Example 1 to calculate the transmembrane permeation free energy of all molecules. This is combined with the SMILES format string of the molecules to form a compound transmembrane free energy dataset. This dataset is presented in CSV format and can be read and used using mainstream data processing tools.

[0053] Example 3 like Figure 3 As shown, a small molecule transmembrane permeation free energy calculation system includes: Molecular coarse-graining module: configured to receive SMILES input, perform coarse-graining parameterization on molecules based on the graph-based molecular bond network algorithm, and generate a coarse-grained molecular model; Membrane environment construction module: configured to generate a coarse-grained water-membrane system; implemented by calling the CHARMM-GUI interface; Dynamic assembly engine: configured to dynamically assemble the coarse-grained molecular model with the water-membrane system, position the molecules to pre-set positions, and perform energy optimization and equilibrium simulations; Transmembrane trajectory generator: configured to drive molecules to move along the membrane normal according to the stretching dynamics model and generate transmembrane reaction coordinate trajectories; Free energy calculation unit: It is configured to extract sampling windows at fixed intervals along the reaction coordinate trajectory, perform umbrella sampling simulation, and output free energy curves and water-membrane partition free energy through the WHAM algorithm.

[0054] Specifically, the configuration is to extract the trajectory window at a 0.1 nm pitch for umbrella sampling.

[0055] It should be noted that: in this embodiment, the SMILES representation of the molecule is input into the molecular coarse-graining module, and a coarse-grained molecular topological structure is generated based on the molecular bond network; then, the membrane environment construction module is used to build a water-membrane system that meets the experimental requirements and the constructed molecular topological structure is inserted into the water-membrane system based on the dynamic assembly engine, and the transmembrane trajectory generator and free energy calculation unit are used to output the transmembrane trajectory and free energy curve as well as the water-membrane distribution free energy data.

[0056] Example 4 like Figure 4 As shown, a system for establishing a small molecule transmembrane permeation free energy dataset includes: Chemical feature extractor: configured to screen neutral small molecules and extract molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, and polar surface area to form a high-dimensional feature space; Feature space dimensionality reducer: configured to use the t-SNE algorithm to map high-dimensional features to a two-dimensional plane; Molecular screening engine: configured to randomly select a preset number of small molecules until the distribution uniformity condition is met; Data synthesis terminal: configured to calculate the transmembrane permeation free energy using the small molecule transmembrane permeation free energy calculation method, and associate the molecular SMILES with the transmembrane free energy calculation results to generate a structured data set.

[0057] It should be noted that: in this embodiment, the input molecular SMILES representation is parsed by a chemical feature extractor to obtain the molecular weight, number of heavy atoms, number of hydrogen bond donors / acceptors, number of rotatable bonds, polar surface area and other characteristics of the input molecule; then the high-dimensional features are reduced in dimension by a feature space dimensionality reducer and mapped into a two-dimensional plane; then the molecules are randomly screened out by a molecular screening engine according to preset constraints; the free energy is calculated using the screened molecules according to the method in Example 1, and the calculation results are generated into a structured data set based on the data synthesis terminal.

[0058] Example 5 The present disclosure provides a device for calculating the free energy of small molecule transmembrane permeation, comprising a processor and memory. Optionally, the device may also include a communication interface and a bus. The processor, communication interface, and memory may communicate with each other via the bus. The communication interface may be used for information transmission. The processor may invoke logic instructions in the memory to execute the method for calculating the free energy of small molecule transmembrane permeation described in the above embodiment.

[0059] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0060] Memory, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as the program instructions / modules corresponding to the methods in the embodiments of the present disclosure. The processor executes the program instructions / modules stored in the memory to perform functional applications and data processing, thereby implementing the method for calculating the free energy of small molecule transmembrane permeation in the above-mentioned embodiments.

[0061] The memory may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal device. Furthermore, the memory may include high-speed random access memory and non-volatile memory.

[0062] The technical solutions of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, an optical disk, and other media that can store program code, or a transient storage medium.

[0063] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for calculating the free energy of small molecule transmembrane permeation, characterized in that: The following steps are involved: Obtain the SMILES format description of the target small molecule; The molecular bond network algorithm based on graph is used to perform coarse-grained parameterization on the molecules to generate a coarse-grained molecular model; Construct a coarse-grained water-membrane system, and dynamically assemble the coarse-grained molecular model with the water-membrane system to position the molecules to the preset positions; Perform stretching dynamics simulations to pull small molecules across the membrane using center-of-mass pulling to generate transmembrane reaction coordinate trajectories. Sampling windows were drawn at fixed intervals along the reaction coordinate trajectory to perform umbrella sampling simulation; The WHAM algorithm was used to perform weighted histogram analysis on the umbrella sampling results, and the transmembrane free energy change curve and water-membrane partition free energy were output.

2. The method for calculating the free energy of small molecule transmembrane permeation according to claim 1, wherein: The molecular bond network algorithm includes: Mapping atoms to coarse-grained beads; parameterize non-bonded interactions between atoms; Parameterize interatomic bonding interactions; Generate the initial three-dimensional structure of the molecule and optimize it based on the MMFF94 force field; Generate molecular structure and parameter files based on atom-bead mapping.

3. The method for calculating the free energy of small molecule transmembrane permeation according to claim 1, wherein: The dynamic assembly includes: Define the small molecule simulation box and center; Insert small molecules 1 nm above the membrane system and replace water molecules at that position; Calculate the number of replaced water molecules and add 0.1M NaCl solution; Perform energy optimization and multi-stage equilibrium simulations.

4. The method for calculating the free energy of small molecule transmembrane permeation according to claim 3, wherein: The equilibrium simulation process adopts the v-rescale temperature coupling algorithm to control the system equilibrium temperature to 303.15K, and uses the Berendsen method to control the system pressure to 1 bar.

5. The method for calculating the free energy of small molecule transmembrane permeation according to claim 1, wherein: The specific method of performing umbrella sampling simulation is as follows: The sampling window is extracted with a pitch of 0.1 nm along the Z axis; 60 windows were extracted from each system, and the simulation time of each window was 100 ns.

6. A method for establishing a small molecule transmembrane permeation free energy dataset, characterized in that: include: Neutral small molecules were screened from the database, and molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds and polar surface area were extracted to form a high-dimensional feature space; The t-SNE algorithm is used to reduce the high-dimensional feature space to a two-dimensional plane; A preset number of small molecules are randomly selected until the distribution uniformity condition is met; Calculating the transmembrane permeation free energy of the selected small molecule using the small molecule transmembrane permeation free energy calculation method according to any one of claims 1 to 5; The molecular SMILES format description is associated with the calculated transmembrane permeation free energy to generate a structured data set.

7. The method for establishing a small molecule transmembrane permeation free energy dataset according to claim 6, characterized in that: The distribution uniformity condition is: the difference in two-dimensional spatial distribution density is less than or equal to 20% and the full coverage rate is greater than or equal to 95%.

8. A small molecule transmembrane permeation free energy calculation system, characterized in that: The method for calculating the free energy of transmembrane permeation of small molecules according to any of claims 1 to 5 comprises: Molecular coarse-graining module: configured to receive SMILES input, perform coarse-graining parameterization on molecules based on the graph-based molecular bond network algorithm, and generate a coarse-grained molecular model; Membrane environment building module: configured to generate a coarse-grained water-membrane system; Dynamic assembly engine: configured to dynamically assemble the coarse-grained molecular model with the water-membrane system and position the molecules to pre-set locations; Transmembrane trajectory generator: configured to drive molecules to move along the membrane normal according to the stretching dynamics model and generate transmembrane reaction coordinate trajectories; Free energy calculation unit: It is configured to extract sampling windows at fixed intervals along the reaction coordinate trajectory, perform umbrella sampling simulation, and output free energy curves and water-membrane partition free energy through the WHAM algorithm.

9. A system for establishing a small molecule transmembrane permeation free energy dataset, characterized in that: include: Chemical feature extractor: configured to screen neutral small molecules and extract molecular weight, number of heavy atoms, number of hydrogen bond donors, number of hydrogen bond acceptors, number of rotatable bonds, and polar surface area to form a high-dimensional feature space; Feature space dimensionality reducer: configured to use the t-SNE algorithm to map high-dimensional features to a two-dimensional plane; Molecular screening engine: configured to randomly select a preset number of small molecules until the distribution uniformity condition is met; Data synthesis terminal: configured to calculate transmembrane permeation free energy using the small molecule transmembrane permeation free energy calculation method according to any one of claims 1 to 5, and associate the molecular SMILES with the transmembrane free energy calculation results to generate a structured data set.

10. A device for calculating the free energy of small molecule transmembrane permeation, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the method for calculating the small molecule transmembrane permeation free energy according to any one of claims 1 to 5 when running the program instructions.

Images