10 results about "Enzyme kinetics" patented technology

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 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.

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 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.

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.

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.