16 results about "Process protein" patented technology

Protein-rich nutrient supplements and animal feed supplements derived from an anaerobic bacterial process are generated through a myriad of cell rupturing and protein fractionation / purification processes. Bacterial fermentation systems and methods of obtaining one or more protein-containing portions from a fermentation process using carbon monoxide-containing gaseous substrates are provided. The invention further provides compositions of protein-rich nutrient supplements with useful applications for intake by a variety of different animals and humans.

The invention relates to a one-button automatic molecular dynamics simulation system and an operation method thereof, the system comprises three parts: a back-end program module, a front-end application module with a graphic operation interface and a simulation result output module, and the back-end program module is linked with the front-end application module through an application programming interface. Molecular dynamics simulation analysis results of protein-protein, protein-polypeptide and protein-small molecule complexes can be automatically obtained in a one-button mode by inputting molecular dynamics simulation type parameters and processed protein and ligand files into a front-end application module with a graphic operation interface. Compared with an existing method which needs to highly depend on code programming, the molecular dynamics simulation system and the operation method thereof achieve operation automation of data processing and result output operation, have the advantages of being time-saving, efficient and high in accuracy, improve the research and development efficiency and reduce the development cost. The method has important application value in the fields of medical drug development and agricultural biological breeding research and development.

The application relates to a protein sample processing method, comprising the following steps: mixing a protein sample with an alkylating agent to seal free cysteine, obtaining a sealed sample; centrifuging the sealed sample through an ultrafiltration membrane, obtaining a membrane sample; the pore size of the ultrafiltration membrane ranges from 10 kDa to 30 kDa; performing first reduction on the membrane sample, obtaining a first reduced sample; adding a biotin labeling agent to the first reduced sample, obtaining a labeled sample; enzymatically digesting the labeled sample, obtaining an enzymatically digested sample; adding avidin microbead agarose to the enzymatically digested sample to adsorb biotin-labeled proteins, obtaining an enriched sample; performing reduction and alkylization on the enriched sample, obtaining a processed sample.

The application discloses a kind of magnetic nanomaterials for targeting enrichment protein and protein sample processing method using the magnetic nanomaterials, and nanomaterial has shell-core structure, inner core is ferroferric oxide magnetic nanoparticle, i.e.magnetic core, outer shell is mesoporous titanium dioxide, mesoporous titanium dioxide is coated on the surface of magnetic core, the mesoporous titanium dioxide has multiple nanopores, can be modified by molecular glue, can specifically bind target protein, when processing protein sample, magnetic nanomaterial is introduced into the complex biological sample containing protein, nucleic acid and salt, and magnetic nanomaterial selectively binds target protein, both can separate the required target protein, obtain peptide segment after digestion elution, and be used for proteomics data acquisition and analysis, the material and method of the application can improve protein fixation recovery efficiency before proteomics determination, save sample, save time and reduce cost.

The application discloses an enzyme turnover number prediction method based on a deep learning model and protein structure information, and the method comprises the following steps: constructing a dataset with unique enzyme sequence-enzyme structure-substrate combination and enzyme turnover number mapping in an offline stage, and training an enzyme turnover number prediction model; and in an online stage, real-time prediction of enzyme turnover number of a to-be-processed protein structure is realized through the trained enzyme turnover number prediction model. By adding protein structure information to enzyme turnover number prediction training and using a deep learning method to mine the potential relationship between the two, the model generalization effect can be effectively enhanced, and the problems of low prediction model accuracy and limitation to sequence similarity in the prior art are solved.

The application provides a protein structure prediction model training method and a protein structure prediction method, and relates to the technical field of computers. The protein structure prediction method and the protein structure prediction method provided by the application are characterized in that each amino acid sequence sample in a training data set has a first feature matrix and a second feature matrix, the first feature matrix and the second feature matrix of each amino acid sequence sample are used as a basis, and a knowledge distillation method is adopted to jointly train a feature enhancement network and a structure prediction network contained in a protein structure prediction model by means of an auxiliary training classification network. The obtained protein structure prediction model can be used to predict the structure of a to-be-processed protein based on a low-quality feature representation matrix of the to-be-processed protein, and a protein result prediction result with high precision can be obtained, thereby improving the prediction accuracy of protein structure prediction.

The application belongs to the field of protein engineering, and particularly relates to an enzyme optimum pH prediction method based on enzyme active sites and secondary loss; the method comprises the following steps: processing protein sequences of enzymes in a training set by using a GraphEC model to obtain activity values of each amino acid; extracting protein physicochemical characteristics of the protein sequences of the enzymes and processing the same, performing average pooling on the processed characteristics to obtain EMS2 representation and ESMC representation; performing weighted pooling processing on the EMS2 representation by using the activity values of the amino acids to obtain weighted EMS2 representation; fusing the protein physicochemical characteristics, the EMS2 representation, the ESMC representation and the weighted EMS2 representation to obtain joint features; inputting the joint features into a prediction network for processing to obtain enzyme optimum pH prediction results; calculating model total loss and adjusting model parameters according to the model total loss to complete training of the model; and the application greatly improves the prediction accuracy of enzyme optimum pH and has good application prospect.

The application discloses a kind of high-activity immune regulation bovine spleen peptide directional enzymatic preparation method, with slaughter waste bovine spleen as raw material, in turn through supermicro crushing coupling supercritical CO2 low-temperature degreasing, weak alkaline pH controllable aqueous extraction, four-element composite protease directional enzymolysis, activated carbon-yeast two-phase composite deodorization, multistage sterile filtration, double-effect low-temperature vacuum concentration, instantaneous temperature control spray drying preparation finished product;The application specific proportion four-enzyme fractional hydrolysis system and step-by-step coupling deodorization process, four enzymes are compounded according to (2-3) :(3-4) :1:1 to realize macromolecule pre-cut, immune characteristic peptide site retention, low-temperature adsorption is combined with yeast intracellular enzyme conversion to completely remove two kinds of fishy and bitter substances.The obtained product small molecule peptide ratio ≥90%, immunological activity is 35% higher than traditional process, fishy smell ≤1 level.The whole process protein extraction rate ≥88%, suitable for large-scale production, no irritating odor.

The present invention relates to extracting and processing protein concentrates, isolates, and a protein-fiber fraction from cluster bean, also known as guar beans (botanical name Cyamopsis tetragonoloba). The disclosed hexane-free, aqueous-ethanol extraction process, combined with controlled low-temperature (<75 °C) vacuum desolventization to preserve light color, bland flavor, and protein functionality, provides a sustainable, clean-label method for producing cluster bean protein concentrates and isolates suitable for direct human foods. This approach avoids the high heat and reverse-polarity extraction seen in prior art and enables food-grade, industrially scalable CPC and CPI.

This invention provides a method for producing processed proteins that enhance the cross-linking effect of proteins. [Solution] A method for producing a processed protein is provided, comprising a crosslinking step of reacting a protein with laccase and transglutaminase, wherein the protein is soy protein, tofu, or fermented soy milk.

The application discloses a kind of accurate control method of pea protein powder flying, comprising: first receiving module, air flow rate detection module, dust particle size detection module, dust concentration detection module, first processing module, second processing module, control module, second receiving module, analysis module;While providing a kind of accurate control method of preventing pea protein powder flying, solve the problem of dust flying in the prior art in the process of processing protein powder, dust flying problem is serious, the pollution to environment and the influence to staff's health are serious, the present application can accurately locate pea protein powder flying area, and according to the dust particle size characteristics of positioning area, proportion corresponding concentration dust suppressant, improve the effect of inhibiting dust flying, by obtaining optimum dust particle size to carry out concentration proportioning of dust suppressant, different particle size dust in range can be used optimum concentration dust suppressant, so that the inhibiting effect is more rapid and accurate.

This application discloses a method for processing protein samples for mass spectrometry detection. The method involves processing the protein sample into peptides using only ultrasound to obtain a protein sample suitable for mass spectrometry detection, without the use of enzymatic digestion. By precisely controlling the power, time, and mode of ultrasound, the high shear force generated by ultrasonic cavitation directly acts on the peptide bonds of the protein, achieving random and non-specific breakage. This method significantly reduces the protein sample pretreatment time from hours in existing enzymatic methods to minutes, eliminates the need for expensive enzymes, significantly reduces detection costs, simplifies the operation process, and can generate peptides of varying lengths covering the entire protein sequence, providing complementary protein sequence coverage information to enzymatic methods. This offers a novel and efficient solution for protein identification and structural analysis.

The embodiment of the invention discloses a protein denoising method and device, a storage medium and a program product, and at least relates to technologies such as artificial intelligence. Through the method, the prediction precision of protein properties can be improved, and the generalization ability of the model in scenes of new protein and the like is enhanced. The method comprises the following steps: acquiring a to-be-processed protein sequence; the to-be-processed protein sequence is processed on the basis of a protein language model, a first evolution sequence including N evolution probabilities is obtained, and each evolution probability is used for representing the mutation probability of multiple amino acids; performing noise adding processing on a target attribute probability in the N evolution probabilities and the T time steps in a sorting space to obtain a second evolution sequence, and performing denoising processing on the second evolution sequence and the to-be-processed protein sequence in a likelihood space to obtain a target attribute sequence corresponding to the target attribute probability, the method is used for predicting the property of the to-be-processed protein sequence.

This utility model provides a screening machine for processing protein mulberry leaf powder, relating to the field of protein mulberry leaf powder processing technology. It includes a screening machine body and a filter assembly. The filter assembly is installed on one side of the screening machine body. The filter assembly includes a filter device body threadedly connected to the surface of the screening machine body. A medium-efficiency filter plate is slidably connected to the inner side of the filter device body. During the screening process, the generated dust is drawn into the filter device body by a fan through the air inlet. The dust-laden air first advances along the connecting channel. When passing through the medium-efficiency filter plate, larger dust particles are effectively intercepted. Subsequently, the preliminarily purified air continues to flow to the high-efficiency filter plate, where even finer particles are efficiently captured. Finally, the clean air is discharged from the air outlet. This dual-layer filtration mechanism not only greatly reduces the potential health threat of dust to workers but also avoids pollution of the external environment caused by dust emissions.

The application provides a food and medicine health-care product processing protein wastewater treatment system, which comprises a storage assembly, a power assembly and a treatment assembly; the storage assembly comprises a treatment tank, a liquid discharge pipe is fixedly connected to the upper portion of the treatment tank, a liquid inlet pipe is fixedly connected to the lower portion of the treatment tank, and a storage tank is fixedly connected to the treatment tank; the power assembly comprises a motor, the motor is connected to the treatment tank, and the output shaft of the motor is connected to a driving bevel gear. The application relates to the technical field of wastewater treatment, in particular to a food and medicine health-care product processing protein wastewater treatment system. The application is developed in view of the deficiencies of the prior art, and the food and medicine health-care product processing protein wastewater treatment system can conveniently realize protein wastewater treatment, can make the medicine liquid and the local area water mix and then be discharged, can realize uniform stirring, can avoid that the protein precipitate is attached to the tank wall and the tank bottom of the treatment tank, and can conveniently realize the separation and discharge of the wastewater and the protein precipitate.

The invention provides a hydrolysis device for protein powder feed processing, and relates to the technical field of protein powder feed processing.The hydrolysis device comprises a hydrolysis box and a plurality of supporting feet, the supporting feet are fixedly installed on the hydrolysis box, a stirring paddle is rotationally arranged in an inner cavity of the hydrolysis box in a sealed mode, and a first gear is arranged at the end of one side of the stirring paddle; a second gear is arranged on one side of the first gear in a meshed mode, a first rotating column is arranged on the second gear, a motor is arranged on the first rotating column, a feeding port and a discharging port are formed in the upper side and the lower side of the hydrolysis box correspondingly, and electromagnetic valves are arranged in the feeding port and the discharging port correspondingly; the problems of non-uniform temperature and low heat efficiency of a traditional heating mode are effectively solved, and the hydrolysis efficiency and the product quality are remarkably improved.