23 results about "Substrate molecule" patented technology

The invention discloses a biotin ligase mutant and application thereof, and belongs to the technical field of gene engineering. According to the invention, a series of biotin ligase mutants are prepared by docking biotin ligase and substrate molecules thereof and carrying out multiple mutations on screened 10 amino acids with binding force acting sites. On the basis, a biotin ligase mutant is connected to escherichia coli through a homologous recombination technology, a series of escherichia coli recombinant bacteria with high biotin yield are obtained, and the biotin yield reaches 0.873 mg / L to the maximum after 24-hour fermentation.

The invention discloses a method for detecting multiple biomarkers based on a nano-enzyme chemiluminescence technology, and the method comprises the following steps: preparing iron oxide nano-particles as a nano-enzyme core, and coating the surfaces of the nano-particles with substrate molecules to form a nano-enzyme-substrate compound; mixing and incubating the nano enzyme-substrate compound and a sample to be detected, adding a hydrogen peroxide solution, transferring to a microplate, and collecting a chemiluminescence signal by using a microplate reader; extracting characteristic parameters including peak value luminous intensity, peak reaching time, half-peak width, rising rate, attenuation rate, integral intensity and / or wavelength ratio in the collected luminous curve, wherein the characteristic parameters comprise the peak value luminous intensity, the peak reaching time, the half-peak width, the rising rate, the attenuation rate and the integral intensity; and constructing and training a multi-layer neural network model so as to predict the concentration of the multiple biomarkers based on the characteristic parameters of the sample data. By means of the scheme, multiple biomarkers can be detected at the same time, and the detection accuracy is improved.

In some embodiments of the present disclosure, there is provided a bioelectrochemical sensor for measuring analyte or substrate molecule (signal) concentration in which the current (response) is insensitive to oxygen, does not require media or sensing product molecule species, including low sensitivity to interferents, and can be used to measure the concentration of an analyte or substrate molecule (signal). And includes high operational stability in both steady state response amplitude and response time.

The invention provides a chiral delta-lactam compound as well as a preparation method and application thereof. The preparation method of the chiral delta-lactam compound comprises the following steps: taking a 1, 4, 2-dioxazole-5-ketone derivative and a nucleophilic reagent as raw materials, and reacting under the action of a chiral metal catalyst and an additive to generate the chiral delta-lactam compound. According to the synthesis strategy, under the catalysis of a chiral Ir (III) catalyst, an olefin part in a substrate molecule and electrophilic metal nitrogen are subjected to an electrophilic addition reaction to generate a carbocation intermediate, then 1, 2-negative hydrogen migration is carried out under the promotion of a chiral ligand, more stable aza carbocations are formed, and the chiral Ir (III) compound is synthesized. And a nucleophilic reagent captures the compound to form a delta-lactam compound containing a continuous gamma, delta-chiral center. The method has excellent yield, diastereomer selectivity and enantiomer selectivity, and is compatible with various carbon, nitrogen and oxygen nucleophilic reagents and biological related molecules. The invention provides a brand-new efficient route for synthesis of the chiral delta-lactam compound.

The invention discloses a concentration detection method and system based on combination of an STM-BJ technology and deep learning, and a storage medium. The method comprises the following steps: S1, collecting conductivity data of a pure probe molecule solution and a mixed solution of probe molecules and substrate molecules; s2, training a pre-constructed supervised deep learning model by adopting the data; s3, collecting conductance data of a mixed solution under different substrate molecule concentrations, and inputting the conductance data into the trained model to obtain the proportion of the conductance data determined to contain substrate molecules under each concentration to the total conductance data under the concentration; s4, fitting and establishing a standard relation curve between the molecular concentration of the substrate and the proportion; s5, collecting the conductivity data of a solution to be detected, inputting the conductivity data into the model, and substituting the identified proportion of the conductivity data containing the substrate molecules in the total number of the conductivity data of the solution to be detected into the standard relation curve to calculate the concentration of the substrate molecules in the solution to be detected; according to the invention, the concentration of an object to be detected can be detected at a second level and an extremely low concentration.

According to the present invention, there is developed and provided a method for efficiently producing an antibody-substrate conjugate which is uniform and has a small molecular size and in which the binding ratio between a substrate molecule and an antibody is controlled in a modification site-specific manner.　Provided is a method for producing an (antibody fragment)-substrate conjugate with high production efficiency, the method comprising fragmenting an antibody to obtain an antibody fragment and then modifying the antibody fragment with a substrate molecule by using an MTG fusion body.

The invention provides a surface imprinting organic catalyst for directionally constructing catalysis and selecting sites, and a preparation method and application of the surface imprinting organic catalyst. According to the method, an aldehyde-alcohol reaction, which is one of important reactions of carbon-carbon bonding, is selected as a target reaction, and a selective cavity matched with a catalytic activity center is constructed on the surface of a magnetic carrier Fe3O4 by adopting a surface molecular imprinting technology and designing template molecules by taking a covalent connection product of a catalyst tryptophan and a target catalytic product as a template. The construction of the surface molecular imprinting cavity ensures that the active center of the catalyst is in full contact with a substrate molecule, the catalytic efficiency is improved, and meanwhile, the imprinting cavity has a certain selective recognition capability, can be matched with a reaction substrate similar to a template structure and a functional group, has a selective catalysis capability in a complex reaction system, and can be used for preparing a catalyst. Wide application prospects are realized.

The application discloses a nanowire-nanotube hybrid sensor and a preparation method and application thereof. The nanowire-nanotube hybrid sensor has two regions of a nanochannel and a nanowire electrode by using a conical double-channel microcapillary. A substrate solution is precisely released to a specific site of a single cell through the nanochannel. After a to-be-measured glycosidase recognizes the substrate molecules, the glycosidic bond is cut to release active substances of the electrode. The nanowire electrode is used for real-time quantitative detection of the active substances, so that quantitative detection of glycosidase substances at a single / subcellular level is realized. The application constructs an efficient and universal detection strategy of non-electrochemical active glycosidase by using the nanowire-nanotube hybrid sensor and an electrical signal conversion method of the reaction of specific glycosidase and a substrate, widens the detection range of electrochemical target objects, and provides a promising method for high-time-space-resolution quantitative monitoring of hydrolytic enzymes at a single / subcellular level.

The invention relates to the technical field of nanometer material synthesis and catalysis, in particular to a gold nanocluster and a preparation method thereof, a catalyst and a preparation method and application of the catalyst. The molecular formula of the gold nanocluster is Au40 (TBBT) 24 (TPMP); wherein the TBBT is 4-tert-butyl thiophenol, and the TPMP is tri (m-phenyl) phosphine. According to the present invention, the gold nano-particles have the accurate number of atoms and the determined molecular structure, the synergistic effect of the mixed ligands (mercaptan and phosphine) on the surface of the gold atomic nucleus further regulates the electronic structure and the surface property of the cluster, and the adsorption and activation ability of the substrate molecule is optimized so as to improve the catalytic efficiency and the stability; especially for reduction reactions such as reduction of 4-nitrophenol, the cluster can realize efficient catalytic conversion under mild conditions.

A complex for a toehold exchange system is provided. The complex comprised a substrate molecule and an output molecule. The substrate molecule and output molecule each comprise: a plurality of complementary regions where the substrate molecule and the output molecule are hybridised; and a non-complementary region where the substrate molecule and output molecule are not hybridised, the non-complementary region being located between complementary regions. The substrate molecule comprises a first exposed toehold region for hybridisation to a catalyst molecule and a second covered toehold region for hybridisation to a fuel molecule, and wherein the second covered toehold region comprises the region of non- complementarity. A toehold exchange system comprising the complex is also provided.

The application discloses a kind of nano bubble regulated hydrogen bond organic framework immobilized enzyme, and hydrogen bond organic framework immobilized enzyme is prepared by in-situ self-assembly and embedding method in water environment containing nano bubble from four (4-amidinophenyl) methane and four (4-carboxyphenyl) methane.The hydrogen bond organic framework is used to realize the immobilization of enzyme by in-situ embedding method, and a multi-level pore immobilized enzyme system based on nano bubble is constructed.Nano bubble can expand the pore size and pore volume of hydrogen bond organic framework as pore-forming template, while maintaining the stability of enzyme structure, significantly improving the mass transfer rate of substrate molecules in the framework, thereby enhancing the catalytic activity and substrate affinity of immobilized enzyme.The method effectively improves the enzyme catalytic reaction efficiency while maintaining the system immobilization efficiency, pH stability, temperature stability and reusability.The process is simple and suitable for the construction of multi-level pore immobilized system for various enzymes.

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 present application discloses a method for detecting multiple biomarkers based on nanozyme chemiluminescence technology, the method comprising: preparing iron oxide nanoparticles as nanozyme cores, coating substrate molecules on the surface of nanoparticles to form nanozyme-substrate complexes; mixing the nanozyme-substrate complexes with the sample to be tested, incubating the mixture, and transferring the mixture to a microplate after adding a hydrogen peroxide solution to collect chemiluminescent signals using a microplate reader; extracting characteristic parameters of the collected luminescence curves including peak luminous intensity, time to peak, half-peak width, rate of rise, rate of decay, integrated intensity, and / or wavelength ratio; constructing and training a multi-layer neural network model to predict the concentrations of multiple biomarkers based on the characteristic parameters of the sample data. Through the scheme of the present application, multiple biomarkers can be detected simultaneously, thereby improving the accuracy of detection.

The invention relates to alkylguanine transferase substrate molecules. In general formula (I) SB is a moiety that can be enzymatically cleaved from the rest of the molecule by an enzyme having an alkyltransferase activity selected from the group consisting of a 2-aminopyrimidinyl moiety, an aminopyridinyl moiety, and a 2-aminopurinyl moiety. Also described are molecules of general formula (II) and general formula (III) L is an optional linker, RN is H, methyl or ethyl or their deuterated or fluorinated derivatives, and R is selected from a detectable label and a selectively reactive moiety.

This invention discloses an artificial intelligence-based method for targeted optimization of chitosanase, comprising: constructing a sequence-function-product standardized association dataset containing chitosanase amino acid sequence, substrate molecular structure, enzyme activity data, and product polymerization degree data; encoding the enzyme sequence using a protein language model and the substrate structure using a chemical language model to obtain enzyme sequence feature vectors and substrate structure feature vectors, and forming a multimodal fusion feature vector by concatenating the vectors; inputting the fusion features into an Extra Trees ensemble model for training to predict the probability of enzyme-substrate interaction, enzyme activity, and product polymerization degree; and performing targeted screening of target chitosanase and determining mutation sites based on the prediction results to obtain optimized mutants. This invention can significantly improve the efficiency and prediction accuracy of chitosanase modification, reduce experimental screening costs, and achieve efficient and accurate optimization of chitosanase.

The invention discloses a preparation method and application of a boric acid ester modified graphdiyne oxide wrapped gold nanosphere composite material. The preparation method comprises the steps of preparation of a thin graphdiyne oxide sheet, preparation of a graphdiyne oxide wrapped gold nanosphere composite material and preparation of the boric acid ester modified graphdiyne oxide wrapped gold nanosphere composite material. According to the invention, 4-aminophenylboronic acid pinacol ester is modified on a prepared graphdiyne oxide coated gold nanosphere composite material by utilizing a coupling reaction of carboxyl and amino, and an SERS detection material for H2O2 in living cells is constructed, so that high-sensitivity and high-specificity detection of H2O2 is realized. The material constructed by the invention has good biocompatibility and unique boric acid-phenol switch, has selective reaction on H2O2, can be used for specific detection of H2O2 in living cells, and can effectively overcome the problem of non-reproducibility of SERS (Surface Enhanced Raman Scattering) signals caused by non-uniform adsorption and irregular distribution of substrate molecules as an internal standard signal.

The application provides an enzyme reaction feasibility evaluation method and system based on multi-task and molecular multi-modal features. The application uses a public data set and a bioengineering reaction rule template library to construct an enzyme reaction feasibility data set; takes the SMILES sequence features and the Morgan fingerprint spatial structure features of the reaction product molecules and the substrate molecules as the inputs of a neural network; constructs a double-branch network based on an attention mechanism and a convolutional neural network to extract molecular multi-modal features; takes a product SMILES sequence generation task as an auxiliary task to strengthen the model learning sequence features, provides more abundant features for the enzyme reaction feasibility evaluation task, and effectively enables the trained model to make accurate judgments on the reaction feasibility by comprehensively considering the molecular multi-modal features. The application significantly improves the calculation speed and reliability in the bio-molecular retrosynthesis pathway design process, avoids unnecessary search expansion in the design process, and improves the experimental efficiency.

This invention belongs to the field of drug metabolism prediction technology, specifically relating to a method and system for predicting drug metabolites based on conditional generative adversarial networks (GANs). The method includes: extracting initial features of drug molecules and masking them, inputting them into a shared encoder to obtain a first encoding result; incorporating atomic position information into the first encoding result, decoding it, and then predicting the structure of the drug molecule; inputting reactant molecules into the shared encoder, inputting the obtained reactant features into a shared decoder, and predicting chemical reaction products; inputting substrate molecules into the shared encoder for encoding; fusing the substrate encoding result with the corresponding enzyme's amino acid sequence and inputting it into the shared decoder to predict metabolites; constructing a generator using the shared encoder and shared decoder, building a multi-task discriminator, and performing adversarial training on the generator and discriminator to obtain a prediction model for predicting metabolites. This invention improves prediction accuracy by fusing information from drug structure and enzymes to construct a prediction model.

The present application relates to the technical fields of serum creatinine detection and nanozyme preparation, and particularly relates to a double-ligand regulated Fe-MOF nanozyme and a preparation method and application thereof. The method comprises the following steps: FeCl3.6H2O, 1,10-phenanthroline and monocarboxylic acid ligand are dissolved in DMF to form solution A by stirring; terephthalic acid is dissolved in DMF to form solution B; solution B is added to solution A, ultrasonic dispersion is performed, and then the solution is transferred to a stainless steel high-pressure reaction kettle for high-temperature reaction; after the reaction is completed and cooled to room temperature, centrifugal washing and vacuum drying are performed to obtain a double-ligand regulated Fe-MOF nanozyme sample. As a ligand, n-butyric acid enhances the affinity to the substrate molecule; as a ligand, 1,10-phenanthroline increases the enzyme activity; the synergy of 1,10-phenanthroline and n-butyric acid achieves high sensitivity and specificity.

The invention discloses an axially chiral N-heterocyclic carbene ligand as well as a preparation method and application thereof. The axially chiral N-heterocyclic carbene ligand has a structure as shown in a general formula (I), wherein an axially chiral part A of the ligand is any one of A-1 or A-2; the part B of the ligand is any one of B-1 and B-2 or is the same as A; and the anion X part of the ligand is any one of chlorine, bromine, iodine, tetrafluoroborate or hexafluorophosphate. The axially chiral N-heterocyclic carbene ligand and a transition metal compound are subjected to in-situ complexation in a reaction system to form a complex catalyst, and the complex catalyst shows good yield and enantioselectivity in amylene amide substrate intramolecular amination and arylation reaction and has a good industrial application prospect. The invention belongs to the field of asymmetric synthetic chemistry.

The present invention provides a method for detecting two target molecules in a sample, both as individual molecules and in proximity, or interaction with one another. The method involves performing three separate assay reactions to detect the first and second target molecules, and their interaction, using proximity probes which are common between the three assay reactions, and nucleic acid reagents which interact with the probes. In particular the methods use unique nucleic acid substrate molecules, such as padlock probes, to detect probes bound to their target and to determine when probes for the two targets are in close proximity, indicating an interaction between the targets.

Bio-production processes that rely on biological activity can be very slow and inefficient, yet, the output of these processes may have significant value. Using biological enzymes outside their natural cellular environments offers a significant and largely untapped opportunity to enhance bio-production processes. By decoupling enzymes from their native contexts, one can modify both their sequences and structures in ways that are favorable for industrial applications. This system and method mixes substrate molecules, PPi, and enzymes that utilize PPi (PPi-dependent enzymes) in a reaction chamber and ends with stable-form products, including phosphorylated molecules.

The application relates to the field of biotechnology and discloses a single-point mutation method for improving the PS synthesis activity of phospholipase D. The activity center of ZET4 is determined through literature comparison, then PLD (2ZE4) is subjected to molecular docking with substrates PC and L-ser through AutoDock Vina, the binding sites of the substrate molecules and the enzyme molecules are determined, protein mutation design is carried out, primers are designed, and 14 mutant strains are constructed. The phospholipase D expressed by eight mutant strains improves the PS synthesis activity, the PS yield of T194A and T194L is increased from 27.46% to 53.52% and 49.23% respectively, the PS conversion rate of T194I, T194V, T194M, T194F, T194C and T194P is increased to different degrees, and the PS yield of T194I phospholipase D reaches 58.32%.