Screening method for ganoderma triterpenoids 5a-reductase inhibitor and related device

Abstract

The present application provides ganoderma triterpenoids 5alpha reductase inhibitor screening method and related device, including: obtaining and preprocessing 5alpha reductase three-dimensional structure, determine active pocket area;Obtain the three-dimensional structure of a plurality of ganoderma triterpenoids candidate compounds and carry out conformation optimization;The candidate compound is docked with the active pocket of 5alpha reductase, and the initial screening is carried out according to the binding energy and interaction mode;Molecular dynamics simulation is carried out on the docking complex corresponding to the candidate inhibitor, the root mean square deviation, the root mean square fluctuation, the gyroradius, the number of hydrogen bonds and the binding free energy and other parameters are calculated, and the target candidate inhibitor with stable combination with 5alpha reductase is determined accordingly.The present application can improve the screening efficiency and accuracy of natural source 5alpha reductase inhibitor, and provide reliable basis for subsequent activity verification and drug development.

Description

Technical Field

[0001] This invention relates to the field of drug component screening technology, and more specifically, to a method and related apparatus for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors. Background Technology

[0002] 5α-reductase is a key rate-limiting enzyme in the steroid metabolic pathway, catalyzing the conversion of testosterone into the more bioactive dihydrotestosterone (DHT). Because DHT has strong biological effects in prostate tissue, hair follicles, and sebaceous glands, abnormally elevated DHT levels can easily induce various androgen-dependent diseases such as benign prostatic hyperplasia, androgenetic alopecia, and acne. Therefore, 5α-reductase has become an important target for the intervention of related diseases, and the screening of inhibitors targeting this enzyme is of great significance.

[0003] Currently, the most commonly used 5α-reductase inhibitors in clinical practice are mainly chemically synthesized drugs, such as finasteride and dutasteride. Although these drugs can inhibit 5α-reductase activity to a certain extent, long-term use may be accompanied by adverse reactions such as decreased libido and erectile dysfunction, and there is also a risk of drug resistance. Therefore, developing 5α-reductase inhibitors that are naturally derived, have high safety, and possess stable inhibitory activity has become an important research direction in this field.

[0004] Reishi mushroom, a traditional medicinal and edible fungus, contains a variety of triterpenoid active ingredients. Studies have shown that reishi triterpenoids possess various biological activities, including anti-inflammatory, antioxidant, and immunomodulatory effects, and are generally characterized by low toxicity and good biocompatibility. Therefore, they are considered an important candidate source of natural enzyme inhibitors. Especially in the development of 5α-reductase inhibitors, reishi triterpenoids have high research value and application potential.

[0005] However, existing research on Ganoderma lucidum triterpenoids inhibiting 5α-reductase is mostly focused on the level of Ganoderma lucidum extracts or mixed components, often failing to identify the specific monomeric compounds that exert the effect and lacking precise screening methods targeting monomeric structures. Furthermore, current screening methods typically emphasize static binding analysis, failing to further assess the stability of the binding conformation between candidate compounds and target proteins under dynamic conditions. This results in insufficient reliability and reproducibility of screening results, hindering the further development of subsequent candidates.

[0006] Molecular docking technology enables rapid virtual screening of candidate compounds based on the spatial matching relationship between the active pocket of the target protein and candidate small molecules, thereby narrowing the screening range and improving the initial screening efficiency. Molecular dynamics simulation can further analyze the conformational changes and binding stability of the candidate compound-target protein complex under dynamic conditions, supplementing and verifying the static results of molecular docking. Therefore, how to establish a screening method based on the combination of molecular docking and molecular dynamics analysis for Ganoderma lucidum triterpenoid candidate compounds to achieve efficient screening of 5α-reductase inhibitor candidates has become an urgent technical problem to be solved in this field. Summary of the Invention

[0007] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a method and related device for screening Ganoderma lucidum triterpenoid 5α reductase inhibitors, so as to overcome the shortcomings of the existing technology.

[0008] The above-mentioned technical objective of the present invention is achieved through the following technical solution: Firstly, a method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors, comprising: S1. Obtain the three-dimensional structural data of 5α reductase, and preprocess the three-dimensional structural data to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. S2. Obtain the three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds, and optimize the conformation of the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. S3. The low-energy stable conformations of each candidate compound are molecularly docked with the pretreated 5α-reductase active pocket to generate docking complexes between the candidate compound and 5α-reductase. The candidate compounds are then screened based on their binding energy and interaction modes to obtain at least one candidate inhibitor. S4. Perform molecular dynamics simulation on the docking complex corresponding to the candidate inhibitor to obtain at least one of the following kinetic parameters: root mean square deviation, root mean square fluctuation, and binding free energy of the complex, and determine the target inhibitor that has a stable binding effect with 5α reductase based on the kinetic parameters.

[0009] In one embodiment, obtaining the three-dimensional structural data of 5α-reductase includes: obtaining crystal structure data of 5α-reductase from a protein structure database; preprocessing the three-dimensional structural data includes: removing water molecules, ligand molecules, and impurity molecules from the crystal structure, completing the missing amino acid side chain structure, and performing energy minimization processing to obtain the preprocessed target protein structure; determining the active pocket region of the 5α-reductase includes: identifying the location of the active pocket based on the preprocessed target protein structure, and determining the pocket center coordinates and pocket coverage area for subsequent molecular docking.

[0010] In one embodiment, obtaining the three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds includes: obtaining the three-dimensional structures of multiple Ganoderma lucidum triterpenoid compounds from a compound database; optimizing the conformation of the three-dimensional structure of each candidate compound includes: optimizing the bond angles, dihedral angles and hydrogen atom arrangement of the candidate compounds using a molecular force field until a preset energy convergence condition is reached to obtain the low-energy stable conformation.

[0011] In one embodiment, the step of molecularly docking the low-energy stable conformations of each candidate compound with the pretreated 5α-reductase activity pocket includes: A molecular docking grid box is constructed with the active pocket region as the center, and conformation search and spatial matching calculations are performed on each candidate compound to generate multiple candidate docking complex conformations. The preliminary screening of candidate compounds based on binding energy and interaction modes includes: using the binding energy of the docking complex formed by the candidate compound and 5α reductase as a screening index, and combining the hydrogen bonding information between the candidate compound and key amino acid residues in the active pocket for comprehensive evaluation.

[0012] In one embodiment, the initial screening includes: screening candidate compounds with binding energies below a preset threshold and forming at least a preset number of hydrogen bonds with key amino acid residues in the active pocket as candidate inhibitors; The candidate compounds were ranked according to their binding energy and hydrogen bonding, and at least one of the top-ranked candidate compounds was selected as a candidate inhibitor for molecular dynamics simulation.

[0013] In one embodiment, performing molecular dynamics simulations on the docking complex corresponding to the candidate inhibitor includes: A solvation system containing the docking complex was constructed, and the solvation system was subjected to energy minimization, system equilibrium and formal kinetic simulation in sequence to obtain the conformational evolution trajectory of the complex under dynamic conditions. Based on the conformational evolution trajectory, at least one of the following kinetic parameters of the complex is calculated: root mean square deviation, root mean square fluctuation, cyclotron radius, number of hydrogen bonds, and binding free energy.

[0014] In one embodiment, determining the target candidate inhibitor with stable binding activity to 5α-reductase based on the kinetic parameters includes: When the root mean square deviation of the complex is within a preset fluctuation range, the root mean square fluctuation is lower than a preset threshold, the gyration radius has no obvious abnormal fluctuation, the number of hydrogen bonds meets the preset stability requirements, and the binding free energy is lower than a preset threshold, the corresponding candidate compound is determined to have a stable binding effect with 5α reductase, and the corresponding candidate compound is output as the target candidate inhibitor.

[0015] Secondly, the Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device includes: A preprocessing unit is used to acquire the three-dimensional structural data of 5α reductase, and to preprocess the three-dimensional structural data to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. An optimization unit is used to acquire three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds and to perform conformational optimization on the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. The docking unit is used to perform molecular docking of the low-energy stable conformation of each candidate compound with the pretreated 5α reductase active pocket to generate docking complexes between the candidate compound and 5α reductase, and to perform preliminary screening of each candidate compound based on binding energy and interaction mode to obtain at least one candidate inhibitor. The simulation unit is used to perform molecular dynamics simulations on the docking complex corresponding to the candidate inhibitor, obtain at least one of the root mean square deviation, root mean square fluctuation and binding free energy of the complex, and determine the target inhibitor with stable binding to 5α reductase based on the kinetic parameters.

[0016] Thirdly, a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0017] Fourthly, a computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method described in the first aspect.

[0018] In summary, the present invention has the following beneficial effects: Based on the combination of molecular docking and molecular dynamics analysis, the present invention provides a screening process for candidate inhibitors of 5α reductase. Molecular docking enables rapid initial screening of a large number of candidate compounds, and molecular dynamics simulation is used to further verify the binding stability of candidate compounds and 5α reductase complexes, thereby improving the accuracy and reliability of screening results, narrowing the scope of subsequent research, reducing screening costs, and improving the screening efficiency of 5α reductase inhibitors from natural sources. Attached Figure Description

[0019] Figure 1 This is a flowchart of the Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening method of the present invention; Figure 2 This is a structural diagram of the Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device in an embodiment of the present invention; Figure 3 This is an internal structural diagram of the computer device in an embodiment of the present invention; Figure 4 This is a molecular docking diagram of the ganoderic acid DM and 7BW1 complex in an embodiment of the present invention; Figure 5 This is a schematic diagram of the two-dimensional interaction between the ganoderic acid DM and 7BW1 complex in an embodiment of the present invention; Figure 6 This is a molecular docking diagram of the complex of ganoderic acid B and 7BW1 in an embodiment of the present invention; Figure 7 This is a schematic diagram of the two-dimensional interaction between the ganoderic acid B and the 7BW1 complex in an embodiment of the present invention; Figure 8 This is a molecular docking diagram of the ganoderic acid A and 7BW1 complex in an embodiment of the present invention; Figure 9 This is a schematic diagram of the two-dimensional interaction between the ganoderic acid A and the 7BW1 complex in an embodiment of the present invention; Figure 10 100 ns molecular dynamics simulation diagrams of RMSD (A), RMSF (B), Rg (C), and hydrogen bonds (D) for the complexes of three candidate inhibitors with 5α reductase; Figure 11 Gibbs free energy 3D and 2D plots for ganoderic acid DM(A), ganoderic acid A(B), and ganoderic acid B(C). Figure 12 The contribution of amino acid residues to the total binding energy of the ganoderic acid DM(A) complex; Figure 13 The contribution of amino acid residues to the total binding energy of the ganoderic acid A(B) complex; Figure 14 The contribution of amino acid residues to the total binding energy of the ganoderic acid B(C) complex; Figure 15 IC50 for three inhibitors and a positive control 50 Value comparison chart; Figure 16 The isosurface plot of amIGM for the weak interactions between the three triterpenoids and 7BW1. Detailed Implementation

[0020] To make the objectives, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0021] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0022] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0023] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0024] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0025] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application should be determined by the protection scope of the claims.

[0026] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0027] Example 1 To address the aforementioned problems, this invention provides a method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors, such as... Figure 1 As shown, it includes: S1 first acquires the three-dimensional structural data of 5α-reductase and preprocesses it to obtain the target protein structure suitable for subsequent molecular docking analysis. The three-dimensional structural data of 5α-reductase can be obtained from the Protein Structure Database (PDB), preferably its crystal structure data (PDB ID 7BW1). Since the raw protein structure downloaded directly from the database usually contains water molecules, endogenous ligands, and other non-target impurity molecules introduced during crystallization, direct use in subsequent docking calculations can easily interfere with active pocket recognition and ligand binding mode analysis. Therefore, the crystal structure must first be preprocessed.

[0028] In some embodiments, PyMOL software can be used to clean the 5α-reductase crystal structure, specifically by deleting water molecules, the endogenous ligand NADPH, and impurity molecules from the protein structure. Removing water molecules and non-target ligands helps eliminate the influence of non-specific interactions on subsequent calculation results, allowing the subsequent screening process to focus more on the actual binding between candidate compounds and the 5α-reductase active region. For locally missing structures in the crystal structure, especially missing amino acid side chains, further completion processing can be performed to improve the integrity and rationality of the target protein's three-dimensional structure.

[0029] After structural cleaning and missing component completion, the resulting protein structure undergoes energy minimization processing to eliminate potential localized unreasonable bond lengths, bond angles, and steric hindrance in the original crystal structure, thereby stabilizing the protein conformation. In this embodiment, the CHARMM force field is used to perform energy minimization calculations on the pretreated 5α-reductase structure, and the energy gradient convergence criterion is set to be no higher than 0.01 kcal / (mol·Å). In this embodiment, the energy gradient is further optimized to converge to 0.005 kcal / (mol·Å) to ensure that the target protein reaches a relatively stable low-energy conformational state. Through the above processing, a pretreated target protein structure suitable for subsequent molecular docking and kinetic simulation analysis can be obtained.

[0030] After obtaining a stable target protein structure, the active pocket region of 5α-reductase was further identified. The active pocket region refers to the binding cavity region on the 5α-reductase that can accommodate candidate compounds and influence their activity. The pocket center coordinates (X: -33.183, Y: 13.039, Z: 29.425) were determined using pocket identification tools (spdbv or SiteMap) after dehydration, ligand removal, and energy minimization of the 7BW1 protein structure. Specifically, the virtual screening parameters were specifically optimized based on the membrane protein characteristics and catalytic mechanism of 5α-reductase: NADPH was removed to simulate a coenzyme-free open conformation, exposing covalent binding sites; the search radius was strictly limited to a cytoplasmic side region of 14 Å, and the inclusion of the subtype-specific residue Phe118 was mandatory; and a pocket sorting system based on the proportion of hydrophobic residues was established to exclude non-specific hydrophobic gaps within the membrane. The final coordinates of the active pocket center are (X: -33.183, Y: 13.039, Z: 29.425). These coordinates serve as the center of the molecular docking grid, defining the search area for candidate compounds. This allows docking calculations to focus on the potential functional binding sites of 5α-reductase, rather than performing an indiscriminate search across the entire protein surface, thus improving screening efficiency and the reliability of docking results. The grid size was further set to 56×48×64 to ensure complete coverage of the active pocket and its surrounding interaction area.

[0031] S2. Obtain the three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds, and optimize the conformation of the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. Specifically, in this embodiment, after preprocessing the 5α-reductase target protein structure, three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds are further obtained, and the conformation of each candidate compound is optimized to obtain a low-energy stable conformation suitable for subsequent molecular docking analysis. The three-dimensional structural data of the multiple Ganoderma lucidum triterpenoid candidate compounds can be obtained from a compound database; preferably, the three-dimensional structural data of the target compound can be downloaded from the PubChem database. In some embodiments, the candidate compounds include: 1. Ganoderic acid I; 2. Ganoderma lucidum C; 3. Ganoderic acid C2; 4. Ganoderma lucidum N; 5. Ganoderic acid C6; 6. Ganoderic acid G; 7. Ganoderic acid B; 8. Ganoderic acid N; 9. Ganoderic acid B; 10. Ganoderic acid H; 11. Ganoderma lucidum E; 12. Ganoderic acid A. M1; 13, Ganoderic acid A; 14, Ganoderic acid K; 15, Ganoderic acid B; 16, Ganoderic acid A; 17, Ganoderic acid H; 18, Dehydroganoderic acid A; 19, Deacetylated Ganoderic acid F; 20, Ganoderic acid A; 21, Ganoderic acid D2; 22, Ganoderic acid D; 23, Ganoderic acid C1; 24, Ganoderic acid D; 25, Ganoderic acid F; 26, Ganoderic acid J; 27, Tanshinone E; 28, Ganoderic ketone triol; 29, Ganoderic acid DM; 30, Ganoderic acid TR; a total of 30 Ganoderma triterpenoid compounds. By uniformly collecting the above compounds, a candidate compound library can be constructed for subsequent virtual screening.

[0032] Since the three-dimensional structures of compounds obtained directly from databases are usually only initial conformations, they may contain inadequate local configurations, unreasonable bond angles and dihedral angles, and unstable hydrogen atom arrangements. Directly using these for molecular docking analysis can easily affect the accuracy of the docking results. Therefore, in this embodiment, the three-dimensional structures of each candidate compound need to be conformationally optimized to achieve a low-energy conformation that more closely approximates the true stable state, thereby improving the reliability of subsequent interaction analysis between the candidate compounds and the target protein's active pocket.

[0033] In some embodiments, the MMFF94 force field is used to optimize the structure of candidate compounds. MMFF94 is a force field specifically developed for drug molecules. Its parameter system is fitted based on a large amount of experimental data from steroidal drugs and small organic molecules, and it highly matches the structural characteristics of 5α-reductase inhibitors, such as the steroidal core, multi-chiral center, high hydrophobicity, and halogen substitution. Compared with other force fields, MMFF94 can more accurately predict the lowest energy conformation of compounds, strictly maintain the chiral center configuration, and quantitatively describe hydrophobic interactions, thereby significantly improving the accuracy of subsequent virtual screening. During the optimization process, the bond angles, dihedral angles, and hydrogen atom arrangements of the compounds can be adjusted, and the total energy of the compounds can be continuously reduced through iterative calculations until a preset energy convergence condition is reached. Preferably, the energy gradient needs to be controlled to converge to no higher than 0.01 kcal / (mol·Å) to obtain the corresponding low-energy stable conformation. Through the above optimization steps, unreasonable configurations in the initial structure of candidate compounds can be eliminated, making the obtained conformations more suitable for conformation search and binding mode analysis in subsequent molecular docking.

[0034] In this embodiment, the structures of the 30 Ganoderma lucidum triterpenoid candidate compounds were optimized, and the dihedral angles of each compound were adjusted to achieve the lowest stable energy. For example, the optimized energy of ganoderic acid DM was -11.19 kcal / mol, ganoderic acid A was -10.68 kcal / mol, and ganoderic acid B was -9.487 kcal / mol, indicating that the above compounds all formed relatively stable low-energy conformations after optimization. It should be noted that the above energy values ​​are only the optimization results for some representative compounds. Those skilled in the art will understand that the other candidate compounds can also undergo conformation optimization in the same manner to obtain their respective stable conformations.

[0035] After conformation optimization, the low-energy stable conformations of each candidate compound can be further saved as a structural file format suitable for molecular docking software to recognize, preferably in PDBQT format, so that they can be directly imported into the docking program for processing in subsequent molecular docking steps.

[0036] S3. The low-energy stable conformations of each candidate compound are molecularly docked with the pretreated 5α-reductase active pocket to generate docking complexes between the candidate compound and 5α-reductase. The candidate compounds are then screened based on their binding energy and interaction modes to obtain at least one candidate inhibitor. Specifically, in this embodiment, after obtaining the pretreated target protein structure of 5α-reductase and the low-energy stable conformations of various Ganoderma lucidum triterpenoid candidate compounds, each candidate compound is further molecularly docked with the active pocket region of the 5α-reductase to generate docking complexes between the candidate compounds and 5α-reductase. Based on binding energy and interaction modes, the candidate compounds are preliminarily screened to obtain at least one candidate inhibitor. This step enables rapid screening of target molecules with strong binding ability and reasonable binding modes from multiple candidate compounds in a short time, providing candidate molecules for subsequent stability analysis.

[0037] In some embodiments, the pretreated 5α-reductase structure and the low-energy stable conformations of each candidate compound can be imported into molecular docking software for docking calculations, preferably using AutoDock Vina software as the molecular docking platform. During molecular docking, a grid box is set with the coordinates of the center of the 5α-reductase active pocket determined above as the origin to limit the search space of the candidate compounds. In some embodiments, corresponding rotational degrees of freedom can be set according to the structural characteristics of each candidate compound. Specifically, based on the shape complementarity of the deep hydrophobic pocket of 5α-reductase and the rigid tetracyclic triterpenoid core structure of ganoderic acid compounds, a three-level rotational degree of freedom is established: the absolutely rigid intracyclic bonds and double bonds of the core are completely locked, the semi-flexible bonds connecting the core and side chains are restricted to a rotation range of ±30° to ±45°, and only the terminal carboxyl and hydroxyl groups that form hydrogen bonds with the catalytic residues are set to be fully flexible. For ganoderic acid DM and ganoderic acid B, five core phase bonds were locked, the rotation angle of three side chain bonds was limited to ±45°, and four terminal group bonds were released. For ganoderic acid enoic acid A, since its C17 side chain contains a C20-C22 double bond, the rotation angle of the semi-flexible bond was further tightened to ±30°. These data settings effectively filtered out unreasonable conformations with side chain shifts. The docking procedure was then initiated. Through the molecular docking calculations described above, multiple candidate docking complex conformations were generated for each candidate compound. Preferably, 10 optimal docking conformations were generated for each candidate compound. The evaluation of the optimal docking conformations was based on the top 10 outputs of the AutoDockVina docking software, using its built-in empirical scoring function. The ranking criterion was the binding free energy of the conformations calculated by weighted summation. Subsequently, conformations with lower binding energies and more reasonable binding modes were selected from the multiple docking conformations corresponding to each candidate compound as representative docking results for subsequent evaluation and analysis. The final docking results for each compound are shown in Table 1.

[0038] Table 1: Docking results of each compound

[0039] It should be noted that in this embodiment, the initial screening of candidate compounds is not based solely on binding energy, but rather on a comprehensive evaluation that considers both binding energy and interaction patterns, particularly hydrogen bonding information between the candidate compound and key amino acid residues in the active pocket. This is because while binding energy alone can characterize the affinity between a candidate compound and the target protein to some extent, it cannot fully reflect the actual binding behavior between the ligand and the receptor. Some compounds, although having low binding energies, may rely primarily on hydrophobic stacking interactions, lacking specific hydrogen bonding interactions with key sites, thus easily forming non-specific bindings. Conversely, some compounds, while having a large number of hydrogen bonds, may have insufficient overall affinity if their overall binding energy is high, which is also detrimental to obtaining stable and reliable candidate complexes. Therefore, this embodiment employs a comprehensive evaluation method that uses binding energy as the core, superimposed with hydrogen bonding information, to simultaneously consider binding strength, binding specificity, and potential conformational stability. This makes the screening results closer to the actual binding situation under real physiological conditions, improving the success rate of subsequent screening. Specifically, the screening criteria in this embodiment are shown in Table 2.

[0040] Table 2: Initial screening conditions for compounds

[0041] Based on Table 2, the initial screening evaluation criteria are as follows: When the binding energy ΔG of the docking complex formed by the candidate compound and 5α-reductase is ≤ -7.5 kcal / mol, and it forms at least two hydrogen bonds with the key amino acid residues in the active pocket, it is judged as a strongly binding compound and given priority; when the binding energy satisfies -7.5 kcal / mol < ΔG < -6.0 kcal / mol, it is judged as a moderately binding compound and can be considered as a candidate; when the binding energy ΔG ≥ -6.0 kcal / mol, it is judged as a weakly binding compound and is eliminated. Through the above stratified screening rules, candidate compounds can be distinguished according to their binding ability and interaction quality, thereby improving the targeting and effectiveness of the initial screening step.

[0042] Based on the docking results in Table 1 and the compound screening criteria in Table 2, the molecular docking results of 30 Ganoderma lucidum triterpenoid candidate compounds showed that most compounds exhibited a certain binding ability, but there were significant differences in binding energy and the number of hydrogen bonds. Specifically, ganoderic acid DM had a binding energy of -11.19 kcal / mol and formed 4 hydrogen bonds with the target protein; ganoderic acid A had a binding energy of -10.68 kcal / mol and formed 3 key hydrogen bonds; and ganoderic acid B had a binding energy of -9.487 kcal / mol and formed 2 hydrogen bonds. These three compounds all met the initial screening criteria of binding energy below -7.5 kcal / mol and at least 2 hydrogen bonds, and therefore could be identified as candidate inhibitors. Specifically, as... Figures 4-9 As shown, Figure 4 The conformation of the molecular docking complex formed by ganoderic acid DM and 7BW1 is shown; Figure 5 A schematic diagram of the two-dimensional interaction between the ganoderic acid DM and 7BW1 complex is shown. Figure 6 The conformation of the molecular docking complex formed by ganoderic acid B and 7BW1 is shown; Figure 7 A schematic diagram of the two-dimensional interaction between the ganoderic acid B and the 7BW1 complex is shown. Figure 8 The conformation of the molecular docking complex formed by ganoderic acid A and 7BW1 is shown; Figure 9 A two-dimensional interaction diagram of the complex between ganoderic acid A and 7BW1 is shown; yellow represents the three inhibitors, purple represents the binding site of 7BW1, and green dashed lines represent hydrogen bonds. Figures 4-9 Intuitive explanation: All three candidate compounds can enter the active pocket of 5α reductase and form clear hydrogen bond interactions with the binding site, thus possessing the structural basis to enter the subsequent screening as candidate inhibitors. Combining the data in the table above and the images in the figure, it can be seen that ganoderic acid DM, ganoderic acid A, and ganoderic acid B form 4, 3, and 2 hydrogen bonds, respectively, and the binding energies are all low.

[0043] In this embodiment, the top three compounds in the ranking are preferred as candidate inhibitors because virtual screening typically generates multiple candidate molecules. Including all candidate molecules in subsequent analysis or experimental verification would be labor-intensive, costly, and time-consuming. The top three compounds with lower binding energies and more hydrogen bonding interactions can well represent the optimal binding structures screened by this method. Therefore, the effectiveness and practicality of the screening indicators and process of this invention in rapidly screening highly active candidate molecules can be demonstrated through these top three candidate compounds. Through the above steps, molecular docking simulation and preliminary screening of multiple Ganoderma lucidum triterpenoid candidate compounds were completed, and candidate inhibitors that can be used for subsequent kinetic stability analysis were obtained.

[0044] S4. Perform molecular dynamics simulation on the docking complex corresponding to the candidate inhibitor to obtain at least one of the following kinetic parameters: root mean square deviation, root mean square fluctuation, and binding free energy of the complex, and determine the target inhibitor that has a stable binding effect with 5α reductase based on the kinetic parameters.

[0045] Specifically, compared to molecular docking, molecular dynamics simulations can continuously track the conformational changes of the complex over time, thus more realistically reflecting the interaction state between the candidate compound and the target protein under near-physiological conditions. Molecular dynamics simulations can be performed using GROMACS software, preferably GROMACS 2024.2. During the simulation, the protein component can be parameterized using the amber14sb_parmbsc1.ff force field, the solvent environment preferably uses the tip3p water model, and the ligand topology corresponding to the candidate inhibitor can be constructed using GAFF2 force field parameters. When constructing the simulation system, the docking complex can be placed in a solvent box, and the minimum distance between the box boundary and the outermost atoms of the system can be set to 1.0 nm to avoid unrealistic interactions between mirror images of the system under periodic boundary conditions. Simultaneously, the complex system can be simulated at 298.15 K, 1 atmosphere, and physiological saline concentration to make the results closer to the actual physiological environment.

[0046] After constructing the solvation system, energy minimization, system equilibrium, and formal kinetic simulations can be performed sequentially to obtain the conformational evolution trajectory of the complex under dynamic conditions. Specifically, energy minimization can be performed on the solvation system first to eliminate local spatial conflicts and unreasonable contacts in the initial system; in this embodiment, the energy minimization parameter emtol is preferably set to 100.0 kJ·mol. -1 ·nm -1 Subsequently, the protein atoms can be subjected to restricted kinetic equilibrium treatment to gradually adapt the solvent environment and ion distribution to the complex system. The preferred equilibrium time is 300 ps with a time step of 1 fs. After the system reaches equilibrium, a formal kinetic simulation is performed, preferably with a simulation time of 100 ns and a time step of 2 fs. During the simulation, Coulomb interactions can be calculated using the PME method, with a Coulomb cutoff radius set to 1.0 nm; van der Waals interactions can be calculated using a truncation method, with a van der Waals cutoff radius also set to 1.0 nm; the pressure coupling algorithm preferably uses the Parrinello-Rahman algorithm. Through these settings, the conformational change trajectory of the candidate inhibitor-5α reductase complex over a longer timescale can be obtained.

[0047] After obtaining the conformational evolution trajectory, the simulated trajectory can be processed to obtain kinetic parameters characterizing the binding stability of the candidate inhibitor and 5α-reductase complex, and the binding free energy and residue energy decomposition results between the candidate inhibitor and 5α-reductase can be further calculated. Specifically, the root mean square deviation (RMSD) is preferably calculated by measuring the coordinate deviation of the protein backbone atoms relative to the initial reference conformation to characterize the overall conformational stability of the complex; the root mean square fluctuation (RMSF) is preferably calculated by measuring the Cα atom fluctuation of each amino acid residue to characterize the local flexibility of residues around the binding site; the radius of gyration (Rg) is preferably calculated for the entire complex or the entire protein atoms to characterize the compactness of the system conformation; the number of hydrogen bonds is preferably counted frame-by-frame between the candidate inhibitor and the key residues in the 5α-reductase active pocket to characterize the persistence of their interaction; and the binding free energy is used to reflect the thermodynamic advantage of the binding between the candidate inhibitor and 5α-reductase.

[0048] In some embodiments, criteria for determining the binding stability of the complex can be established based on the aforementioned kinetic parameters. Preferably, when the RMSD of the complex is stable within the range of 0.2-0.6 nm, the overall conformation of the complex is considered relatively stable. In this embodiment, the upper limit of RMSD is relaxed to 0.6 nm to accommodate the natural oscillation of the transmembrane helix. When the RMSF is below 0.2 nm, the movement of the relevant amino acid residues is considered relatively smooth, and the local binding environment remains stable. The RMSF of the active pocket residues is strictly limited to below 0.2 nm to ensure shape complementarity. When the complex forms two or more hydrogen bonds during the simulation, it is considered that there is a good and sustained interaction between the candidate inhibitor and the active pocket. At least two hydrogen bonds are required to compensate for the hydrogen bonds in the hydrophobic binding mode. The deficiency of insufficient contribution; when the Rg value does not show obvious abnormal fluctuations, it can be considered that the overall conformation of the complex has not shown obvious loosening or collapse. Here, abnormal fluctuations refer to the fact that the value of the radius of gyration is always stable, the overall fluctuation amplitude does not exceed 5% of the average value, and the overall change curve remains basically horizontal, without a trend of continuous increase or decrease, and the change per nanosecond does not exceed 0.001 nanometers. This standard can accurately distinguish between normal slight shaking of the protein and abnormal situations such as protein dispersion and excessive contraction. When the binding free energy calculated by the MM-PBSA method is lower than -20 kcal / mol, it can be considered that the candidate inhibitor has a relatively stable binding effect with 5α reductase. Based on one or more of the above indicators, it can be determined whether the corresponding candidate compound can be used as a target candidate inhibitor with a stable binding effect with 5α reductase. The above data setting standards are not only applicable to ganoderic acid DM, ganoderic acid B, and ganoderic acid enoic acid A in this example, but also applicable to all complexes of 5α reductase subtypes and steroid / steroidal skeleton inhibitors.

[0049] In this embodiment, the complexes corresponding to the three candidate inhibitors obtained through molecular docking screening were subjected to the aforementioned molecular dynamics simulation analysis. The results showed that the RMSD of all three complexes was stable within the range of 0.2-0.6 nm, the RMSF values ​​were all below 0.13 nm, the Rg values ​​fluctuated between 1.90-2.04 nm, and the number of hydrogen bonds remained between 2 and 6, indicating that the three candidate inhibitors could maintain a relatively stable conformational state after binding to 5α-reductase. Furthermore, the binding free energies of the three compounds, calculated using the MM-PBSA method, were: ganoderic acid DM -52.16 kcal / mol, ganoderic acid A -41.4 kcal / mol, and ganoderic acid B -23.42 kcal / mol, all below the stable binding threshold of -20 kcal / mol. Therefore, it can be determined that all three candidate compounds have a stable binding effect with 5α-reductase and can be identified as target candidate inhibitors.

[0050] like Figure 10 As shown, it contains four subplots, which are graphs showing the changes in RMSD, RMSF, Rg, and hydrogen bond number of the three inhibitors in the 7BW1 complex.

[0051] Figure 10 A represents the RMSD changes of the three complexes in a 100 ns kinetic simulation. As can be seen from the figure, all three curves are stable in the range of 0.2-0.6 nm, indicating that the complexes formed by the three candidate compounds and 7BW1 did not show obvious dissociation or large conformational drift during the simulation, indicating that the overall stability of the complexes is good.

[0052] Figure 10 B represents the RMSF changes of the three complexes in a 100 ns kinetic simulation. As can be seen from the figure, the RMSF of the binding site residues of the three complexes are all below 0.13 nm, indicating that the key residues near the active pocket fluctuate little in the simulation, and the binding region does not show obvious loosening or violent oscillation, indicating that the local binding environment is stable.

[0053] Figure 10 C represents the Rg change of the three complexes in a 100 ns kinetic simulation. As can be seen from the figure, the fluctuation range is controlled between 1.90 and 2.04 nm, indicating that the protein or complex as a whole maintains a relatively stable compactness without obvious collapse or loosening, indicating that the overall conformation of the system is compact and stable.

[0054] Figure 10D represents the change in the number of hydrogen bonds of the three complexes during the 100 ns kinetic simulation. As can be seen from the figure, the number of hydrogen bonds of the three complexes remains between 3 and 6, indicating that the three candidate compounds and 7BW1 maintain a significant and stable hydrogen bond relationship throughout the entire dynamic process. This is not an accidental instantaneous binding, indicating that the binding effect of the complexes is continuous.

[0055] like Figure 11 As shown, the 3D and 2D plots of the Gibbs free energies of the complexes formed by the three candidate compounds with 7BW1 are presented. Figure 11 As can be seen, it mainly stays in a dominant low-energy region, rather than drifting randomly between multiple conformational states of varying levels. This proves that all three complexes have relatively clear and stable low-energy binding conformational basins, which supports the stability conclusions of RMSD / RMSF / Rg mentioned above from the perspective of free energy.

[0056] In this embodiment, to clarify the key binding sites between the candidate inhibitor and 5α-reductase, the complexes obtained from molecular dynamics simulations were further analyzed for binding free energy and residue energy decomposition. Specifically, the gmx_MMPBSA program was used to calculate the binding free energy between the candidate inhibitor and 5α-reductase, and the contribution of each amino acid residue to the total binding energy was statistically analyzed to identify the key residues in each complex that significantly contribute to ligand binding. The analysis results are as follows: Figure 12 , Figure 13 , Figure 14 As shown, for the ganoderic acid DM-7BW1 complex, key residues with significant beneficial contributions include Arg227, Tyr107, Phe223, Phe118, Leu20, Lys29, and Arg94; for the ganoderic acid A-7BW1 complex, key residues with significant beneficial contributions include Arg114, Phe118, Phe223, Ser31, Arg94, and Trp53; and for the ganoderic acid B-7BW1 complex, key residues with significant beneficial contributions include Arg94, Arg171, Asn102, Trp201, Leu224, and Leu167. These results indicate that the binding of different candidate inhibitors to 5α-reductase is not random, but depends on favorable interactions formed by several key amino acid residues within the active pocket, thus providing a site basis for stable binding between candidate inhibitors and target proteins.

[0057] Through the above steps, the molecular dynamics simulation verification of the docking complex corresponding to the candidate inhibitor was completed. This not only allows for dynamic supplementation and verification of the static screening results obtained from molecular docking, but also enables a comprehensive evaluation of the candidate compounds from multiple dimensions such as conformational stability, local fluctuation characteristics, interaction persistence, and thermodynamic binding trend, thereby improving the accuracy and reliability of the screening results for the target candidate inhibitor.

[0058] In this embodiment, to further verify the actual inhibitory activity of the candidate compounds selected through molecular docking and molecular dynamics simulations against 5α-reductase, ganoderic acid DM, ganoderic acid B, and ganoderic acid A were selected as test compounds, with finasteride as a positive control. The inhibitory activity against 5α-reductase was detected by HPLC. During the experiment, each triterpenoid compound was prepared to a final concentration of 0.5 mM and added to a reaction system containing the 5α-reductase reaction substrate and enzyme system. The mixture was incubated at 37°C for 1 h to allow the test compounds to fully react with the enzyme system. After incubation, methanol was added to terminate the reaction. The substrate conversion in each reaction system was then detected by HPLC, and the inhibition rate of each candidate compound against 5α-reductase was calculated accordingly.

[0059] like Figure 15 As shown, the experimental results indicate that ganoderic acid DM, ganoderic acid B, and ganoderic acid A all exhibited significant inhibitory activity against 5α-reductase. Specifically, ganoderic acid DM showed an inhibition rate of 62.43%, ganoderic acid B 43.68%, and ganoderic acid A 38.23%. Furthermore, the inhibitory effect of ganoderic acid DM was superior to that of the positive control finasteride. These results demonstrate that the three candidate compounds obtained through the aforementioned virtual screening process all exhibited good 5α-reductase inhibitory activity in in vitro enzyme activity experiments, thus confirming that all three candidate compounds are effective 5α-reductase inhibitors.

[0060] Example 2 To confirm the good reproducibility and stability of the inhibitory activities of ganoderic acid DM, ganoderic acid B, and ganoderic acid A obtained in Example 1 against 5α-reductase, three parallel replicate experiments were further performed in this example. The method of the replicate experiments was the same as the in vitro enzyme activity verification steps in Example 1, with finasteride as a positive control, the same concentration gradient and reaction conditions, and three replicates for each experiment to calculate the average inhibition rate and relative standard deviation (RSD) of each compound.

[0061] Repeated experiments showed that the inhibition rates of 5α-reductase by ganoderic acid DM were 59.14%, 61.49%, and 62.84% in three measurements, with an average of 61.16% and an RSD of 1.87%; the inhibition rates by ganoderic acid B were 42.96%, 39.41%, and 43.09% in three measurements, with an average of 41.82% and an RSD of 2.08%; and the inhibition rates by ganoderic acid A were 35.53%, 37.64%, and 36.04% in three measurements, with an average of 36.40% and an RSD of 1.10%. Since the RSDs of all three compounds were less than 3%, their inhibitory activity against 5α-reductase exhibited good repeatability and experimental stability, further demonstrating that the three candidate compounds screened were reliable 5α-reductase inhibitors.

[0062] Furthermore, to further verify the binding stability between the three candidate compounds and 5α-reductase at the structural level, supplementary analysis of the resulting complex trajectories was performed after completing the molecular dynamics simulation. Specifically, the simulation continued for 1 ns under NVT ensemble conditions, and a total of 1001 frames of conformational data were obtained by saving one frame every 1 ps. During the simulation, the ligand portion was frozen, and then amIGM analysis was performed using Multiwfn software. The analysis results were visualized using VMD software, as shown in the figure. Figure 16 As shown in the figure, the blue isosurface regions represent strong attractive interactions dominated by strong electrostatic effects, corresponding to sites of strong polar interactions such as hydrogen bonds; the green isosurface regions represent weak attractive interactions mainly dominated by van der Waals forces; and the red regions represent steric hindrance or strong repulsive interactions within the system.

[0063] The analysis results showed that in the ganoderic acid DM-7BW1 complex system, obvious blue isosurface regions were observed between the ligand and protein binding pocket residues Lys29, Tyr107, Arg114, and Arg227, corresponding to strong hydrogen bonding interactions. Hydrogen bonding accounted for the highest proportion of all non-covalent interactions in this system. In the ganoderic acid A-7BW1 complex system, the binding interface was predominantly green isosurfaces, but blue interaction regions surrounded by green isosurfaces were observed at the corresponding positions of Ser31, Trp53, and Arg114, indicating that stable hydrogen bonding was formed between the compound and these residues. For the ganoderic acid B-7BW1 complex system, although the isosurface coverage of the binding interface was relatively small compared to the other three complexes, blue isosurfaces corresponding to hydrogen bonding were still observed at Arg94 and Arg171 residues, while the remaining areas were mainly green isosurfaces.

[0064] The non-covalent interaction characteristics obtained from the amIGM analysis are highly consistent with the binding modes and interaction energy decomposition results obtained from the aforementioned molecular dynamics simulations. This further indicates that ganoderic acid DM, ganoderic acid B, and ganoderic acid A can all form real, stable, and differentiated binding modes with 5α reductase, thus providing a structural basis for their in vitro enzyme inhibitory activity. It also further verifies the reliability of the aforementioned molecular docking and molecular dynamics screening results.

[0065] Example 3 Please see Figure 2 A Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device, comprising: Preprocessing unit 1 is used to acquire the three-dimensional structural data of 5α reductase, and to preprocess the three-dimensional structural data to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. Optimization unit 2 is used to acquire three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds and to perform conformational optimization on the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. Docking unit 3 is used to perform molecular docking of the low-energy stable conformation of each candidate compound with the pretreated 5α reductase active pocket to generate docking complexes between the candidate compound and 5α reductase, and to perform preliminary screening of each candidate compound based on binding energy and interaction mode to obtain at least one candidate inhibitor. Simulation unit 4 is used to perform molecular dynamics simulation on the docking complex corresponding to the candidate inhibitor, obtain at least one of the root mean square deviation, root mean square fluctuation and binding free energy of the complex, and determine the target inhibitor with stable binding to 5α reductase based on the kinetic parameters.

[0066] Specific limitations regarding the Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device can be found in the limitations of the Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening method described above, and will not be repeated here. Each module in the aforementioned Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0067] Those skilled in the art will understand that Figure 2The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the present application. The specific Ganoderma lucidum triterpenoid 5α reductase inhibitor screening device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0068] Example 4 A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors as described in Example 1.

[0069] Example 5 In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. When the computer program is executed by the processor, it implements a method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors.

[0070] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0071] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps: including: S1. Obtain the three-dimensional structural data of 5α reductase, and preprocess the three-dimensional structural data to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. S2. Obtain the three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds, and optimize the conformation of the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. S3. The low-energy stable conformations of each candidate compound are molecularly docked with the pretreated 5α-reductase active pocket to generate docking complexes between the candidate compound and 5α-reductase. The candidate compounds are then screened based on their binding energy and interaction modes to obtain at least one candidate inhibitor. S4. Perform molecular dynamics simulation on the docking complex corresponding to the candidate inhibitor to obtain at least one of the following kinetic parameters: root mean square deviation, root mean square fluctuation, and binding free energy of the complex, and determine the target inhibitor that has a stable binding effect with 5α reductase based on the kinetic parameters.

[0072] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors, characterized in that, Includes the following steps: The three-dimensional structural data of 5α reductase were obtained and preprocessed to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. Three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds were obtained, and the conformation of each candidate compound was optimized to obtain the corresponding low-energy stable conformation. The low-energy stable conformations of each candidate compound were molecularly docked with the pretreated 5α-reductase active pocket to generate docking complexes between the candidate compound and 5α-reductase. The candidate compounds were then screened based on their binding energy and interaction modes to obtain at least one candidate inhibitor. Molecular dynamics simulations were performed on the docking complexes corresponding to the candidate inhibitors to obtain at least one of the following kinetic parameters: root mean square deviation, root mean square fluctuation, and binding free energy. Based on the kinetic parameters, the target inhibitors that have a stable binding effect with 5α reductase were determined.

2. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 1, characterized in that, The acquisition of the three-dimensional structural data of 5α reductase includes: acquiring the crystal structure data of 5α reductase from a protein structure database; The preprocessing of the three-dimensional structural data includes: removing water molecules, ligand molecules and impurity molecules from the crystal structure, completing the missing amino acid side chain structure, and performing energy minimization processing to obtain the preprocessed target protein structure. The determination of the active pocket region of the 5α reductase includes: identifying the location of the active pocket based on the pretreated target protein structure, and determining the pocket center coordinates and pocket coverage for subsequent molecular docking.

3. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 2, characterized in that, The acquisition of three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds includes: acquiring the three-dimensional structures of multiple Ganoderma lucidum triterpenoid compounds from a compound database; The conformation optimization of the three-dimensional structure of each candidate compound includes: using a molecular force field to optimize the bond angles, dihedral angles and hydrogen atom arrangement of the candidate compounds until a preset energy convergence condition is reached to obtain the low-energy stable conformation.

4. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 1, characterized in that, The step of molecularly docking the low-energy stable conformations of each candidate compound with the pretreated 5α-reductase activity pocket includes: A molecular docking grid box is constructed with the active pocket region as the center, and conformation search and spatial matching calculations are performed on each candidate compound to generate multiple candidate docking complex conformations. The preliminary screening of candidate compounds based on binding energy and interaction modes includes: using the binding energy of the docking complex formed by the candidate compound and 5α reductase as a screening index, and combining the hydrogen bonding information between the candidate compound and key amino acid residues in the active pocket for comprehensive evaluation.

5. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 4, characterized in that, The initial screening includes: selecting candidate compounds with binding energies below a preset threshold and forming at least a preset number of hydrogen bonds with key amino acid residues in the active pocket as candidate inhibitors; The candidate compounds were ranked according to their binding energy and hydrogen bonding, and at least one of the top-ranked candidate compounds was selected as a candidate inhibitor for molecular dynamics simulation.

6. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 1, characterized in that, The molecular dynamics simulation of the docking complex corresponding to the candidate inhibitor includes: A solvation system containing the docking complex was constructed, and the solvation system was subjected to energy minimization, system equilibrium and formal kinetic simulation in sequence to obtain the conformational evolution trajectory of the complex under dynamic conditions. Based on the conformational evolution trajectory, at least one of the following kinetic parameters of the complex is calculated: root mean square deviation, root mean square fluctuation, cyclotron radius, number of hydrogen bonds, and binding free energy.

7. The method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors according to claim 1, characterized in that, The determination of target candidate inhibitors with stable binding activity to 5α-reductase based on the aforementioned kinetic parameters includes: When the root mean square deviation of the complex is within a preset fluctuation range, the root mean square fluctuation is lower than a preset threshold, the gyration radius has no obvious abnormal fluctuation, the number of hydrogen bonds meets the preset stability requirements, and the binding free energy is lower than a preset threshold, the corresponding candidate compound is determined to have a stable binding effect with 5α reductase, and the corresponding candidate compound is output as the target candidate inhibitor.

8. A screening device for Ganoderma lucidum triterpenoid 5α-reductase inhibitors, characterized in that, The Ganoderma lucidum triterpenoid 5α-reductase inhibitor screening device includes: A preprocessing unit is used to acquire the three-dimensional structural data of 5α reductase, and to preprocess the three-dimensional structural data to remove non-target molecules, complete missing structures, minimize energy, and determine the active pocket region of the 5α reductase. An optimization unit is used to acquire three-dimensional structural data of multiple Ganoderma lucidum triterpenoid candidate compounds and to perform conformational optimization on the three-dimensional structure of each candidate compound to obtain the corresponding low-energy stable conformation. The docking unit is used to perform molecular docking of the low-energy stable conformation of each candidate compound with the pretreated 5α reductase active pocket to generate docking complexes between the candidate compound and 5α reductase, and to perform preliminary screening of each candidate compound based on binding energy and interaction mode to obtain at least one candidate inhibitor. The simulation unit is used to perform molecular dynamics simulations on the docking complex corresponding to the candidate inhibitor, obtain at least one of the root mean square deviation, root mean square fluctuation and binding free energy of the complex, and determine the target inhibitor with stable binding to 5α reductase based on the kinetic parameters.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors as described in any one of claims 1-7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method for screening Ganoderma lucidum triterpenoid 5α-reductase inhibitors as described in any one of claims 1-7.

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