28 results about "Enzyme kinetics" patented technology

The invention provides an enzyme activity parameter extraction method and system based on a large language model, and belongs to the field of text information processing and data mining. According to the method, the document in the PDF format is converted into the Markdown format through the OCR technology, and then key data are automatically extracted by combining a large language model with an optimized cue word; the accuracy and consistency of data are ensured through strict cue word optimization and post-processing operation in the automatic extraction process; and verifying the effectiveness of automatic extraction through accuracy and recall rate, wherein the finally generated enzyme database can be used for subsequent research and analysis. By combining the OCR technology and the large language model, the limitation of existing manual data extraction is broken through, and the automation degree of literature analysis and data extraction is remarkably improved; through cue word engineering and optimized cue word design, automatic extraction of structured data in complex literatures is achieved, and especially accurate recognition and extraction of enzyme kinetic parameters are achieved.

The invention relates to an enzyme kinetic parameter prediction method and application thereof. A brand-new enzyme kinetic parameter prediction framework based on artificial intelligence is designed, the framework is used for modeling enzyme-substrate information based on a protein language model, a compound molecule language model and molecular fingerprints, and then a machine learning algorithm is applied to fit enzyme kinetic parameters including the enzyme conversion number kcat, the Michaelis constant Km and the catalytic efficiency kcat / Km. And training is carried out on a clustered 10-fold cross validation data set, the prediction accuracy and the model generalization ability are improved, a new enzyme mining scheme is further developed, and the success rate of enzyme mining can be remarkably improved by combining a traditional sequence alignment method.

The invention discloses an enzyme kinetic parameter and domain label prediction method and device, equipment and a medium, and relates to the technical field of enzymes, and the method comprises the steps: training an initial enzyme kinetic parameter prediction model comprising a feature extraction sub-model and a domain adversarial neural network through employing an intra-domain data set and an extra-domain test set, obtaining a target enzyme kinetic parameter prediction model; inputting the target reaction substrate and the target enzyme sequence into a target enzyme kinetic parameter prediction model so that the target enzyme kinetic parameter prediction model performs enzyme kinetic parameter prediction to map to a corresponding enzyme kinetic parameter prediction value, and performing domain tag mapping to obtain a corresponding domain prediction tag, outputting an enzyme kinetic parameter prediction value and a domain prediction tag corresponding to the target reaction substrate and the target enzyme sequence. Through a special training process, the characteristics of a substrate and an enzyme sequence can be extracted more accurately, so that the prediction accuracy of enzyme kinetic parameters and domain tags is improved.

The invention provides an enzyme screening method and device, and belongs to the technical field of enzymes, the method is used for screening enzymes in a large range of enzyme types based on the binding capacity of the enzymes and a substrate and enzyme kinetic parameters, and multiple enzymes with low type similarity and high activity are obtained through rapid screening; the multiple enzymes obtained through screening are high in environmental adaptability and high in catalytic capacity upper limit, so that high conversion efficiency is achieved, it is guaranteed that the multiple enzymes obtained through screening can convert more substrates into products in a short time in the microbial fermentation environment, and then the microbial fermentation efficiency is remarkably improved.

The invention belongs to the technical field of aptamer hydrogel, and relates to a preparation method and application of bimetallic nano-enzyme aptamer hydrogel. The affinity of the aptamer and a target is accurately regulated and controlled through a flexible single chain with adjustable length and the gap width of a molecular tweezer region to obtain the aptamer with high affinity and binding stability, the aptamer hydrogel is constructed, and Pt-Ru bimetallic nano-enzyme is embedded in a polyacrylamide network in situ, so that the aptamer hydrogel is obtained. By doping metal, enzyme kinetic parameter optimization is realized, high-sensitivity signals are given to the hydrogel, structure-function integrated design of a sensing material is realized, and naked-eye rapid detection of sulfadimethoxine can be carried out.

The invention discloses a multi-parameter adaptive biochemical kit configuration method based on fusion of a genetic algorithm and a particle swarm optimization algorithm (GA-PSO), which is characterized by comprising the following steps: constructing a theoretical framework containing an enzymatic reaction mechanism, an enzyme kinetic parameter library and a mathematical calculation model; in combination with parameters such as input sample volume, reagent volume, reaction time and linear range, automatic derivation of formulas of the reagent I and the reagent II is realized through GA global search and PSO local optimization cooperative calculation; under a 0.5 cm optical path system, the TBA corresponding to 180 [mu] mol / L is less than or equal to 0.8 in A405nm, the TBA corresponding to 5 [mu] mol / L is greater than or equal to 0.036 in A405nm, the intra-batch CV is less than or equal to 2.5%, and the inter-batch CV is less than or equal to 3.5%. By replacing enzyme kinetic parameters (such as a target enzyme Km), a reaction mechanism and a detection wavelength, the method can be extensively applied to enzymatic detection kits for glucose, urea and the like.

The invention relates to the cross technical field of artificial intelligence and bioinformatics, in particular to a multi-modal enzyme kinetic parameter prediction method of an adaptive protein language model. Aiming at the problems that an existing processing method is lack of enzymatic reaction dynamic mechanism modeling and insufficient in three-dimensional structure utilization, the invention provides the following technical scheme: step 1, acquiring and preprocessing multi-modal data; 2, protein language model and molecular fingerprint feature extraction; 3, carrying out substrate recognition feature fusion based on cross attention; step 4, extracting conformation adaptive features based on the hybrid expert network; 5, correcting enzyme-substrate distribution alignment characteristics; step 6, kinetic parameter regression prediction; step 7, constructing a multi-objective loss function; and step 8, model training and parameter optimization. Through an enzyme reaction bridging adapter and an enzyme-substrate distribution alignment technology, high-precision prediction of enzyme kinetic parameters is realized, and cross-data-set accuracy and robustness are remarkably improved.

The present application relates to the biomedical detection technical field, disclose the liver reserve function evaluation product and the application of doxofylline in the evaluation product, the method is continuously intravenous infusion doxofylline to the subject, collects at least three time point blood samples during infusion, adopts liquid chromatography-mass spectrometry to detect the concentration of its metabolites theophylline acetaldehyde, theophylline acetic acid, hydroxyethyl theophylline and theophylline acetic acid-2' hydroxyethyl ester, based on the change data of total molar concentration of metabolite with time, the linear slope is calculated in combination with enzyme kinetics principle, and then the liver metabolic reserve function is detected.The present application also provides a complete detection system, the related use and pharmaceutical composition of doxofylline.The scheme is high in liver specificity, fast in detection, convenient in operation, excellent in safety, and superior in sensitivity to classical ICG clearance test, can solve the limitation of existing evaluation method, is suitable for preoperative risk assessment of hepatobiliary surgery, chronic liver disease staging and other scenes, and has important clinical application value.

The invention discloses a soil carbon (SOC and MBC) remote sensing inversion algorithm system based on a microbial decomposition process. The system comprises a data input module, a model construction and calculation module, a parameter optimization module, a space inversion module and an output verification module. The core of the soil carbon remote sensing inversion method is that a microbial four-pool decomposition model based on Michaelis-Menten enzyme kinetics is constructed, and the dynamic interaction of plant source carbon, microbial biomass carbon and two types of microbial residue carbon libraries is clearly depicted; carrying out efficient inversion and calibration on key dynamic parameters of the model by using a Bayesian optimization algorithm and taking limited ground observation data as constraints; and finally, fusing multi-source remote sensing data, solving a steady-state solution of the model pixel by pixel, and generating a high-precision soil organic carbon and microbial biomass carbon spatial distribution product. According to the method, high-precision, high-resolution and clear-mechanism soil carbon reserve estimation in a large-range region is realized, and a reliable technical tool is provided for regional carbon sink management and climate change research.

The application discloses methyl phenolic compounds, a preparation method and application thereof. Six new methyl phenolic compounds are separated from the skin of eleocharis tuberosa, and the compounds all show good inhibitory activity on alpha-glucosidase, and are stronger than the clinical first-line drug acarbose. The inhibitory activity of compound 3 is the best, enzyme kinetics research shows that the compound 3 plays a role as a reversible mixed inhibitor, ADME predicts that the compound 3 has good drug properties, including high gastrointestinal absorption and no CYP450 enzyme inhibition. The cytotoxicity experiment shows that the six compounds have no obvious growth inhibition on human embryonic kidney cells HEK293 at a concentration of 100 muM, and have good safety. The compounds can be combined with a pharmaceutically acceptable carrier to form a pharmaceutical composition, and are used for preparing a health care product for reducing blood sugar or a drug for treating diabetes. The preparation method is simple, easy to operate, suitable for industrial production, and is helpful to the high-value reuse of the skin of eleocharis tuberosa.

SARS-CoV-2 has raised the alarm to search for effective therapy for this virus. To date several vaccines have been approved, but few available drugs reported recently still need approval from FDA. Antiviral compositions having niclosamide derivatives were prepared for treating COVID-19. Using a FRET-based enzymatic assay, three niclosamide derivatives, JMX0286, JMX0301, and JMX0941, were identified as potent allosteric inhibitors against SARS-CoV-2 3CLpro, with IC50 values similar to that of known covalent inhibitor boceprevir. In a cell-based antiviral assay, these inhibitors can inhibit the virus growth with EC50 in the range of 2-3 μM. The mechanism of action of JMX0286, JMX0301, and JMX0941 were characterized by enzyme kinetics, affinity binding and protein-based substrate digestion. Molecular docking suggested that JMX0286, JMX0301, and JMX0941 bind specifically to an allosteric pocket of the SARS-CoV-2 3CL protease.

The present invention discloses an artificial intelligence-based odor feedback method, which relates to the technical field of odor feedback. The method comprises the following steps: dynamically calculating the clearance rate of odor components in patients with liver and kidney dysfunction by using a CYP2A6 enzyme kinetic model and a renal replacement therapy adsorption equation; combining the liver and kidney metabolic overload threshold constraints of a contraindication mapping table to reduce toxicity risks and solve the metabolic uncontrollability problem of traditional methods; designing a pulse release waveform based on an olfactory sensitivity attenuation model, coupling reverse airflow flushing, shortening the receptor recovery period and the EEG response latency, thereby overcoming the desensitization effect caused by sustained release.

The present invention relates to a method for improving the enzyme kinetics of a fumonisins esterase, to an improved fumonisins esterase and the use thereof, to a composition comprising said fumonisins esterase and to a method for modifying fumonisins.

The present application relates to the field of bionics, and in particular to a liposome in-vitro digestion simulation method based on the digestive physiological characteristics of infants and young children. Based on the digestive physiological characteristics of infants and young children in the early life, BSSL and PLRP2 are used in the simulation process, so that the simulation environment is more realistic, and the simulation effect is improved. The fitting degree of the method of the present application to the in-vivo lipid digestion conditions of infants and young children is improved by 30-50% compared with the prior art. By dynamically regulating the simulated gastric juice secretion rate, the simulated intestinal juice secretion rate, the acid liquid secretion rate, the alkaline liquid secretion rate, the mechanical parameters and the enzyme kinetic parameters, high-precision fitting of the digestive environment characteristics of infants and young children after feeding is achieved. The present application first realizes the system integration of special digestive enzymes and dynamic physiological parameters of infants and young children, and provides a high-bionic standardized scheme for the evaluation of the lipid digestion characteristics of infant formula food.

The invention relates to the technical field of bionics, in particular to a lipid in-vitro digestion simulation method based on infant digestion physiological characteristics. According to the method, BSSL and PLRP2 are used in the simulation process on the basis of the early-stage digestion physiological characteristics of the life of the infant, so that the simulation environment is more real, the simulation effect is improved, and the fitting degree of the method and the lipid digestion condition in the body of the infant is improved by 30-50% compared with the prior art; by dynamically regulating and controlling the simulated gastric juice secretion rate, the simulated intestinal juice secretion rate, the simulated acid liquid secretion rate, the simulated alkali liquid secretion rate, mechanical parameters and enzyme kinetic parameters, high-precision fitting of digestive environment characteristics after infant ingestion is realized; system integration of a special digestive enzyme system and dynamic physiological parameters of infants is achieved for the first time, and a high-bionic-degree standardized scheme is provided for lipid digestion characteristic evaluation of infant formula food.

This invention belongs to the field of drug metabolism and analytical chemistry, specifically relating to a method for the rapid determination of tigustastat and its active metabolite GD-MET-1 concentrations in a human liver microsome incubation system using liquid chromatography-tandem mass spectrometry (LC-MS / MS). The method first prepares stock solutions of tigustastat, GD-MET-1, and an internal standard, and prepares a series of standard curve solutions, quality control solutions, and precipitant solutions containing the internal standard. Next, the sample with the added precipitant solution undergoes vortexing and centrifugation pretreatment. Finally, chromatographic and mass spectrometric conditions are set, and the analysis is performed by LC-MS / MS. This method has been validated for specificity, accuracy, precision, matrix effects, recovery, residues, and stability, and can be reliably used for metabolic stability studies of tigustastat and GD-MET-1 in a human liver microsome incubation system, GD-MET-1 formation studies, metabolic enzyme identification, enzyme kinetic studies, and drug interaction studies.

The invention belongs to the technical field of enzyme kinetic parameter prediction, and discloses an enzyme kinetic parameter prediction model construction method and system.The method comprises the steps that an enzyme kinetic parameter set is constructed through multi-source data integration, data cleaning and data enhancement are conducted in sequence, and protein information supplement and compound data matching are achieved; constructing a multi-task learning enzyme kinetic parameter prediction model, and outputting a prediction result of the enzyme kinetic parameters by modeling a collaborative relationship between Mie's constants and enzyme turnover number data; and based on a multi-stage training strategy, carrying out segmented training on the enzyme kinetic parameter prediction model. According to the method, a richer enzyme kinetic parameter data set and a more reasonable deep learning model are constructed, so that the accuracy of enzyme kinetic parameter prediction is improved; by accurately predicting enzyme kinetic parameters, virtual screening and rational design of strains are assisted, so that the development process of a biosynthesis strategy is accelerated.

The invention relates to the field of medical materials, in particular to a nano-enzyme sonosensitizer Co3O4 (at) PAO (at) BSA (CPB) and a preparation method and application thereof. According to the invention, the Co3O4 (at) PAO (at) BSA (CPB) nano sound-sensitive agent is synthesized and regulated, a US enhanced enzyme kinetics strategy using Co3O4 CPHs as a substrate, the introduction of PAO consumes polyamine in tumors, and a carbonyl stress strategy of polyamine consumption successfully overcomes the defect of oxidative damage treatment, and the effect of Co ion mediated SDT / CDT induced oxidative damage treatment is enhanced through a nano enzyme cascade catalytic effect.

As described herein, RNA detection with high sensitivity and multiplexed specificity can be achieved with short detection times by encapsulating the Cas reaction in droplets and monitoring enzyme kinetics fluorescently.

The invention discloses a high-throughput screening system of an hPirin protease inhibitor and application, and relates to the technical field of biomedical engineering.The high-throughput screening system comprises a target spot structure modeling and screening system construction module; a high-throughput virtual screening module; an in-vitro enzyme activity verification module; an enzyme kinetics characterization module; a cell biological activity verification module; the non-specific limitation of a traditional transcription inhibitor is broken through, the enzyme activity center of hPirin protease is screened specially, the enzyme catalysis function can be specifically blocked, interference to other biological pathways is avoided, and the effect specificity of the inhibitor is remarkably improved. The screening system is high in reliability, through the layer-by-layer progressive design of multi-round progressive virtual screening combined with multi-technology combined verification (ultraviolet spectrum + HPLC-MS / MS + enzyme kinetics + cell experiment), the false positive screening result is effectively reduced, and the screening efficiency and quality of the high-activity candidate inhibitor are greatly improved.

Provided are methods of analyzing target nucleic acids, the methods comprising, using the target nucleic acids as reagents and reporters as substrates, assaying enzyme kinetic parameters of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) endonucleases comprising guide RNAs (gRNAs) that hybridize with reference nucleic acids. In certain aspects, certain such methods comprise comparing a sequence of a target nucleic acid with a sequence of a reference nucleic acid. In some embodiments, such comparison is based on the rates of cleavage of the reporters at plurality of concentrations of the reporters. The kinetic parameters can also be the Michaelis-Menten constant (KM), the apparent turnover rate (K*cat), and / or the apparent catalytic efficiency (K*cat / KM). Kits for performing the methods of the disclosure are also provided.

The invention discloses an enzyme kinetic parameter prediction and virtual screening method based on multi-source feature fusion, which belongs to the field of biological enzyme engineering and biological catalysis, and constructs a multi-modal fusion feature vector by combining a protein sequence and structural information of a substrate molecule and respectively utilizing a ProtT5 protein pre-training language model and a MolT5 model. According to the method, the extreme random tree model is used for performing high-precision prediction on the catalytic kinetic parameters of the enzyme-substrate pair. On the basis, systematic residue mutation is carried out on a candidate sequence similar to a target enzyme sequence at a key site, a mutant database is constructed, batch prediction and sorting are carried out on the mutant database, and finally virtual screening of the target enzyme is achieved. The method has remarkable advantages in the aspects of feature extraction, modeling efficiency and screening precision, and is suitable for large-scale enzyme engineering application.

The invention discloses an artificial intelligence-based odor feedback method, which relates to the technical field of odor feedback, and comprises the following steps: dynamically calculating the odor component removal rate of a patient with liver and kidney dysfunction through a CYP2A6 enzyme kinetic model and a kidney replacement therapy adsorption equation, and calculating the odor component removal rate of the patient with liver and kidney dysfunction in combination with the liver and kidney metabolism overload threshold constraint of a taboo mapping table. The toxicity risk is reduced, and the problem of uncontrollable metabolism in a traditional method is solved; a pulse release waveform is designed based on an olfactory sensitivity attenuation model, reverse airflow scouring is coupled, the receptor recovery period is shortened, the EEG response incubation period is shortened, and the desensitization effect caused by continuous release is broken through.

The invention belongs to the field of biological nano sensors, and particularly discloses a method for ultrasensitively detecting the activity of beta-glucosyltransferase (beta-GT) based on a CRISPR (clustered regularly interspaced short palindromic repeats) nano sensor. The invention designs a 5-hmC modified dumbbell probe integrating multiple functions of target recognition, palindromic isothermal amplification and restriction enzyme cutting sites, and realizes ultra-sensitive detection of beta-GT activity at a single molecule level by utilizing palindromic primer hyperbranched rolling circle amplification (PP-HRCA) based on a CRISPR (clustered regularly interspaced short palindromic repeats) nano sensor. The nano sensor can accurately quantify the activity of beta-GT in a complex biological matrix, and the method is convenient and fast, low in price, high in sensitivity and suitable for being popularized and applied to inhibitor screening and enzyme kinetic analysis.

The present invention discloses a snake venom thrombin protein and its preparation method and application. It belongs to the technical field of snake venom protein. The present invention uses SUPERDEX 75INCREASE 10 / 300GL gel chromatography column and C18SP‑100‑5‑ODS‑P liquid chromatography column to separate and purify a protein 3185 with thrombin activity from the venom of Agkistrodon acutus. Protein spectrum identification combined with transcript data analysis shows that the number of peptide segments of the protein is 10, the number of amino acids is 260, the protein molecular weight is 29.1KDa, and the isoelectric point is 8.18. The enzyme activity method measures the enzyme specific activity to be 1032U / mg. The protein reacts with the thrombin-specific chromogenic substrate S‑2238, and the reaction conforms to enzyme kinetics. The protein only acts on the Aα chain of fibrinogen, releases fibrin polypeptide A to form a loosely structured fibrinogen monomer, and forms a soluble fibrin degradation product.

The invention relates to the technical field of system biology, in particular to a toolkit for constructing a personalized multi-constraint metabolic network model based on modular thinking. The Core module is used for defining and managing a core object and a structure in a toolkit and constructing and expanding a multi-constraint metabolic network model; the Analysis module is used for providing a function tool for analyzing the model; the Ecmpy module is used for acquiring corrected enzyme kinetic parameters and automatically constructing an enzyme constraint model; the lo module is used for reading, writing and processing multi-constraint metabolic network model data; the Plotting module is used for visualizing multi-constraint metabolic network model data and an analysis result; and the Tmodel module is used for automatically acquiring thermodynamic parameters and automatically constructing a thermodynamic constraint model. According to the toolkit for constructing the personalized multi-constraint metabolic network model based on modular thinking, through modular design and automatic parameter acquisition and model construction functions, the demand of manual intervention is reduced, the flexibility and expansibility of modeling are improved, and the modeling speed and accuracy are improved.

The invention discloses a hyoscyamine 6 beta hydroxylase mutant, a gene and application, and relates to the technical field of biology, and compared with wild hyoscyamine 6 beta hydroxylase, the mutant has the following mutations: the 43rd amino acid is mutated from histidine to aspartic acid, the 247th amino acid is mutated from glutamine to glutamic acid, and the 43rd amino acid is mutated from glutamine to glutamic acid. The 324th amino acid is mutated into glutamic acid from aspartic acid, and the amino acid sequence of the mutant is as shown in SEQ ID NO: 4. A nucleotide sequence for coding the hyoscyamine 6 beta hydroxylase mutant is shown as SEQ ID NO: 8. According to the invention, the HnH6H mutant with remarkably improved catalytic activity is obtained, and the HnH6H mutant is proved to have stronger production performance than wild type HnH6H in escherichia coli fermentation, in-vitro enzyme kinetic analysis and plant metabolism engineering, and has important application value in scopolamine metabolism engineering and synthetic biology.

The invention relates to the technical field of network model toolkits, in particular to a generation method and application of a multi-constraint metabolic network model toolkit. The invention discloses a method for generating a multi-constraint metabolic network model toolkit. The method comprises the following steps: constructing a multi-constraint metabolic network model; performing parameter correction on the multi-constraint metabolic network model to obtain a model after parameter correction; performing model analysis by using the model after parameter correction to obtain a model analysis result; the multi-constraint metabolic network model comprises an enzyme constraint model, an enzyme heat constraint model and a thermodynamic constraint model; the parameter correction comprises enzyme kinetic parameter correction and thermodynamic parameter correction. According to the generation method disclosed by the invention, the influence of the metabolite concentration on reversibility can be effectively reflected by integrating thermodynamic factors, so that the ubiquitous problems of constraint relaxation, prediction distortion, single research angle and the like caused by excessive simplification of a current enzyme constraint model are solved.