A method and system for screening female reproductive drugs in the field of reproduction

Abstract

This invention relates to the field of molecular docking technology, and discloses a method and system for screening female reproductive drugs in reproductive medicine. The method includes: constructing a female reproductive drug screening platform for target female users; defining a data parsing algorithm for the user interface; parsing reproductive examination data and reproductive needs into physiological parameters of the target user; mapping physiological states to relevant target proteins; retrieving molecular data of relevant target proteins; and matching ligand molecules of relevant target proteins. The method also includes: culturing target cells in vitro; adding ligand molecules to the in vitro cultured tissue; detecting cell activity, gene expression, and protein expression in the ligand test tissue; analyzing the enhancing effect of the ligand molecules on the ligand test tissue; calculating the gain coefficient of the enhancing effect; screening the optimal ligand molecules; and determining the female reproductive drugs for the target female users. This invention can improve the efficiency and accuracy of female reproductive drug screening in reproductive medicine.

Description

Technical Field

[0001] This invention relates to the field of molecular docking technology, and in particular to a method and system for screening female reproductive drugs in the field of reproductive medicine. Background Technology

[0002] Female reproductive drugs refer to a class of drugs specifically used for the female reproductive system and related diseases, such as hormonal drugs, ovulation-inducing drugs, and contraceptive drugs. Since different women may respond differently to drugs, screening can help identify which drugs may cause serious side effects, thereby reducing unnecessary risks.

[0003] Currently, the main method for screening female reproductive drugs is high-throughput screening. This method mainly uses automated equipment to rapidly screen a large number of compounds in order to find compounds with biological activity. However, because this method ignores compounds with complex mechanisms of action and cannot fully simulate the biological environment in the body, it is impossible to predict the actual behavior of the drug in the body, thus making the drug screening less accurate. Summary of the Invention

[0004] This invention provides a method and system for screening female reproductive drugs in reproductive medicine, the main purpose of which is to improve the efficiency and accuracy of screening female reproductive drugs in reproductive medicine.

[0005] To achieve the above objectives, the present invention provides a method for screening female reproductive drugs in reproductive medicine, comprising:

[0006] Acquire reproductive examination data and reproductive needs of target female users, and construct a female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module.

[0007] Define a data parsing algorithm for the user port. Based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into physiological parameters of the target user. Based on the physiological parameters, use the data processing module to analyze the physiological state of the target female user and map the physiological state to relevant target proteins. Define a retrieval algorithm for the chemical information database. Based on the chemical information database, use the retrieval algorithm to retrieve molecular data of the relevant target proteins. Define a task allocation algorithm for the molecular docking module. Based on the molecular data, use the task allocation algorithm to match ligand molecules of the relevant target proteins.

[0008] Based on the physiological state, target cells of the target female user are extracted, an in vitro culture environment for the target cells is constructed, and the target cells are cultured in vitro based on the in vitro culture environment to obtain in vitro cultured tissue. A physiological environment for the in vitro cultured tissue is constructed, and the ligand molecule is added to the in vitro cultured tissue based on the physiological environment to obtain ligand test tissue.

[0009] Cell activity, gene expression, and protein expression in the ligand test tissue are detected. Based on the cell activity, gene expression, and protein expression, the enhancing effect of the ligand molecule on the ligand test tissue is analyzed, and the gain coefficient of the enhancing effect is calculated. Based on the gain coefficient, the optimal ligand molecule is screened, and based on the optimal ligand molecule, the female reproductive medicine for the target female user is determined.

[0010] To address the above problems, the present invention also provides a female reproductive drug screening system, the system comprising:

[0011] The screening platform construction module is used to acquire the reproductive examination data and reproductive needs of target female users, and to construct a female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module.

[0012] The ligand molecule screening module is used to define the data parsing algorithm of the user port, and based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into the physiological parameters of the target user. Based on the physiological parameters, the data processing module analyzes the physiological state of the target female user and maps the physiological state to relevant target proteins. The module also defines a retrieval algorithm for the chemical information database, and uses the retrieval algorithm to retrieve molecular data of the relevant target proteins based on the chemical information database. Finally, the module defines a task allocation algorithm for the molecular docking module, and uses the task allocation algorithm to match ligand molecules of the relevant target proteins based on the molecular data.

[0013] The ligand testing module is used to extract target cells from the target female user according to the physiological state, construct an in vitro culture environment for the target cells, culture the target cells in vitro based on the in vitro culture environment to obtain in vitro cultured tissue, construct a physiological environment for the in vitro cultured tissue, and add the ligand molecule to the in vitro cultured tissue based on the physiological environment to obtain ligand testing tissue.

[0014] The drug screening module is used to detect cell activity, gene expression, and protein expression in the ligand test tissue. Based on the cell activity, gene expression, and protein expression, it analyzes the enhancing effect of the ligand molecule on the ligand test tissue and calculates the gain coefficient of the enhancing effect. Based on the gain coefficient, it screens the optimal ligand molecule and determines the female reproductive drug for the target female user.

[0015] This invention, through the construction of a female reproductive drug screening platform for the target female users, can provide more efficient, safe, and personalized services, thereby improving the overall level of women's reproductive health. Optionally, this invention, based on the data parsing algorithm, analyzes the reproductive examination data and reproductive needs into physiological parameters of the target users. By analyzing the trends of these physiological parameters, potential reproductive health problems can be predicted, enabling early intervention. This invention, by mapping the physiological states to relevant target proteins, can help to deeply understand the mechanisms of occurrence and development of physiological states, significantly improving the quality and efficiency of medical services. This invention, based on the molecular data, utilizes the task... The allocation algorithm for matching ligand molecules to relevant target proteins can handle large amounts of molecular and target data, support diverse screening strategies, and significantly improve the efficiency of ligand molecule screening, shorten the screening cycle, and quickly identify potential ligand candidates. In this embodiment, by adding the ligand molecules to in vitro cultured tissues based on the physiological environment, the resulting ligand test tissues can be used for personalized drug testing targeting specific female users' ligand responses, improving the accuracy of drug screening. Finally, by determining the optimal ligand molecules, this embodiment ensures the safety and efficacy of female reproductive drugs for the target female user while providing higher-quality drug options. Therefore, this invention can improve the efficiency and accuracy of female reproductive drug screening in reproductive medicine. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for screening female reproductive drugs in a reproductive medicine department, as provided in an embodiment of the present invention.

[0017] Figure 2 This is a functional block diagram of a female reproductive drug screening system provided in an embodiment of the present invention;

[0018] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0019] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0020] This application provides a method for screening female reproductive drugs in reproductive medicine. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0021] Reference Figure 1 The diagram shown is a schematic flowchart of a method for screening female reproductive drugs in a reproductive medicine department according to an embodiment of the present invention. In this embodiment, the method for screening female reproductive drugs in a reproductive medicine department includes:

[0022] S1. Obtain the reproductive examination data and reproductive needs of the target female users, and construct a female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module.

[0023] This invention provides personalized drug screening plans for each female user by acquiring their reproductive health examination data and reproductive needs, thereby improving the targeting and effectiveness of medications. The reproductive health examination data refers to medical examination results and data related to the health status of the female reproductive system, such as hormone level test data, ultrasound examination data, and genetic test data. Reproductive needs refer to a woman's specific goals and desires regarding reproductive health.

[0024] This invention, through the construction of a female reproductive drug screening platform for the target female users, can provide more efficient, safe, and personalized services, thereby improving the overall level of women's reproductive health. The female reproductive drug screening platform refers to a system specifically designed for women, which, based on their reproductive examination data and reproductive needs, utilizes information technology, data analysis, and bioinformatics tools to screen and recommend reproductive-related drugs suitable for their individual circumstances.

[0025] As an embodiment of the present invention, the construction of the female reproductive drug screening platform for the target female user includes:

[0026] Clearly define the platform's construction goals, platform functions, and service scope corresponding to the target female users;

[0027] Based on the construction goals, the platform functions, and the service scope, construct the access interface of the platform to be constructed;

[0028] Write the interface elements of the access interface, define the interactive behavior of the interface elements, and construct the user port of the platform to be built based on the interface elements, the access interface, and the interactive behavior.

[0029] Determine the data interface of the user port and construct a data cleaning module for the data interface;

[0030] Define a data feature extraction algorithm for the platform to be built, and construct a data analysis module for the data of the platform to be built based on the data interface, the data cleaning module, and the data feature extraction algorithm.

[0031] Construct a database of data for the platform to be constructed, and determine the mining objectives required for the database based on the construction objectives;

[0032] Based on the stated mining objective, target data is mined from a pre-defined public database, and the target data is populated into the database to obtain a chemical information database.

[0033] Determine the molecular docking software for the chemical information database, and construct the molecular docking module of the platform to be constructed based on the molecular docking software;

[0034] Based on the user port, the data processing module, the chemical information database, and the molecular docking module, a female reproductive drug screening platform for the target user is constructed.

[0035] The construction goal refers to the specific objectives and outcomes expected to be achieved by creating a female reproductive drug screening platform for target female users. The platform functions refer to the capabilities of the female reproductive drug screening platform in providing users with a series of operations and services. The service scope refers to the specific service content and coverage areas provided by the female reproductive drug screening platform. The access interface refers to the interface through which users interact with the female reproductive drug screening platform. The interface elements refer to the various visual and interactive components that constitute the access interface, such as text elements, input elements, buttons, and links. The interaction behavior refers to the interaction methods and response rules between users and the interface elements of the female reproductive drug screening platform, such as click events, input operations, drag-and-drop behavior, etc. The user port refers to the set of interactive interfaces and functions specifically designed for users within the female reproductive drug screening platform. The data interface refers to the software components within the female reproductive drug screening platform used for data exchange and communication. The data cleaning module refers to the software components within the female reproductive drug screening platform used to process and clean user-uploaded data. The data feature extraction algorithm refers to the computational methods used to process, interpret, and extract valuable information from data. The data analysis module refers to the part of the female reproductive drug screening platform specifically responsible for processing, interpreting, and extracting useful information from data. The database refers to the system used for storing, managing, and retrieving data within the female reproductive drug screening platform. The mining target refers to valuable information or knowledge extracted from a large amount of data. The pre-set public database refers to existing and publicly accessible data resources. The target data refers to the data that the female reproductive drug screening platform specifically focuses on and needs to collect during drug screening and analysis. The chemical information database refers to a database specifically used for storing, retrieving, and managing chemical information. The molecular docking software refers to a computational tool used to predict the optimal binding mode between two or more molecules (typically proteins and small molecule ligands). The molecular docking module refers to a component within the female reproductive drug screening platform specifically designed to perform molecular docking tasks.

[0036] Optionally, the access interface of the platform to be built, based on the construction goal, the platform functions, and the service scope, can be constructed using front-end development technology.

[0037] Optionally, the data feature extraction algorithm for the platform to be built can be defined using statistical analysis and deep learning.

[0038] S2. Define the data parsing algorithm for the user port. Based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into physiological parameters of the target user. Based on the physiological parameters, use the data processing module to analyze the physiological state of the target female user and map the physiological state to relevant target proteins. Define the retrieval algorithm for the chemical information database. Based on the chemical information database, use the retrieval algorithm to retrieve molecular data of the relevant target proteins. Define the task allocation algorithm for the molecular docking module. Based on the molecular data, use the task allocation algorithm to match ligand molecules of the relevant target proteins.

[0039] This invention, through defining a data parsing algorithm for the user port, can identify and eliminate invalid or inaccurate data, improving the overall quality of the dataset. It can quickly extract key information from large amounts of data, increasing the speed and efficiency of data processing. The data parsing algorithm refers to a specific program or instruction set specifically designed for processing and analyzing reproductive health examination data and reproductive needs information.

[0040] Alternatively, as an embodiment of the present invention, the data parsing algorithm for defining the user port can be defined using data analysis techniques.

[0041] This invention, through its data parsing algorithm, transforms reproductive health examination data and reproductive needs into physiological parameters for the target user. By analyzing trends in these physiological parameters, potential reproductive health problems can be predicted, enabling early intervention. These physiological parameters refer to a series of quantitative indicators extracted from the reproductive health examination data and reproductive needs.

[0042] As an embodiment of the present invention, the step of parsing the reproductive examination data and the reproductive needs into the physiological parameters of the target user based on the data parsing algorithm includes:

[0043] Extract experimental test data, menstrual cycle data, and imaging data from the reproductive health examination data;

[0044] Based on the data parsing algorithm, the experimental test data and the reproductive requirements are quantitatively analyzed to obtain hormone level parameters;

[0045] Image features are extracted from the image data, and the image features are analyzed to obtain reproductive organ parameters;

[0046] Periodic analysis of the menstrual cycle data yields the menstrual cycle length and menstrual regularity.

[0047] The physiological parameters of the target user are determined based on the hormone level parameters, reproductive organ parameters, menstrual cycle length, and menstrual regularity.

[0048] The experimental detection data refers to biochemical and biological indicators related to reproductive health obtained through laboratory testing methods. The menstrual cycle data refers to information related to a woman's menstrual cycle. The imaging data refers to image data related to the reproductive system obtained through medical imaging technology. The physiological characteristics refer to directly observable properties related to the human reproductive system and reproductive health. The hormone level parameters refer to hormone concentration indicators closely related to reproductive health and function, determined through laboratory testing. The image features refer to specific attributes in an image that can be quantified and analyzed. The reproductive organ parameters refer to specific quantitative indicators related to the structure and function of reproductive organs. The menstrual cycle length refers to the number of days from the first day of one menstrual cycle to the first day of the next menstrual cycle. The menstrual regularity refers to the regularity and predictability of a woman's menstrual cycle.

[0049] Optionally, the step of quantitatively analyzing the experimental test data according to the data parsing algorithm to obtain hormone level parameters can be achieved using chemiluminescent immunoassay.

[0050] This invention, through its embodiment, analyzes the physiological state of a target female user based on the aforementioned physiological parameters using the data processing module. This analysis provides a more accurate assessment of the target female user's health status and predicts potential health risks and their progression. The physiological state refers to the female user's overall health condition at a specific point in time.

[0051] Optionally, as an embodiment of the present invention, the analysis of the physiological state of the target female user based on the physiological parameters using the data processing module can be obtained through time series analysis.

[0052] This invention, by mapping physiological states to relevant target proteins, can help to gain a deeper understanding of the mechanisms by which physiological states occur and develop, significantly improving the quality and efficiency of medical services. The relevant target proteins refer to a class of proteins that play a key role in specific physiological processes.

[0053] As an embodiment of the present invention, mapping the physiological state to relevant target proteins includes:

[0054] Analyze the abnormal factors of the physiological state and extract the abnormal correlation data of the abnormal factors;

[0055] Based on the aforementioned abnormality-related data and preset normal state data, the physiological state is analyzed for differential expression using the following formula to obtain the differential analysis results:

[0056]

[0057] Where C represents the result of the difference analysis, This represents the mean of the outlier data related to anomalies. This represents the mean of normal data under normal conditions. This represents the variance of outlier-related data. N1 represents the normal data variance of the normal state data, N2 represents the number of abnormal data groups of the abnormal related data, and N2 represents the number of normal data groups of the normal state data.

[0058] The mapping pathway of the abnormal factor is determined, and the abnormal factor is mapped to the mapping pathway based on the difference analysis results to obtain the mapped abnormal factor;

[0059] Based on the mapping pathway, the mapping anomaly factor, the anomaly factor, and the physiological state, functional enrichment analysis is performed on the mapping pathway to obtain the functional enrichment probability:

[0060] Construct a protein-protein interaction network for the mapped anomalous factors, and analyze the location and function of anomalously expressed proteins of the mapped anomalous factors based on the functional enrichment probability using the protein-protein interaction network.

[0061] Based on the location and function of the abnormally expressed protein, the relevant target proteins of the mapped abnormal factor are determined.

[0062] The term "abnormal factor" refers to biomolecules that exhibit significant differences or abnormal changes compared to the normal state, as discovered in physiological state analysis. "Abnormal-related data" refers to datasets directly related to abnormal factors in the physiological state. "Preset normal state data" refers to data collected under a set of standard or reference conditions, representing a healthy or normal physiological functional state. "Difference analysis results" refers to the summary of significant differences obtained through statistical methods or other analytical tools when comparing two or more biological datasets (usually data from normal and abnormal states). "Mapping pathway" refers to the process of associating differentially expressed genes or proteins with the biological processes, pathways, or functions they participate in. "Mapped abnormal factors" refers to genes, proteins, or other biomolecules that exhibit abnormal expression compared to the normal state, identified through mapping analysis in bioinformatics analysis. "Functional enrichment probability" refers to the statistical significance of a specific biological function or pathway appearing in a given list of genes in bioinformatics analysis. "Protein-protein interaction network" refers to a complex interaction diagram formed between different proteins through physical contact or indirect interaction. "Abnormally expressed protein location" refers to the location within a cell or organism where a specific protein exhibits expression different from the normal state under abnormal physiological or pathological conditions. The role of anomalously expressed proteins refers to the biological function or effect produced by proteins under anomalous expression conditions.

[0063] Optionally, the mapping pathway for determining the abnormal factor can be determined by expression and RNA interference methods;

[0064] Optionally, the protein-protein interaction network for constructing the mapping aberration factor can be constructed using affinity purification mass spectrometry.

[0065] Optionally, the step of performing functional enrichment analysis on the mapping pathway based on the mapping abnormality factor, the abnormality factor, and the physiological state to obtain the functional enrichment probability includes:

[0066] Determine the total number of pathway factors for the mapped pathway and analyze the total number of factors for the physiological state;

[0067] Identify the number of anomalous factors of the anomalous factors, and determine the number of mapped anomalous factors of the mapped anomalous factors;

[0068] Based on the total number of factors in the pathway, the total number of factors, the number of anomalous factors, and the number of mapped anomalous factors, the functional enrichment probability of the mapped pathway is calculated using the following formula:

[0069]

[0070] Where G represents the functional enrichment probability, P represents the number of pathway factors corresponding to the mapping pathway, u represents the number of mapping abnormal factors of the mapping abnormal factors, Q represents the total number of factors corresponding to the physiological state, and q represents the number of abnormal factors of the abnormal factors.

[0071] The term "total factor count" refers to the total number of molecules (such as proteins, enzymes, transcription factors, small molecules, etc.) involved in a specific signal transduction pathway or biological metabolic pathway. The total factor count refers to the number of molecules (such as genes, proteins, metabolites, etc.) that participate in or influence the pathway under physiological conditions. The term "abnormal factor count" refers to the number of molecules (such as genes, proteins, metabolites, etc.) that exhibit abnormal changes under specific conditions. The term "mapped abnormal factor count" refers to the number of abnormal factors determined after mapping identified abnormal factors (such as genes, proteins, metabolites, etc.) to known biological pathways, networks, or functional modules.

[0072] This invention, through defining a retrieval algorithm for the chemical information database, can accurately identify and retrieve chemical information matching query conditions, reducing false positives and false negatives. The retrieval algorithm refers to a series of rules and calculation steps used to find and extract specific chemical data from the chemical information database.

[0073] As an embodiment of the present invention, the retrieval algorithm for the chemical information database includes:

[0074] Determine the initial search algorithm for the chemical information database, and analyze the objective function, search step size, and Hessian matrix of the initial search algorithm;

[0075] Determine the descent point and descent direction of the initial search algorithm, and based on the descent point, determine the number of searches for the initial search algorithm;

[0076] When the number of searches exceeds the search step size, the objective function will be iteratively updated to obtain an iterative objective function;

[0077] Calculate the search accuracy and convergence speed of the iterative objective function;

[0078] Construct a memory matrix for the iterative objective function, and map the search accuracy and the convergence speed to the memory matrix to obtain an accuracy memory matrix and a speed memory matrix;

[0079] Based on the precision memory matrix and the velocity memory matrix, the Hessian matrix is ​​updated using the following formula to obtain the updated Hessian matrix:

[0080]

[0081] Among them, S i+1 This indicates updating the Hessian matrix, Si Let v represent the Hessian matrix in the i-th iteration. i Let a represent the velocity memory matrix for the i-th iteration. i This represents the precision memory matrix for the i-th iteration. The velocity transpose of the velocity memory matrix in the i-th iteration. This represents the precision transpose of the precision memory matrix for the i-th iteration.

[0082] The descent direction is updated based on the updated Hessian matrix to obtain the updated descent direction;

[0083] The search count is updated based on the updated descent direction to obtain the updated search count;

[0084] When the number of update searches is less than the search step size, the iteration objective function is used as the update objective function;

[0085] Based on the updated objective function and the updated Hessian matrix, the initial search algorithm is updated to obtain the retrieval algorithm for the chemical information database.

[0086] The initial search algorithm refers to the algorithm used for preliminary searching in chemical information database retrieval. The objective function is a mathematical function that calculates the similarity between the query compound and compounds in the database. The search step size is a fixed search distance throughout the algorithm's execution. The Hessian matrix is ​​a square matrix composed of the second-order partial derivatives of a real-valued function. The descent point is the point where the objective function value decreases. The direction in which the algorithm moves from the current point along this direction reduces the objective function value. The number of searches refers to the number of times the algorithm attempts to improve the current solution. The iterative objective function is the function optimized in each iteration step. The search accuracy refers to the degree of precision achieved in finding the optimal solution or a solution that satisfies specific conditions. The convergence speed refers to how quickly a sufficiently good solution is found or a predetermined accuracy is achieved. The memory matrix is ​​a data structure used to store information or patterns learned by the algorithm during iteration. The accuracy memory matrix is ​​a matrix used to store information about the accuracy achieved by the algorithm during iteration. The velocity memory matrix is ​​a matrix used to store information related to the convergence speed of the algorithm during iteration. The updated Hessian matrix refers to the matrix after correction or recalculation during the iterative optimization process. The updated descent direction refers to the updated descent direction. The updated search count refers to the updated number of searches. The updated objective function refers to the function obtained after iteratively updating the objective function.

[0087] Optionally, the objective function, search step size, and Hessian matrix of the initial search algorithm can be analyzed using optimization algorithm analysis methods.

[0088] Optionally, the search accuracy and convergence speed of the iterative objective function can be calculated using optimality conditions and superlinear convergence methods.

[0089] This invention, through the retrieval algorithm based on the chemical information database, allows for the retrieval of molecular data of the relevant target proteins, which can be used for virtual screening and molecular docking, accelerating the discovery and screening process of lead compounds. Here, the molecular data refers to various chemical and biological information data related to the target proteins.

[0090] This invention, through defining a task allocation algorithm for the molecular docking module, ensures that each docking task receives sufficient computational resources, thereby improving the accuracy of molecular docking and enhancing the reliability of screening results. The task allocation algorithm refers to an algorithm for allocating molecular docking tasks in a parallel computing environment.

[0091] As an embodiment of the present invention, the task allocation algorithm for the molecular docking module includes:

[0092] Obtain the computational tasks of the molecular docking module, analyze the task characteristics of the computational tasks, and determine the priority of the computational tasks based on the task characteristics;

[0093] The computing nodes of the computing task are determined, and the node resources of the computing nodes are analyzed, wherein the node resources include node CPU, node memory, and node GPU.

[0094] The resource utilization rate of the node resources is monitored in real time, and a task allocation strategy for the computing tasks is constructed based on the resource utilization rate and the priority.

[0095] According to the task allocation strategy, the computing tasks are allocated to the computing nodes to obtain computing execution nodes;

[0096] Check the load status of the computing node, and based on the load status, construct a load feedback mechanism and a load adjustment mechanism for the computing node;

[0097] The task allocation algorithm for the molecular docking module is determined based on the task allocation strategy, the load feedback mechanism, and the load adjustment mechanism.

[0098] The computational tasks refer to the computational tasks required by the molecular docking module. Task characteristics refer to the specific attributes and features of the computational tasks during execution, such as computational complexity, time sensitivity, and resource requirements. Priority refers to the order in which multiple tasks or requests are assigned according to specific standards and rules when processing is required. A computing node refers to an independent computing unit responsible for executing computational tasks in a computing cluster or distributed computing environment. Node resources refer to the available hardware and software resources on a computing node. A node CPU refers to the central processing unit installed on a specific computing node. Node memory refers to the random access memory installed on a computing node. A node GPU refers to the graphics processing unit installed on a computing node. Resource utilization refers to the ratio of actual computing resource usage to total resource capacity within a certain time period. The task allocation strategy refers to the rules and methods used in a computing cluster or distributed computing environment to determine how to allocate computational tasks to different computing nodes. A computing running node refers to the node that executes computational tasks in a computing cluster or distributed computing system. Load status refers to the resource usage and workload level of a computing node when executing computational tasks. The load feedback mechanism refers to a systematic method for collecting, reporting, and processing load information of computing nodes when executing tasks. The load adjustment mechanism is a strategy and method used in computing clusters or distributed systems to dynamically adjust resource allocation and task execution based on node load.

[0099] Optionally, determining the priority of the computation task based on the task characteristics can be done using a heuristic algorithm.

[0100] Optionally, the load feedback mechanism and load adjustment mechanism for the computing running node based on the load status can be constructed using dynamic threshold settings and adaptive scheduling algorithms.

[0101] This invention, through the task allocation algorithm based on the molecular data, can process large amounts of molecular and target data, support diverse screening strategies, and significantly improve the efficiency of ligand molecule screening, shorten the screening cycle, and quickly identify potential ligand candidates. The ligand molecule refers to a molecule that, through screening and optimization, has been determined to most effectively bind to a specific target (such as a receptor, enzyme, or other biomolecule) and elicit the desired biological response.

[0102] S3. Based on the physiological state, extract target cells from the target female user, construct an in vitro culture environment for the target cells, and culture the target cells in vitro based on the in vitro culture environment to obtain in vitro cultured tissue. Construct a physiological environment for the in vitro cultured tissue, and add the ligand molecule to the in vitro cultured tissue based on the physiological environment to obtain ligand test tissue.

[0103] This invention, through the extraction of target cells from the target female user based on her physiological state, allows for drug screening using these cells, enabling more accurate prediction of drug efficacy and safety in vivo. The target cells refer to cells with specific functions, characteristics, or those associated with specific abnormal states.

[0104] Optionally, as an embodiment of the present invention, the extraction of target cells from the target female user based on the physiological state can be obtained through cell separation technology.

[0105] This invention, by constructing an in vitro culture environment for the target cells, facilitates cell survival in vitro, laying the foundation for subsequent drug screening experiments. The in vitro culture environment refers to a system that simulates the conditions for cell growth and functional performance in vivo.

[0106] As an embodiment of the present invention, constructing the in vitro culture environment for the target cells includes:

[0107] Configure a sterile environment and sterile culture medium for the target cells;

[0108] The in vivo environment of the target cells is analyzed, and the sterile culture medium is prepared based on the in vivo environment to obtain the prepared culture medium;

[0109] In a sterile environment, the target cells are inoculated into the prepared culture medium to obtain the inoculation culture medium;

[0110] Maintain a constant temperature and humidity in the inoculation medium;

[0111] The growth status of the target cells is monitored in real time, and a replacement mechanism for the inoculation culture medium is constructed based on the growth status.

[0112] The in vitro culture environment for the target cells is constructed based on the sterile environment, the constant temperature, the constant humidity, and the replacement mechanism.

[0113] The sterile environment refers to an environment devoid of any living microorganisms. The sterile culture medium refers to a nutrient substrate that has undergone special treatment to ensure it is free of any living microorganisms. The in vivo environment refers to the physiological environment of the target cells within an organism. The prepared culture medium refers to a liquid culture medium prepared for cell growth and maintenance by adding necessary nutrients, growth factors, hormones, salts, buffers, and other additives to a basal culture medium according to the specific cell type's needs. The inoculation medium refers to the culture medium used to transfer cells to a medium containing necessary nutrients and growth factors. The constant temperature refers to a temperature maintained at a preset value with very small fluctuations over a certain period of time, typically 37°C. The constant humidity refers to a relative humidity maintained at a certain percentage value over a certain period of time without significant changes over time. The growth state refers to the specific condition of an organism during its growth and development stages in its life cycle. The replacement mechanism refers to a system or procedure that periodically or according to the needs of the cell growth state during cell culture.

[0114] Optionally, the sterile environment and sterile culture medium for configuring the target cells can be configured using aseptic techniques.

[0115] Optionally, the sterile culture medium is prepared based on the in vivo environment, and the prepared culture medium can be prepared by bioinformatics analysis.

[0116] This invention, through in vitro culture of the target cells in a simulated in vivo environment, yields in vitro cultured tissues that can be cultured using the target female user's own cells, facilitating personalized drug testing. Specifically, the in vitro cultured tissues refer to tissue-like structures with specific structures and functions formed by culturing cells in an in vitro system that mimics the in vivo environment.

[0117] This invention provides an experimental model that more closely resembles in vivo conditions by constructing a physiological environment for the in vitro cultured tissue, thereby improving the reliability of drug screening and toxicity testing. The physiological environment refers to the sum of a series of biochemical and physical conditions that simulate the normal survival and functional performance of cells in a living organism.

[0118] Optionally, as an embodiment of the present invention, the physiological environment for constructing the in vitro cultured tissue can be constructed by extracellular matrix simulation.

[0119] Furthermore, in this embodiment of the invention, by adding the ligand molecules to in vitro cultured tissue based on the physiological environment, a ligand testing tissue is obtained. This tissue can be used for personalized drug testing based on the ligand response of specific target female users, improving the accuracy of drug screening. The ligand testing tissue refers to a tissue model used for experimental research in an in vitro culture system where specific ligand molecules are added to cultured cell or tissue samples.

[0120] Optionally, as an embodiment of the present invention, the addition of the ligand molecule to in vitro cultured tissue based on the physiological environment to obtain ligand test tissue can be obtained through tissue engineering techniques.

[0121] S4. Detect cell activity, gene expression, and protein expression in the ligand test tissue. Analyze the enhancing effect of the ligand molecule on the ligand test tissue based on the cell activity, gene expression, and protein expression, and calculate the gain coefficient of the enhancing effect. Based on the gain coefficient, screen the optimal ligand molecule. Based on the optimal ligand molecule, determine the female reproductive medicine for the target female user.

[0122] This invention, through detecting cell activity, gene expression, and protein expression in the ligand test tissue, can determine the direct impact of the ligand on cell growth and survival, and assess the cytotoxicity or growth-promoting effect of the ligand. Cell activity refers to the ability of cells to maintain their physiological functions and viability. Gene expression refers to the process by which information in a gene is transcribed into messenger RNA (mRNA) and then translated into protein, or the process by which gene information is transcribed into non-coding RNA (such as microRNA, rRNA, tRNA, etc.). Protein expression refers to the process by which gene information, after transcription and translation, ultimately produces functional proteins.

[0123] As an embodiment of the present invention, the detection of cell activity, gene expression, and protein expression of the ligand test tissue includes:

[0124] The ligand test tissue and the corresponding in vitro cultured tissue were subjected to an MTT assay to obtain the test experimental tissue and the control experimental tissue.

[0125] Configure the test experiment organization and the blank experimental group;

[0126] The absorbance of the test tissue, the control tissue, and the blank experimental group was measured using a pre-set microplate reader to obtain the absorbance values ​​of the experimental group, the control group, and the blank group.

[0127] Based on the absorbance values ​​of the experimental group, the control group, and the blank group, the cell viability of the ligand test tissue was calculated using the following formula:

[0128]

[0129] Where α represents cell viability, X xp X represents the absorbance of the experimental group, and X0 represents the absorbance of the blank group. p This represents the absorbance value of the control group;

[0130] Ligand tissue RNA was extracted from the ligand test tissue, and the ligand tissue RNA was transcribed into ligand tissue cDNA;

[0131] Prepare the qPCR reaction mixture of the ligand tissue cDNA by mixing the ligand tissue cDNA with the qPCR reaction mixture to obtain a ligand tissue mixture;

[0132] The Ct value of the ligand-tissue mixture is detected, and the gene expression of the ligand-tested tissue is calculated based on the Ct value.

[0133] Total protein was extracted from the ligand test tissue, and the total protein was quantified to obtain quantitative protein.

[0134] The quantitative protein was subjected to a labeling experiment to obtain protein detection results. Based on the detection results, the protein expression of the ligand test tissue was analyzed.

[0135] The MTT assay is an experimental method for detecting cell proliferation and cell viability. The test tissue refers to tissue treated with the ligand test tissue. The control tissue refers to tissue treated with in vitro cultured tissue. The blank control group is a control group without cells, used to correct background values ​​in the experiment. The preset ELISA reader is a laboratory instrument used to detect and analyze biochemical experimental samples. The absorbance of the test group refers to the absorbance value of the test tissue measured by the ELISA reader at a specific wavelength. The absorbance value of the control group refers to the absorbance value of the control tissue measured by the ELISA reader at a specific wavelength. The absorbance value of the blank control group refers to the absorbance value of the experimental well containing only the solvent (e.g., culture medium) and MTT, but without cells, measured by the ELISA reader at a specific wavelength. The ligand tissue RNA refers to RNA extracted from the ligand test tissue. The ligand tissue cDNA refers to complementary cDNA synthesized by reverse transcription of the ligand tissue RNA. The qPCR reaction mixture refers to the mixture used for real-time quantitative polymerase chain reaction. The Ct value refers to the number of cycles required for the fluorescence signal to first reach a predetermined threshold in real-time quantitative polymerase chain reaction. Total protein refers to the collection of all proteins extracted from the ligand test tissue. Quantitative protein refers to the protein content accurately measured using specific experimental methods. Protein detection results refer to data or information obtained after quantitative or qualitative analysis of proteins using experimental methods.

[0136] Optionally, the transcription of the ligand tissue RNA into ligand tissue cDNA can be performed using a transcriptase.

[0137] Optionally, the Ct value of the ligand tissue mixture can be detected by real-time quantitative PCR.

[0138] This invention, through analyzing the enhancing effect of the ligand molecule on the ligand test tissue based on cell activity, gene expression, and protein expression, can determine whether the ligand molecule can improve cell survival or proliferation, thereby assessing its potential cell growth-promoting effect. The enhancing effect refers to the influence of the ligand molecule on the ligand test tissue.

[0139] Optionally, as an embodiment of the present invention, the analysis of the enhancing effect of the ligand molecule on the ligand test tissue based on the cell activity, the gene expression, and the protein expression can be obtained through multi-omics joint analysis.

[0140] This invention, through calculating the gain coefficient of the enhanced effect, can help determine which ligand has a more significant enhancing effect. The gain coefficient is a parameter used to quantify the degree of influence of the ligand molecule on the test tissue.

[0141] Alternatively, as an embodiment of the present invention, the gain coefficient for calculating the enhancement effect can be calculated using molecular dynamics simulations.

[0142] This invention, through screening the ligand molecules based on the gain coefficient, selects ligand molecules with high gain coefficients and low side effects, thereby reducing potential side effects during drug efficacy and improving the safety of medication for target female users. The optimal ligand molecule refers to the ligand molecule that exhibits the best performance among a series of candidate ligand molecules through specific screening criteria and evaluation systems.

[0143] This invention, by determining the female reproductive drugs for target female users based on the optimal ligand molecule, can ensure safety and effectiveness while providing female users with higher quality drug options.

[0144] This invention, through the construction of a female reproductive drug screening platform for the target female users, can provide more efficient, safe, and personalized services, thereby improving the overall level of women's reproductive health. Optionally, this invention, based on the data parsing algorithm, analyzes the reproductive examination data and reproductive needs into physiological parameters of the target users. By analyzing the trends of these physiological parameters, potential reproductive health problems can be predicted, enabling early intervention. This invention, by mapping the physiological states to relevant target proteins, can help to deeply understand the mechanisms of occurrence and development of physiological states, significantly improving the quality and efficiency of medical services. This invention, based on the molecular data, utilizes the task... The allocation algorithm for matching ligand molecules to relevant target proteins can handle large amounts of molecular and target data, support diverse screening strategies, and significantly improve the efficiency of ligand molecule screening, shorten the screening cycle, and quickly identify potential ligand candidates. In this embodiment, by adding the ligand molecules to in vitro cultured tissues based on the physiological environment, the resulting ligand test tissues can be used for personalized drug testing targeting specific female users' ligand responses, improving the accuracy of drug screening. Finally, by determining the optimal ligand molecules, this embodiment ensures the safety and efficacy of female reproductive drugs for the target female user while providing higher-quality drug options. Therefore, this invention can improve the efficiency and accuracy of female reproductive drug screening in reproductive medicine.

[0145] like Figure 2The diagram shown is a functional block diagram of a female reproductive drug screening system provided in an embodiment of the present invention.

[0146] The female reproductive drug screening system 200 of this invention can be installed in an electronic device. Depending on the functions implemented, the female reproductive drug screening system 200 may include a screening platform construction module 201, a ligand molecule screening module 202, a ligand testing module 203, and a drug screening module 204. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0147] In this embodiment, the functions of each module / unit are as follows:

[0148] The screening platform construction module 201 is used to acquire the reproductive examination data and reproductive needs of the target female users, and construct the female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module.

[0149] The ligand molecule screening module 202 is used to define the data parsing algorithm of the user port, and based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into the physiological parameters of the target user. Based on the physiological parameters, the data processing module analyzes the physiological state of the target female user and maps the physiological state to relevant target proteins. The module also defines a retrieval algorithm for the chemical information database, and uses the retrieval algorithm to retrieve molecular data of the relevant target proteins based on the chemical information database. Finally, the module defines a task allocation algorithm for the molecular docking module, and uses the task allocation algorithm to match ligand molecules of the relevant target proteins based on the molecular data.

[0150] The ligand testing module 203 is used to extract target cells from the target female user according to the physiological state, construct an in vitro culture environment for the target cells, culture the target cells in vitro based on the in vitro culture environment to obtain in vitro cultured tissue, construct a physiological environment for the in vitro cultured tissue, and add the ligand molecule to the in vitro cultured tissue based on the physiological environment to obtain ligand testing tissue.

[0151] The drug screening module 204 is used to detect cell activity, gene expression, and protein expression of the ligand test tissue, analyze the enhancing effect of the ligand molecule on the ligand test tissue based on the cell activity, gene expression, and protein expression, calculate the gain coefficient of the enhancing effect, screen the optimal ligand molecule based on the gain coefficient, and determine the female reproductive drug for the target female user based on the optimal ligand molecule.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for screening female reproductive drugs in reproductive medicine, characterized in that, The method includes: Acquire reproductive examination data and reproductive needs of target female users, and construct a female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module. Define a data parsing algorithm for the user port. Based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into physiological parameters of the target female user. Based on the physiological parameters, use the data processing module to analyze the physiological state of the target female user and map the physiological state to relevant target proteins. Define a retrieval algorithm for the chemical information database. Based on the chemical information database, use the retrieval algorithm to retrieve molecular data of the relevant target proteins. Define a task allocation algorithm for the molecular docking module. Based on the molecular data, use the task allocation algorithm to match ligand molecules of the relevant target proteins. Based on the physiological state, target cells of the target female user are extracted, an in vitro culture environment for the target cells is constructed, and the target cells are cultured in vitro based on the in vitro culture environment to obtain in vitro cultured tissue. A physiological environment for the in vitro cultured tissue is constructed, and the ligand molecule is added to the in vitro cultured tissue based on the physiological environment to obtain ligand test tissue. Cell activity, gene expression, and protein expression in the ligand test tissue are detected. Based on the cell activity, gene expression, and protein expression, the enhancing effect of the ligand molecule on the ligand test tissue is analyzed, and the gain coefficient of the enhancing effect is calculated. Based on the gain coefficient, the optimal ligand molecule is screened, and based on the optimal ligand molecule, the female reproductive medicine for the target female user is determined.

2. The method for screening female reproductive drugs in reproductive medicine as described in claim 1, characterized in that, The construction of the female reproductive drug screening platform for the target female users includes: Clearly define the platform's construction goals, platform functions, and service scope corresponding to the target female users; Based on the construction goals, the platform functions, and the service scope, construct the access interface of the platform to be constructed; Write the interface elements of the access interface, define the interactive behavior of the interface elements, and construct the user port of the platform to be built based on the interface elements, the access interface, and the interactive behavior.

3. The method for screening female reproductive drugs in reproductive medicine as described in claim 2, characterized in that, The construction of the female reproductive drug screening platform for the target female users includes: Determine the data interface of the user port and construct a data cleaning module for the data interface; Define a data feature extraction algorithm for the platform to be built, and construct a data analysis module for the data of the platform to be built based on the data interface, the data cleaning module, and the data feature extraction algorithm. Construct a database of data for the platform to be constructed, and determine the mining objectives required for the database based on the construction objectives.

4. The method for screening female reproductive drugs in reproductive medicine as described in claim 3, characterized in that, The construction of the female reproductive drug screening platform for the target female users includes: Based on the stated mining objective, target data is mined from a pre-defined public database, and the target data is populated into the database to obtain a chemical information database. Determine the molecular docking software for the chemical information database, and construct the molecular docking module of the platform to be constructed based on the molecular docking software; Based on the user port, the data processing module, the chemical information database, and the molecular docking module, a female reproductive drug screening platform for the target user is constructed.

5. The method for screening female reproductive drugs in reproductive medicine as described in claim 1, characterized in that, The process of parsing the reproductive health examination data and reproductive needs into physiological parameters of the target user based on the data parsing algorithm includes: Extract experimental test data, menstrual cycle data, and imaging data from the reproductive health examination data; Based on the data parsing algorithm, the experimental test data and the reproductive requirements are quantitatively analyzed to obtain hormone level parameters; Image features are extracted from the image data, and the image features are analyzed to obtain reproductive organ parameters; Periodic analysis of the menstrual cycle data yields the menstrual cycle length and menstrual regularity. The physiological parameters of the target user are determined based on the hormone level parameters, the reproductive organ parameters, the menstrual cycle length, and the menstrual regularity.

6. The method for screening female reproductive drugs in reproductive medicine as described in claim 1, characterized in that, The mapping of the physiological state to relevant target proteins includes: Analyze the abnormal factors of the physiological state and extract the abnormal correlation data of the abnormal factors; Based on the abnormality-related data and the preset normal state data, differential expression analysis is performed on the physiological state to obtain differential analysis results; The mapping pathway of the abnormal factor is determined, and the abnormal factor is mapped to the mapping pathway based on the difference analysis results to obtain the mapped abnormal factor.

7. The method for screening female reproductive drugs in reproductive medicine as described in claim 6, characterized in that, The mapping of the physiological state to relevant target proteins includes: Based on the mapping pathway, the mapping anomaly factor, the anomaly factor, and the physiological state, functional enrichment analysis is performed on the mapping pathway to obtain the functional enrichment probability: Construct a protein-protein interaction network for the mapped anomalous factors, and analyze the location and function of anomalously expressed proteins of the mapped anomalous factors based on the functional enrichment probability using the protein-protein interaction network. Based on the location and function of the abnormally expressed protein, the relevant target proteins of the mapped abnormal factor are determined.

8. The method for screening female reproductive drugs in reproductive medicine as described in claim 7, characterized in that, The step of performing functional enrichment analysis on the mapping pathway based on the mapping abnormality factor, the abnormality factor, and the physiological state to obtain the functional enrichment probability includes: Determine the total number of pathway factors for the mapped pathway and analyze the total number of factors for the physiological state; Identify the number of anomalous factors of the anomalous factors, and determine the number of mapped anomalous factors of the mapped anomalous factors; The functional enrichment probability of the mapped pathway is calculated based on the total number of factors in the pathway, the total number of factors, the number of anomalous factors, and the number of mapped anomalous factors.

9. The method for screening female reproductive drugs in reproductive medicine as described in claim 1, characterized in that, The retrieval algorithm for the chemical information database is defined as follows: Determine the initial search algorithm for the chemical information database, and analyze the objective function, search step size, and Hessian matrix of the initial search algorithm; Determine the descent point and descent direction of the initial search algorithm, and based on the descent point, determine the number of searches for the initial search algorithm; When the number of searches exceeds the search step size, the objective function will be iteratively updated to obtain an iterative objective function; Calculate the search accuracy and convergence speed of the iterative objective function; Construct a memory matrix for the iterative objective function, and map the search accuracy and the convergence speed to the memory matrix to obtain an accuracy memory matrix and a speed memory matrix; Based on the precision memory matrix and the velocity memory matrix, the Hessian matrix is ​​updated to obtain the updated Hessian matrix; The descent direction is updated based on the updated Hessian matrix to obtain the updated descent direction; The search count is updated based on the updated descent direction to obtain the updated search count; When the number of update searches is less than the search step size, the iteration objective function is used as the update objective function; Based on the updated objective function and the updated Hessian matrix, the initial search algorithm is updated to obtain the retrieval algorithm for the chemical information database.

10. A female reproductive drug screening system, characterized in that, The system is used to perform the method for screening female reproductive drugs in reproductive medicine as described in any one of claims 1-9, the system comprising: The screening platform construction module is used to acquire the reproductive examination data and reproductive needs of target female users, and to construct a female reproductive drug screening platform for the target female users. The female reproductive drug screening platform includes: a user port, a data processing module, a chemical information database, and a molecular docking module. The ligand molecule screening module is used to define the data parsing algorithm of the user port, and based on the data parsing algorithm, parse the reproductive examination data and reproductive needs into the physiological parameters of the target user. Based on the physiological parameters, the data processing module analyzes the physiological state of the target female user and maps the physiological state to relevant target proteins. The module also defines a retrieval algorithm for the chemical information database, and uses the retrieval algorithm to retrieve molecular data of the relevant target proteins based on the chemical information database. Finally, the module defines a task allocation algorithm for the molecular docking module, and uses the task allocation algorithm to match ligand molecules of the relevant target proteins based on the molecular data. The ligand testing module is used to extract target cells from the target female user according to the physiological state, construct an in vitro culture environment for the target cells, culture the target cells in vitro based on the in vitro culture environment to obtain in vitro cultured tissue, construct a physiological environment for the in vitro cultured tissue, and add the ligand molecule to the in vitro cultured tissue based on the physiological environment to obtain ligand testing tissue. The drug screening module is used to detect cell activity, gene expression, and protein expression in the ligand test tissue. Based on the cell activity, gene expression, and protein expression, it analyzes the enhancing effect of the ligand molecule on the ligand test tissue and calculates the gain coefficient of the enhancing effect. Based on the gain coefficient, it screens the optimal ligand molecule and determines the female reproductive drug for the target female user.

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