18 results about "Protein solubility" patented technology

The invention relates to a protein solubility prediction method and system based on GCN and an improved attention network. The method comprises the following steps: constructing a protein sequence data set; the method comprises the following steps: acquiring a protein three-dimensional structure file through AlphaFold3, and constructing a node feature vector; extracting position embedding, bidirectional projection direction features, a cross-node atom pair distance and a rotation relation, and constructing an edge feature vector; extracting global physicochemical property feature vectors of the protein; and constructing protein graph structure data, inputting the data to the graph convolutional network module and the improved graph attention network module, and performing training to obtain a graph convolutional network and an improved attention network model to perform protein solubility prediction. By extracting node and edge features and protein global physicochemical property features, subsequent model training is facilitated; and the two-way projection and the rotation relation enable the model to accurately sense the spatial orientation between residues, so that the model has more quantitative understanding on the protein folding and gathering driving force, and the accuracy of protein solubility prediction is improved.

The invention discloses a construction method of a protein solubility capability prediction model, a protein solubility capability prediction method and a prediction device, and relates to the field of protein solubility capability prediction. According to the method, the accuracy, the adaptability, the practicability and the automatic integration capability of the model are remarkably improved in a protein solubility capability prediction task, multiple limitations in data quality, generalization capability, calculation cost and practical application in the prior art are overcome, and the method has good popularization prospects and industrial conversion values.

This invention provides material compositions and / or methods suitable for the prevention and / or treatment of protein depletion (protein deficiency), comprising material compositions that preserve the natural function of peptides / proteins while limiting and / or preventing the formation and / or aggregation of said peptides / proteins into amyloid protein. It also provides material compositions and formulations for enhancing peptide / protein solubility, stability, cycle time, receptor interaction, brain permeability, CSF half-life, and promoting peptide / protein synthesis and purification.

The invention discloses a preparation method of ultrasonic-heat treatment synergistically modified flaxseed protein and application of the flaxseed protein in ice cream. The method comprises the following steps: (1) degumming pretreatment of flaxseed cake meal; (2) flaxseed protein extraction; and (3) ultrasonic-heat treatment synergistic modification. The synergistic effect of ultrasonic and heat treatment can destroy the compact structure of flaxseed protein and expose more hydrophilic groups and hydrophobic groups, so that the solubility of the protein is improved to 80% or above, the emulsifying activity index is improved by 40% or above compared with that of natural protein, and the emulsion is still stable after being stored at 4 DEG C for 30 days; when the modified flaxseed protein is applied to the ice cream, the expansion rate of the product can be increased by 15-20%, the melting rate can be reduced by 25% or above, the hardness is moderate, the taste is smooth, and meanwhile the nutritional additional value of the product is increased. According to the method, resource upgrading of the flaxseed cakes is realized, low-price byproducts are converted into high-added-value food ingredients, the industrial chain of flaxseeds is prolonged, and the comprehensive benefits of the industry are improved.

The application belongs to the field of biological medicine, and particularly relates to a catalytic antibody mutant for degrading Helicobacter pylori urease, and a preparation method and application thereof. The application takes wild-type catalytic antibody Ua15-L (WT) for degrading Helicobacter pylori urease as a starting antibody, rationally designs a catalytic antibody mutant for degrading Helicobacter pylori urease with better performance, and verifies through experiments that the I48C-G64C mutant is mutated at the 48th and 64th amino acids, and is mutated from isoleucine and glycine to cysteine, so that a disulfide bond is formed between the two, which is helpful to improve the thermal stability of the catalytic antibody. On this basis, the mutations L9E, L54R and T14Q-I15P are introduced to increase the protein solubility and expression amount. Compared with the wild-type catalytic antibody for degrading Helicobacter pylori urease, the mutant 1 (L9E-I48C-G64C) increases the Tm value by 6 DEG C, increases the solubility by 81%, and increases the expression amount by 4 times; and the time for the urease fragment to be hydrolyzed by half at 37 DEG C is shortened by 52% compared with the wild type.

The invention relates to a method of treating a material comprising corn protein with a protein deamidase. The enzyme treated material has improved water holding capacity, emulsifying capacity and / or improved corn protein solubility compared to a material obtained using the same method but without the protein deamidase.

This application relates to the field of antibody technology, specifically providing a truncated fragment of the African swine fever virus pB602L protein, an antibody thereof, or an antigen-binding fragment thereof, and their applications. The truncated fragment, encoded by SEQ ID NO.1, eliminates mismatched disulfide bonds and repetitive sequences by deleting the first 200 amino acids from the N-terminus, thereby improving protein solubility and immunogenicity. The antibody thereof or its antigen-binding fragment contains the heavy chain variable region shown in SEQ ID NO.2 and the light chain variable region shown in SEQ ID NO.4, exhibiting a blocking rate of greater than 90% against the pB602L protein. This truncated fragment and antibody demonstrate high specificity and sensitivity, and can be used for the detection, diagnosis, and evaluation of vaccine immunization efficacy for African swine fever virus, providing an important tool for the prevention and control of African swine fever.

The invention relates to a protein solubility prediction method and device based on deep learning, computer equipment and a storage medium, and the method comprises the steps: obtaining a to-be-predicted sample which is a protein amino acid sequence; according to an ESM-2 model and the to-be-predicted sample, a high-dimensional feature vector is obtained, and each feature dimension of the high-dimensional feature vector corresponds to an abstract representation component of a protein sequence in a semantic space of the ESM-2 model; obtaining a protein solubility prediction probability according to the high-dimensional feature vector and a depth residual multi-layer perceptron model; and obtaining a protein solubility prediction result according to the protein solubility prediction probability. The accuracy of protein solubility prediction can be improved.

The embodiment of the invention discloses medicago sativa functional protein powder and a preparation method thereof. The protein content of the alfalfa functional protein powder is greater than or equal to 85%, the protein solubility is 92-95%, the emulsifying activity is greater than or equal to 70%, and the foamability is greater than or equal to 450%; the activity of superoxide dismutase (SOD) is larger than or equal to 250 U / g, the polysaccharide content of the ganoderma lucidum is larger than or equal to 2.0 mg / g, and the flavone retention rate is larger than or equal to 90%. According to the preparation method, a brand new fermentation system is constructed by introducing artificial ganoderma lucidum life active bacteria, and ultrasonic-enzymolysis synergistic extraction and low-temperature freeze-drying coupling drying processes are combined, so that the alfalfa functional protein powder with high protein content, high-activity metabolites and high functional characteristics is prepared; the problems that existing alfalfa protein powder is low in extraction rate, poor in activity and free of unique functions are solved.

This invention relates to a method for evaluating the spectra of biological material of animal, plant, or mixture thereof, the method comprising the steps of: a) detecting spectrometers in a network formed by at least one spectrometer and an input / output device; b) requesting the respective status of each spectrometer in the network of step a), and displaying the detected spectrometers and their status on the input / output device, wherein the status reflects whether the spectrometer is available for recording spectra; c) receiving a selection from spectrometers available for recording spectra on the input / output device; d) recording the spectrum of the sample material of animal, plant, or mixture thereof on the spectrometer selected in step c); e) predicting at least one parameter from the spectrum of step d) using at least one calibration function and / or calibration plot suitable for predicting the value of the parameter. The values ​​of the parameters, wherein the at least one parameter is selected from the content of at least one amino acid, crude protein content, ammonia content, content of all amino acids containing ammonia, content of all amino acids not containing ammonia, crude fat content, dry matter content, crude ash content, energy content, content of at least one biogenic amine, content of at least one anti-nutritional factor, content of at least one sugar, starch content, crude fiber content, neutral detergent fiber content, acid detergent fiber content, total phosphorus content, phytic acid phosphorus content, reactive lysine content, total lysine content, ratio of reactive lysine content to total lysine content, protein dispersibility index, protein solubility, trypsin inhibitor activity, urease activity, and processing condition index (PCI); and f) displaying the predicted results of step e) on the input / output device.

A photosynthetic microorganism-derived food ingredient composition is provided, wherein the composition has a protein content of at least 40%, wherein the composition has a protein solubility of at least 50%, further wherein the composition has a whiteness index of at least 50. Also provided are methods of adjusting the colour of photosynthetic microorganism biomass, and food ingredient compositions comprising a blend of a proteinaceous photosynthetic microorganism-derived fraction and one or more proteinaceous fractions of dairy, egg, fungi, animal or plant origin.

The application relates to the technical field of grain beverage processing, and discloses a preparation method of rice milk slurry with heat stability, which comprises the following steps: crushing rice into 100-mesh screen, preparing 15%-25% rice slurry, and adjusting pH to 6.0-6.6; two-stage enzymolysis: first, adding 0.02%-0.04% medium-temperature alpha-amylase, and keeping 80-95 DEG C for 5-15 min; cooling to 65 DEG C, then adding 0.03%-0.08% enzyme, and reacting at 65-72 DEG C for 1-3 h; high-temperature shearing at 125-135 DEG C for 30-60 s, and cooling to obtain the slurry. The whole pretreatment process is composed of two-stage enzymolysis + high-temperature shearing after enzyme inactivation, the two-stage enzymolysis eliminates secondary starch gelatinization, the high-temperature shearing improves protein solubility, and the UHT paste tube problem of rice milk slurry caused by secondary starch gelatinization and protein precipitation is solved.

The utility model provides a high-pressure jet Venturi tube for improving the solubility of rice protein, and belongs to the technical field of food processing equipment. Comprising a main venturi tube; the auxiliary venturi tube is arranged at the inner left part of the main venturi tube; the gas-liquid mixing chamber is formed in the right part in the main Venturi tube; the zigzag spoilers are annularly connected to the inner wall of the gas-liquid mixing chamber; the honeycomb-shaped micro-pore plate is arranged on the right side of the sawtooth-shaped spoiler, and a plurality of hexagonal honeycomb runner holes are formed in the surface of the honeycomb-shaped micro-pore plate; the nozzle cap is connected to the right end of the main Venturi tube, and a nozzle opening is formed in the right end of the nozzle cap; according to the method, the shearing efficiency is enhanced by utilizing instantaneous ultrahigh pressure generated by collapse of microbubbles, so that the rice protein aggregate is efficiently crushed, the protein is protected by utilizing inert gas and is prevented from being oxidized in the modification process, and finally, the protein is sprayed out from a nozzle opening, so that the protein structure is expanded, more hydrophilic groups are exposed, and the solubility of the protein is improved.

The invention provides a preparation method of soybean protein isolate with low beany flavor and high water solution transparency, which comprises the following steps: carrying out hot steam heat treatment on defatted soybean meal to obtain defatted soybean meal subjected to heat treatment; desalted water is added into the degreased soybean meal subjected to heat treatment for protein extraction; after extraction, centrifuging to remove bean dregs, adding sodium pyrosulfite into the extract, adjusting the pH value, centrifuging, and precipitating to obtain protein curd; redissolving the protein curd with water to obtain protein liquid; and mixing the protein liquid with compound protease, performing sterilization, flash evaporation and homogenization treatment, and performing spray drying, thereby obtaining the product. The defatted soybean meal is subjected to superheated steam pretreatment and high-temperature instantaneous treatment to inactivate lipoxygenase and the like, so that beany flavor substances generated by oxidation in the subsequent process are greatly reduced; the added sodium pyrosulfite inhibits the activity of polyphenol oxidase to realize soybean protein bleaching, and the whiteness of the product is improved; the protein solubility and emulsification stability are improved through a compound proteolysis process, and the transparency of the product is improved.

The application discloses a south heaven lotus seed protein with antioxidant efficacy and a preparation method thereof, and belongs to the technical field of plant protein extraction and bioactive functional material. The south heaven lotus seed protein is prepared from dried seeds of south heaven lotus seed as raw materials through the following steps: crushing and degreasing, weak base buffer solution dissolution, auxiliary agent synergistic reaction, acid precipitation and purification, low-temperature redissolution, freezing concentration and vacuum drying. The south heaven lotus seed protein with high activity is prepared. The protein intermolecular disulfide bond is broken and the protein binding network is broken through sodium sulfite and polysaccharide auxiliary agent, and segmented temperature control reaction and low-temperature post-treatment process are matched, so that the extraction rate and the product purity of the south heaven lotus seed protein are greatly improved, the protein antioxidant activity is maximally reserved, the antioxidant performance is obviously better than that of a product prepared by a traditional process, the protein solubility and the storage stability are excellent, and the south heaven lotus seed protein can be widely applied to the fields of functional food, nutritional health-care products, antioxidant skin care raw materials and the like.

A turkey collagen hydrolysate composition is prepared from turkey collagen sources, wherein the composition has: a protein concentration of from about 80 wt % to 100 wt %; a protein molecular weight distribution wherein from about 80% to 100% of the protein in the turkey collagen hydrolysate composition has a molecular weight of from about 500 to about 15,000 Daltons; a protein solubility of from about 97% to 100% at a pH selected from the group consisting of pH 7.0, pH 3.4, pH 5, and all of pH 7.0, pH 5, and pH 3.4; and a protein amino acid content of 3 to 25 glycine (g / 100 g sample), 0.5 to 15 hydroxyproline (g / 100 g sample), 1 to 18 proline (g / 100 g sample), 0.02 to 4 taurine (g / 100 g sample), and 0.05 to 3 tryptophan (g / 100 g sample). Methods of preparing turkey collagen hydrolysate compositions are described.

The application discloses a protein solubility prediction method and system based on deep learning, and belongs to the technical field of bioinformatics and artificial intelligence. The method comprises the following steps: firstly, an ESMC-300M large-scale protein language model is applied to capture deep evolution and structure information; a "BiLSTM-MultiCNN-Attention" multi-scale feature extraction architecture is designed; a bilinear pooling technology is introduced to model the high-order interaction between the beginning and the end of the sequence; a five-way feature fusion strategy and layer normalization are adopted to unify the feature distribution; and a class balance loss, gradient clipping and other robust training strategies are adopted to improve the stability of the model. In the test, the accuracy of the method reaches 74.78%, and the Matthews correlation coefficient is 0.4963, which is significantly higher than that of the existing method; and the calculation efficiency is optimized. The method can be widely applied to the fields of biopharmaceutical research and development, synthetic biology metabolic pathway optimization, precision medical individualized drug design and agricultural biotechnology stress-resistant crop development, and provides efficient and accurate technical support for protein engineering and drug research and development.

This invention belongs to the field of bioinformatics and relates to a method, apparatus, and medium for predicting the impact of amino acid variations on protein solubility: The method involves acquiring mutated amino acids and their feature value sets from a dataset; inputting the feature values ​​from the feature value sets into a three-classification module, which outputs a first probability vector indicating that the mutated amino acid belongs to different predicted categories; inputting the feature values ​​from the feature value sets into three two-layer three-classification modules corresponding to different predicted categories, and based on the outputs of each two-layer three-classification module, obtaining a second, third, and fourth probability vector indicating that the mutated amino acid belongs to different predicted categories; and inputting the first, second, third, and fourth probability vectors into a meta-learner, which outputs the predicted category of the mutated amino acid. This scheme, based on a multi-layer stacking strategy, constructs a prediction model that covers all possible binary and three-class classifications, exhibiting high prediction accuracy and efficiency.