48 results about "Enzyme function" patented technology

The invention belongs to the field of bioinformatics, and relates to an enzyme function prediction method based on multi-view fusion and comparative learning. According to the method, through multi-view data construction, feature extractor design, cross-view contrast learning mechanism introduction, feature fusion module design and loss function optimization, an enzyme function prediction model with comprehensive decision ability is constructed. Firstly, an independent deep feature extractor is designed for each visual angle so as to capture feature information of each visual angle to the maximum extent; secondly, by utilizing a cross-view contrast learning mechanism, the consistency of cross-view features is improved by approaching the feature representation of the same enzyme under different views, and meanwhile, the feature representation of different enzymes under the same view is deduced, so that the discrimination capability of the model is optimized; finally, multi-view feature weighted fusion is adopted, the features of different views are integrated in a unified mode, and the functions of the enzyme are predicted through a classifier. According to the method, the prediction precision and the robustness are improved.

The invention provides an algorithm for predicting enzyme functions by combining a GPT model on the basis of the application of a deep learning technology in biological enzyme. Comprising the steps of sequence embedding and sequence feature extraction through a mask multi-head self-attention mechanism. Firstly, enzyme sequence data is obtained from a public database, and pre-training and fine tuning data sets are divided; self-supervising and pre-training a GPT model by using an enzyme sequence, and learning sequence autoregression generation; then, adding a classifier on the pre-trained model, and finely adjusting the model by using data with an enzyme function label; adversarial training is introduced in the fine tuning stage to enhance robustness. According to the technical scheme, six layers of Transform decoders are adopted, the unified sequence length is 700 tokens, and high-dimensional features are mapped to an enzyme function space through a layer of full-connection network. According to the method, the problems that an existing enzyme function prediction method depends on manual features and is weak in generalization ability are solved, and end-to-end high-precision enzyme function prediction is achieved.

The invention discloses cloning and functional identification of a liverwort flavone synthetase gene, and belongs to the technical field of gene engineering. According to the invention, one flavone synthase I (flavones synthase I, FNS I) is obtained through screening, and is named as MpFNS I; a prokaryotic expression system is utilized, an MpFNS I recombinant protein is obtained through purification, and the result of in-vitro enzyme activity identification shows that an MpFNS I enzyme substrate is relatively wide in selectivity, has a flavone synthetase function and also has a part of flavonol synthetase function. The liverwort flavonoid has a significant difference on affinity and catalytic efficiency of different substrates, the in-vivo function of the liverwort flavonoid is verified by utilizing heterologous expression of arabidopsis thaliana, experimental evidence is provided for comprehensively analyzing a biosynthetic pathway of the liverwort flavonoid, and meanwhile, a research target is provided for deeply researching a mechanism for synthesizing and responding to UV-B radiation of the liverwort flavonoid.

The invention belongs to the field of bioinformatics, relates to an enzyme function prediction method based on structure perception and semantic features, and integrates technologies such as a protein large language model, a protein structure prediction model, a graph convolutional neural network and a cross-modal attention mechanism. The method comprises the following five steps of initial multi-view feature extraction, key structure perception, key semantic information extraction, multi-view information fusion and function classification. The method comprises the following steps: firstly, inputting an amino acid sequence of enzyme into ESM2 and ProtT5 protein large language models and an ESMFold protein structure prediction model for preprocessing so as to extract Esm semantic information, Prt semantic information and structure information; then, inputting the Esm semantic information and the structure information into a key structure sensing module provided by the method so as to obtain key structure features; a large number of experimental results show that the method can efficiently and accurately predict the enzyme function, and the performance of an existing method is remarkably improved.

The invention relates to the field of biology, in particular to application of a coix lacryma-jobi diacylglycerol acyltransferase gene (ClDGAT2). The invention discloses an application of a coix lacryma-jobi diacylglycerol acyltransferase gene (ClDGAT2) in improving the yield of oil. The coix lacryma-jobi diacylglycerol acyltransferase gene (ClDGAT2) has the following functions: triglyceride can be generated, a DGAT enzyme function is realized, and the capability of recovering TAG defect type saccharomyces cerevisiae oil production is realized.

The invention discloses a cerium nano-enzyme composite active material and application thereof in hepatic failure treatment, and belongs to the technical field of nano-materials. The invention combines the functions of miR122 and cerium dioxide nano-enzyme, develops a new stem cell differentiation inducer, namely a cerium nano-enzyme composite active material, and deeply studies the potential mechanism of the nano-enzyme material with catalytic activity in regulating stem cell fate, and the cerium dioxide nano-enzyme can be used for delivering miR122 into stem cells after being modified, so that the stem cell differentiation inducer can be used for inducing stem cell differentiation. The miR122 is highly enriched in cells, so that hepatic differentiation is induced. Meanwhile, the catalytic activity of the cerium dioxide nano-enzyme can regulate the ROS steady state in the cells and protect mitochondria from being damaged by ROS induction, so that the mitochondrial function is maintained, the energy requirement in the differentiation process is met, and the method is of great importance to successful differentiation of the stem cells. In order to solve the problem of activity damage in hepatic cell transplantation, a layer of Ce < 4 + >-polyphenol skeleton is coated on the surface of induced hepatic-like cells (iHLCs), so that the function and activity of the hepatic cells after transplantation are further protected, and the in-vivo treatment effect of the hepatic cells is improved.

The present disclosure belongs relates to a 2709 alkali protease mutant modified based on molecular dynamics calculation and use thereof in liquid detergents. The dynamic structure feature of a 2709 alkali protease derived from Bacillus licheniformis are studied by using a molecular dynamics method through computer simulation, which is a unique effective method capable of studying a relationship between the structure of the 2709 alkali protease and molecular dynamics as well as an enzyme function in an atomic level. After molecular dynamics calculation, appropriate sites are selected for protein engineering to obtain the 2709 alkali protease mutant suitable for industrial application of detergents. The protease mutant has significantly improved enzyme activity under the alkaline condition, is better in stability, not only has good decontamination effect but also has good component compatibility with components in the detergent, and can be widely applied to the field of washing industry.

This invention discloses a high-yield lactyl-3-4 ...5-4-4-4-4-4- N This invention relates to plasmid-free genetically engineered strains of tetrasaccharides and their applications, belonging to the field of microbial genetic engineering. The invention screened strains with higher activity. β -1,3-galactosyltransferase gene PmgalT Computer-aided enzyme function modification was used to achieve a shake-flask yield of 10.05 g / L for the constructed mutant. Subsequently, genome integration was performed... breast Multi-copy integration PmgalT * V27I / V39I / Y147F ‑galE‑galU A plasmid-free strain was constructed, enabling it to grow in shake flasks with lactoyl- N The yield of tetrasaccharides reached 14.4 g / L. Using glucose as the sole carbon source, the highest yield of 68.19 g / L was achieved at 64.5 h; using glycerol as the sole carbon source, the highest yield of 62.88 g / L was achieved at 60.5 h, providing a basis for its industrial production.

The present disclosure provides a technique for inhibiting ubiquitin ligase RFFL function and improving the plasma-membrane expression of a mutant CFTR protein. The present disclosure also provides a novel therapeutic agent for CF.　The present inventors have found that a modified oligonucleotide, or a salt thereof, having a specific base sequence and a modified structure, can inhibit ubiquitin ligase RFFL function and improve the plasma-membrane expression of a mutant CFTR protein.

The disclosed embodiments relate to methods of initiating aripiprazole treatment in a patient who is a CYP2D6 poor metabolizer or a CYP3A4 poor metabolizer, or both.

The invention discloses an enzyme targeted response type benzyl fluorine bridged glucoside gadolinium compound and application thereof as a magnetic resonance contrast agent. According to the invention, a high-stability macrocyclic gadolinium contrast agent is subjected to structural modification, a glycoside group and a benzyl fluorine bridging group with specific biological enzyme responsiveness are introduced, and the benzyl fluorine bridging group triggered by enzyme response forms a quinone methylation active intermediate; the quinone intermediate can react with a nucleophilic biomacromolecule functional group to form a covalent bond to obtain a gadolinium biomacromolecule compound, so that the magnetic resonance relaxation rate of gadolinium molecules can be remarkably improved, the enhancement of an MRI signal is realized, and the real-time specific enzyme tracking function of MRI is realized. Compared with the existing non-targeted responsive gadolinium contrast agent, the contrast agent provided by the invention has specific biological enzyme targeted responsiveness, can be used for real-time and non-invasive monitoring of diagnosis and treatment of enzyme function abnormality diseases, and has important significance in the aspects of precision medical treatment and the like.

A computational system and method for digital modeling of biochemical reactions within cardiac cells are disclosed. The system comprises processors and a computer-readable storage device with instructions to maintain biological data related to cardiac cell reactions and receive user selections via a user interface to configure a simulation. The user can select a cardiac cell class, and functions to load cellular components, generate enzyme activity, load specific enzymes, and perform enzymatic reactions. The system performs in silico experiments, predicts new biological data, and compiles this into configuration data. An enzyme activity model is generated and simulated under various conditions, including user-defined enzymatic dysregulation, to replicate and study cardiac physiology and pathology. The results, such as changes in energy metabolism parameters like glucose consumption and ATP usage, are outputted. The system provides a detailed and interactive platform for research and education in cardiac electrophysiology and disease.

The application belongs to the field of biological enzyme engineering, and provides a rational design method for enzyme modification based on deep learning, which comprises the following steps: constructing a protein crystal structure data set; adding an atomic microenvironment centered on an amino acid residue based on the protein crystal structure data set, and reconstructing the protein crystal structure data set; predicting the amino acid residue of the reconstructed protein crystal structure data set by using a pre-trained amino acid residue prediction model according to the reconstructed protein crystal structure data set; and determining potential sites for enzyme function optimization according to the difference between the predicted amino acid residue probability and the actual amino acid probability of the natural enzyme. The application takes the protein crystal structure data as a basic data set, fully utilizes the physicochemical properties of the protein, and rationally designs and modifies the enzyme based on artificial intelligence, thereby avoiding the inconvenience caused by manual screening.

The invention discloses an enzyme function prediction method based on three-dimensional point cloud characterization and multi-modal fusion. The method comprises the following steps: extracting point cloud features on the surface of protein by using dMaSIF to characterize geometric and chemical characteristics; the point cloud features are coded through the pre-trained Point Net + +; a decoupling cross attention mechanism is adopted to fuse PointNet + + point cloud coding, Sapot network structure coding and ESM-2 sequence coding, and the network is optimized through comparison learning based on sorting loss. The invention also provides an enzyme function prediction system based on three-dimensional point cloud representation and multi-modal fusion, and the system comprises a point cloud feature extraction module, a point cloud coding module, a multi-modal fusion module and an optimization module, and is used for realizing the method. By integrating the protein three-dimensional structure, sequence and multi-source information of surface physicochemical characteristics, the functional prediction accuracy and robustness are remarkably improved, and the method has excellent performance in enzyme classification (EC number prediction) tasks.

There is provided a polynucleotide-modifying enzyme with a functional nuclease domain and a display domain. The functional nuclease domain comprises a nuclease catalytic pocket. The display domain comprises a peptidic recognition sequence of from 3 to 20 amino acids in length, in a loop, an alpha helix or an extension off the end of the alpha helix that is positioned on an external surface of the polynucleotide-modifying enzyme. The peptidic recognition sequence recognizes a target cell receptor of a target cell to allow cell internalization of the polynucleotide-modifying enzyme in said target cell.

The invention discloses a sandalwood callus transient expression method and application thereof. The method comprises the following steps: by taking sandalwood embryogenic callus as a transformation receptor, instantaneously introducing a target gene with a GFP tag into the embryogenic callus by adopting an agrobacterium-mediated method, and screening a positive material by utilizing fluorescence microscopic observation, so that the transient expression of the target gene in the callus can be quickly detected; further collecting samples, performing gene expression or GC-MS (gas chromatography-mass spectrometry) analysis on metabolites, and identifying gene / enzyme functions.

The invention discloses a vascular specific VND gene promoter and application of the vascular specific VND gene promoter in driving expression of xylan hydrolase in plants. The invention provides a DNA fragment. The DNA fragment is any one of the following: 1) the nucleotide sequence of the DNA fragment is sequence 1; and 2) a nucleic acid sequence which has more than 90% of homology with the nucleic acid sequence shown in 1) and has the same function. Experiments prove that a SbNAC31 gene promoter specifically expressed by a vascular tissue is connected with CDS of a xylan hydrolase gene SbXyl, and a vector with the fusion gene is used for converting a sorghum xylan hydrolase function deletion mutant, so that the growth and development defects of the mutant are made up; meanwhile, the excellent lignocellulose quality (high feed quality) of the mutant is reserved.

The invention provides a detection-based fine-grained protease function prediction method. The method comprises the following steps: firstly, sending an initial input protein sequence into a pre-trained ESM-1b encoder to obtain a general initial embedded feature, and constructing an enzyme function prediction model based on an encoder-decoder structure, including a protein residue encoder and an enzyme function decoder; then training and optimizing the model by adopting a bipartite graph matching-based model training mode; then constructing a functional specific enzyme active site labeling method based on an attention mechanism, and locating important functional sites in an enzymatic reaction while predicting enzyme functions; the model finally realizes single-function enzyme prediction and multi-function enzyme prediction tasks, and performs interpretive enzymatic reaction active site labeling according to prediction results. And finally establishing the relation between the protein structure and the function.

The present application discloses a protease having carnosine hydrolase function and its use in L-carnosine synthesis, wherein the protease comprises the amino acid sequence shown in SEQ ID NO: 6. The protease described herein can utilize either β-alanine methyl ester hydrochloride and L-histidine as substrates, or β-alanine and L-histidine as substrates, thereby reducing costs and utilizing β-alanine produced due to the instability of β-alanine methyl ester hydrochloride.

Provided are a highly efficient base editing system, a preparation method therefor and the use thereof. Specifically, provided is a fusion protein, comprising a nuclease domain and an editing enzyme domain, wherein the editing enzyme domain is inserted into an insertion site in the nuclease domain. The nuclease domain in the fusion protein has the function of a nuclease, the editing enzyme domain in the fusion protein has the function of an editing enzyme, and the nuclease domain is derived from a Cas protein or a Cas protein mutant. On the basis of an activation-induced cytosine deaminase (AID), a new AID mutant having a shorter sequence and higher base editing efficiency is obtained by means of screening, and then the highly active AID mutant is randomly inserted into nSaCas9 (D10A) KKH, such that a new cytosine base editor EB-TAM having high base editing efficiency and an expanded and narrowed editing scope is successfully obtained by means of screening.

The invention discloses an enzyme functionalized sensor for detecting nano plastic DPV in a biological matrix as well as a preparation method and a detection method of the enzyme functionalized sensor, and belongs to the field of nano plastic detection. The sensor comprises an electrode and CAT enzyme, wherein the surface of the electrode is modified with positively charged nano-gold particles, and the CAT enzyme is fixed through positive and negative electrostatic interaction. According to the sensor, the CAT enzyme and the nano plastic are combined to generate conformational change to change the activity of the CAT enzyme so as to cause DPV signal change, the sensitivity is high, the sensor has similar DPV signal response to different types of nano plastic, and a unified calibration model can be utilized to detect a complex biological matrix system so as to realize total amount determination of various nano plastic. And the electrochemical detection method does not need complex instruments and pretreatment, and provides a rapid, economic and extensible detection scheme for nano plastic exposure evaluation and environmental monitoring.

The invention relates to the field of air purification and environmental governance, and discloses a biological enzyme compound preparation for removing hydrogen sulfide and a preparation method thereof, the compound preparation comprises a compound biological enzyme, a functional additive, polyhexamethylene biguanide, a stabilizer and deionized water; the functional additive is a double-metal-based additive which is prepared by adopting an impregnation method and interacts with a copper-based imidazole ionic liquid and an iron-based metal organic framework, and is prepared by grafting modification by utilizing polyvinylpyrrolidone; the copper-based imidazole ionic liquid is prepared from 1-butyl-3-methylimidazole chlorine salt and copper chloride monohydrate by adopting a melting method; the iron-based metal organic framework is prepared by promoting coordination and self-assembly of 2-aminoterephthalic acid and iron ions through solvothermal reaction, a composite biological enzyme system is formed by carbonic anhydrase, hydrogen sulfide oxidase, thiocyanase and laccase, and the hydrogen sulfide removal efficiency of the composite preparation is improved by introducing a functional additive; and the temperature-resistant range is wider.

The invention aims to provide a method, equipment, medium and program product for determining a target enzyme expressed in a target host, and the method comprises the following steps: on the basis of amino acid sequence information and structure information corresponding to a heterologous enzyme meeting a required function and information of the target host, predicting the target enzyme by using a codon sequence prediction model, the codon sequence prediction model is used for determining codon sequence information and corresponding score information, the score information is used for comparing expression quantities of different codon sequences, the enzyme corresponding to the codon sequence with the higher score can have the higher expression quantity in the target host, and the enzyme corresponding to the codon sequence with the higher score can have the higher expression quantity in the target host. Furthermore, the enzyme efficiently expressed in the target host can be quickly screened out, and the screening cost is reduced. In addition, an enzyme function prediction model and / or an enzyme-substrate interaction prediction model can be combined to screen from the aspects of expression quantity, catalytic reaction type and / or enzyme activity and the like, so as to obtain the enzyme which is high in expression and activity and has required functions.

The present application relates to a kind of functional gene detection method, specifically sulfate-reducing bacteria metabolic enzyme functional gene detection method.The specific sequence of three different hairpin DNA chains is designed according to the specificity of sulfate-reducing bacteria metabolic enzyme, after mixing three different hairpin DNA chains, incubation is carried out by adding the sample to be detected, after incubation, hemin, TMB and H2O2 are added to the system to react, and the key metabolic enzyme DNA of sulfate-reducing bacteria in the sample to be measured is qualitatively / quantitatively detected by color reaction.The preparation method of the present application is simple to operate, and the reaction is rapid, and visible to naked eye.The construction of sulfate-reducing bacteria metabolic enzyme functional gene detection method has potential application value in the research fields of molecular biology, biological analytical chemistry and medical detection.

The invention belongs to the field of food processing and functional food, and particularly relates to astringency removal and enzyme function evaluation of aronia melanocarpa. The astringent taste of the aronia melanocarpa is reduced, the polyphenol content of the aronia melanocarpa is increased, the oxidation resistance of the aronia melanocarpa is enhanced, the application range of the aronia melanocarpa in the food industry is widened, and the astringent taste of the aronia melanocarpa is improved. A new thought and method are provided for high-value deep processing and astringency removal of aronia melanocarpa, and meanwhile, a new raw material and product research direction is provided for enterprises related to enzyme products.

The present application relates to the field of biological medicine and tissue engineering, and particularly relates to a nano-enzyme functionalized dynamic hydrogel as well as a preparation method and application thereof.The nano-enzyme functionalized dynamic hydrogel comprises black phosphorus nanosheets and nano-enzymes.The preparation method of the nano-enzyme functionalized dynamic hydrogel comprises the following steps: (1) synthesis of a hydrogel precursor solution; (2) preparation of biomimetic nano-enzymes; and (3) preparation of a dynamic hydrogel.In the present application, BP can maintain Ce(III) / Ce(IV) redox cycling through self-oxidation and improve the ROS scavenging capacity in the microenvironment, thereby serving as CeO x a stabilizer of nano-enzymes.In addition, the MBC obtained by wrapping BP@CeO x in the nucleus pulposus cell membrane can better achieve nucleus pulposus cell targeting, so that BP@CeO x can effectively and durably scavenge intracellular ROS.

The invention relates to a synthase mutant for synthesizing lycopene and application of the synthase mutant, enzyme function improvement is performed on difunctional phytoene synthase / lycopene cyclase from exogenous eukaryotic microorganisms, so that the functional activity of the lycopene cyclase is inactivated, and the mutant is applied to construction of a new lycopene biosynthesis path. And efficient and specific synthesis of lycopene in oil-producing fungi is realized.

Provided are methods of increasing root biomass, shoot biomass and / or suberized regions in plants by reducing expression and / or activity of one or more Gly-Asp-Ser-Leu (GDSL) lipases in the plant. Also provided are transgenic or gene-edited plants that have reduced expression and / or activity of one or more GDSL lipases, and have increased root biomass, shoot biomass and / or suberized regions. Also provided are isolated or recombinant molecules used in the provided methods and / or for generating the provided plants.

This invention relates to the field of enzyme function prediction technology, specifically to an enzyme function prediction method based on deep contrastive learning. The method includes: acquiring amino acid sequence data of the target enzyme and molecular structure data of the reaction substrate; performing sequence embedding encoding on the amino acid sequence data to generate sequence feature vectors, and performing graph structure modeling on the reaction substrate molecular structure data to generate molecular graph feature vectors; fusing the two data across modalities to generate a joint feature representation containing spatial complementarity features of enzyme-substrate binding sites and electron transfer features of catalytic active centers; calling a pre-trained contrastive learning encoder to perform contrast sample mining on the joint feature representation, generating a set of positive and negative sample pairs; constructing a contrastive loss function based on this set, and updating the encoder parameters through backpropagation to obtain an optimized model; inputting the data into the optimized model, and outputting the predicted catalytic function category of the target enzyme. This method improves the accuracy and stability of enzyme function prediction.

Disclosed herein are systems for regulating enzyme function using an enzyme inhibitor linked to a target recognition sequence, which releases the inhibitor from the enzyme in the presence of a specific target analyte (e.g., a marker of a disease or disorder), thereby activating the enzyme. These enzymes may generate detectable signals and / or perform therapeutic functions. Also disclosed herein are methods of using these systems for the detection of target analytes and the observation, monitoring, and treatment of diseases and disorders.