77 results about "Antibody antigen" patented technology

A protein interface prediction method based on three-track coding comprises the following steps: combining a fine-tuned protein language model SiteT5 with evolutionary, geometric and statistical features extracted from a sequence, sending the combined features into a three-track coding network, and integrating a cyclic gating module, a multi-resolution aggregation module and a long sequence deformation module to obtain a protein interface prediction model SiteT5; the method comprises the following steps: respectively capturing a time sequence relation, a local mode and long-range dependence among residues, respectively mapping the three codes into different weights, carrying out point multiplication on the three codes, and carrying out aggregation through a multi-view cross attention module; then the protein residues are sent to a three-layer hierarchical interactive learning module, local structure and global dependency are cooperatively mined through an eight-head gating self-attention module and a position-by-position feedforward module, and finally the probability that each protein residue is an interface is obtained through a classifier. According to the invention, a protein-DNA interface, a protein-RNA interface, a protein-protein interface and an antibody-antigen interface can be effectively captured. And the robustness is ensured, and meanwhile, relatively high prediction precision is also shown.

Antibodies, antigen-binding proteins and Fc-fusion proteins that comprise recombinant polypeptides containing a chimeric heavy chain constant region sequence are provided that bind to certain Fc receptors however have reduced effector functions. Methods of making constructs for expression of such chimeric Fc-containing antibodies, antigen-binding proteins and Fc-fusion proteins in cell systems, and methods of producing and isolating the chimeric Fc-containing proteins are provided.

The application discloses a kind of vibration device for immunofluorescence method, belong to medical detection device field, the device adopts cavity, vibration unit, cooling device and sound insulation cotton, sound insulation cotton is used to reduce noise in experimental process, cooling device reduces the heat generated due to vibration, avoid the heat generated by vibration to cause the influence to sample;After energization, vibration unit forms a kind of vibration source, the vibration of slide in incubation box in cavity is driven by vibration, and then promote the exposure of fixed antigen / antibody epitope on slide, accelerate and antibody / antigen in incubation sample are combined, shorten incubation time, improve experimental efficiency.

This disclosure provides methods and apparatus for generating training data, training machine learning models, and analyzing biological samples. Generating training data includes: acquiring a first image of a biological sample; generating a first set of annotations for the first image based on a second image of the biological sample stained by a quantitative method that converts antibody / antigen complexes into dots; and outputting the first image and a benchmark truth including the first set of annotations as data for training a first machine learning model (“ML”) to analyze the biological sample. Furthermore, the generated (output) training data can then be used to train the ML model, and the trained ML model can be used to analyze the biological sample.

The invention discloses an up-conversion nano-composite with a core-shell structure, a preparation method and application, and belongs to the technical field of biomedical bimodal nano-probes. According to the nanocomposite, up-conversion nanoparticles (UCNPs) serve as a core, metal-organic frameworks (MOFs) serve as a shell layer, horse radish peroxidase (HRP) is loaded on the shell layer, and UCNP (at) MOF / HRP is formed. Subsequent biological functional modification, such as coupling of an antibody, an antigen, nucleic acid and other substances, can be carried by an activating group or a metal coordination bond carried by a shell ligand of the upconversion nanocomposite MOF with the core-shell structure, so that the functions of specific recognition, targeted capture, specific loading and the like are realized.

The present disclosure addresses the problem of providing a therapeutic agent for a disease in which formation of tertiary lymphoid tissue occurs in a lesion.　This prophylactic or therapeutic agent for a disease in which formation of tertiary lymphoid tissue occurs in a lesion contains an anti-CD153 antibody having cytotoxicity or an antigen-binding fragment of the antibody.

Embodiments described herein relate to systems and methods for mapping molecules into interfaces. An example interface includes a visual interface having a map visualization. Example molecules include proteins, or any protein-like molecules or fragments thereof such as antibodies, antigens, proteins, lectins, receptors. Embodiments described herein relate to systems and methods for mapping molecules into interfaces by processing data using dimensionality reduction to generation representations of molecule maps (e.g. map visualizations).

Provided herein are antibodies, antigen-binding portions thereof, and antibody peptide conjugates that specifically bind to neuropilin-1 (NRP1) and various compositions of such antibodies, antigen-binding portions, and antibody-peptide conjugates. The disclosure also provides nucleic acids encoding the antibodies, antigen-binding portions thereof, or antibody peptide conjugates; cells comprising the nucleic acids; and methods for producing the antibodies, antigen-binding portions thereof, or antibody peptide conjugates. Also provided are methods for using the antibodies or antigen-binding portions thereof in therapeutics and diagnostics for cancer.

The invention relates to the technical field of biology, in particular to an SERS probe for Mfn2 detection, a preparation method of the SERS probe, an SERS sensor and application of the SERS sensor. Based on a surface enhanced Raman spectroscopy (SERS) technology, a gold nanoparticle SERS probe coated with an antibody 1 and a silver nanoparticle SERS probe coated with an antibody 2 are constructed, a sandwich structure is formed through combination of the antibody 1, an antigen and the antibody 2, the structure effectively improves SERS hot spot distribution and Mfn2 detection sensitivity, and traditional measurement steps are simplified. The constructed biologically coded SERS probe can be used for measuring Mfn2 with different concentrations. Based on the prepared SERS sensor, the dynamic measurement of the expression of the single living cell Mfn2 in the process of electrical stimulation of dental pulp stem cell odontogenic differentiation is realized, and the SERS sensor has wide clinical application prospect and transformation value in the aspects of measurement of protein molecules in a single cell organelle and diagnosis of Mfn2 related diseases.

Predictive models are deployed to generate epitope predictions (e.g., B-cell epitopes). Predictive models analyze structural features of a protein, such as an antibody, or an antibody-antigen pair, and can identify epitopes and paratopes.

The subject invention provides a composition comprising an enomomer which comprises a) a carrier molecule, and b) at least one aptamer, wherein the carrier molecule is an antibody, an antigen-binding moiety, a serum protein, an intracellular protein, a messenger RNA (mRNA) or human serum albumin.

The application provides a set of methods for constructing antigen-antibody complex mutual recognition interface descriptors (i.e., protein molecular fingerprints), which maximally present the structure and physicochemical characteristics of specific recognition by describing the binding interface of the three-dimensional structure of the antibody-antigen from both sides. Based on the protein molecular fingerprints generated by the set of methods, based on the specific interaction recognition rules of the antigen-antibody, the epitope prediction algorithm specific to the antibody and the virtual screening model of the antibody are designed, and the existing machine learning or deep learning tools are docked, so that the antigen epitope prediction based on the antibody and the high-throughput virtual screening of the antibody based on the specific epitope can be quickly realized.

Antibodies, antigen-binding fragments, and conjugates (e.g., antibody-drug conjugates) thereof that bind CD73 are disclosed. The disclosure further relates to methods and compositions for use in the treatment of, e.g., cancer by administering the compositions provided herein.

This provides methods and materials involved in binding a molecule (e.g., an antibody, a fragment of an antibody, an antibody domain, a chimeric antigen receptor (CAR), a cell engager, or an antibody-drug conjugate (ADC)) to a B7 homolog 3 (B7-H3) polypeptide (e.g., a human B7-H3 polypeptide). For example, binders (e.g., antibodies, antigen binding fragments, antibody domains, CARs, cell engagers, or ADCs) that bind to a B7-H3 polypeptide as well as methods and materials for using such binders to treat cancer are provided. Also provided are cells (e.g., host cells) designed to express one or more binders (e.g., antibodies, antigen binding fragments, antibody domains, CARs, or cell engagers) having the ability to bind to a B7-H3 polypeptide as well as methods and materials for using such cells to treat cancer.

Provided herein are methods and materials relating to binding conjugates (e.g., antibodies, antigen binding fragments, antibody domains, CARs, cell cement, and / or ADCs) to BAFF-R polypeptides. For example, provided herein are conjugates (e.g., antibodies, antigen-binding fragments, antibody domains, CARs, cell cement, and / or ADCs) that bind to BAFF-R polypeptides, and methods and materials for using one or more such binding molecules to treat mammals (e.g., humans) having a cancer (e.g., one or more B-cell carcinoma).

An embodiment provides a method for treating a body fluid of a patient with an inflammatory cytokine storm, including: removing the body fluid from a patient; applying a treatment to the body fluid, wherein the treatment comprises an antibody that joins with an antigen in the body fluid to form an antibody-antigen complex; removing the antibody-antigen complex from the body fluid; and returning the body fluid to the patient. Other aspects are described and claimed.

The invention discloses a chemiluminiscence detection reagent for detecting an HCV antibody and a use method of the chemiluminiscence detection reagent, and relates to the technical field of immunodetection. The detection reagent is combined with a sandwich method and an indirect method for detection. When in use, a sample is incubated with the first reagent and the sample treating fluid, so that the HCV antibody to be detected in the sample reacts with the HCV coating antigen in the first reagent to form an antigen-antibody compound; adding a second reagent, and reacting the formed antigen-antibody compound with the HCV labeled antigen labeled by acridinium ester and the anti-IgG antibody labeled by acridinium ester in the second reagent to form an antigen-antibody-antigen compound and an antigen-antibody-secondary antibody compound; and finally, adding excitation liquid to enable acridinium ester to emit light, and detecting the HCV antibody in the sample by detecting a light-emitting signal value. The technical scheme of the invention greatly improves the sensitivity and specificity of HCV antibody detection, and can be used for solving the problem of easy missing detection in HCV antibody detection.

This disclosure provides an anti-SIGLEC15 antibody, antigen-binding fragment, and the use thereof.

The present application belongs to the field of biosensing technology and tumor marker instant detection, and particularly relates to a preparation method of a human epididymis protein 4 (HE4) biosensor based on electrochemical principle and detection application thereof. The present application constructs an "antibody-antigen-antibody" sandwich complex structure, realizes simple, accurate and efficient detection of serum HE4; the KB-PEI@AuNPs composite material is used as a base material, which can effectively fix antibody molecules and promote electron transmission of the electrode interface, and significantly improves the conductive performance of the sensor; by using the specific binding principle of antigen and antibody, the CoFeZn-MOF prepared by the present application has peroxidase-like activity as a nanoenzyme; when the electrode modified by the probe CoFeZn-MOF / Ab2 is detected, the nanoenzyme can catalyze H2O2 to decompose to generate active oxygen substances such as hydroxyl radicals; this redox process triggers electron transfer, thereby causing a change in the current signal, thereby exhibiting i-t rapid response characteristics, high sensitivity performance and a lower detection limit.

Provided are antibodies or antigen-binding fragments that specifically recognize human liver-intestine cadherin, and the pharmaceutical use thereof.The antibody or antigen-binding fragment containing specific amino acid sequences. The antibody or the antigen-binding fragment thereof has high specificity and affinity to liver-intestine cadherin, and can mediate the killing of liver-intestine cadherin expressing cells. Therefore, further relates to a pharmaceutical composition comprising the antibody or the antigen-binding fragment thereof, and use thereof in the preparation of medicament for the prevention and / or treatment of tumors.

Characterization of the binding dynamics at the interface between any two proteins that specifically interact plays a role in myriad biomedical applications. The methods disclosed herein provide for the high-throughput characterization of the specific interaction at the interface between two protein binding partners and the identification of functionally significant mutations of one or both protein binding partners. For example, the methods disclosed herein may be useful for epitope and paratope mapping of an antibody-antigen pair, which is useful for the discovery and development of novel therapies, vaccines, diagnostics, among other biomedical applications.

The invention relates to anti-PD-1 antibody binding domains which do not disrupt signaling between PD1 and PD-L1, and immunoconjugates comprising same targeting an immunomodulatory domain to PD-1-expressing cells.

Disclosed are anti-human GAS6 antibodies, antigen-binding fragments, and uses thereof.

The invention relates to a nanometer antibody and antigen interaction prediction method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a to-be-detected nano antibody sequence and a to-be-detected antigen sequence; according to the to-be-detected nano-antibody sequence and the to-be-detected antigen sequence, utilizing a first embedding generator to respectively generate a nano-antibody embedding vector and an antigen embedding vector; according to the to-be-detected nano-antibody sequence and the to-be-detected antigen sequence, generating a nano-antibody antigen pair embedding vector by using a second embedding generator; fusing the nano-antibody embedded vector and the nano-antibody antigen pair embedded vector to obtain a nano-antibody fusion feature, and fusing the antigen embedded vector and the nano-antibody antigen pair embedded vector to obtain an antigen fusion feature; and predicting the interaction between the to-be-detected nano-antibody sequence and the to-be-detected antigen sequence according to the nano-antibody fusion characteristics and the antigen fusion characteristics. By adopting the method, the accuracy of predicting the interaction between the nano antibody and the antigen can be improved.

This article provides methods and compositions for improving the crystallization of antibodies, antigen-binding fragments (e.g., Fab or Fab') or fusion proteins and Fab / Fab' / mAb:antigen complexes.

Antibodies and antigen binding fragments that specifically bind to gp120 and neutralize HIV-1 are disclosed. Nucleic acids encoding these antibodies, vectors and host cells are also provided. Methods for detecting HIV-1 using these antibodies are disclosed. In addition, the use of these antibodies, antigen binding fragment, nucleic acids and vectors to prevent and / or treat an HIV-1 infection is disclosed.

The invention discloses a bigeminy immunoassay kit for detecting an HPV (human papillomavirus) antibody and a preparation method of the bigeminy immunoassay kit, relates to the field of biomedicine, and is characterized in that the bigeminy immunoassay kit for detecting the HPV antibody and the preparation method of the bigeminy immunoassay kit are provided. The magnetic microspheres for detecting the neutralizing antibodies of the human papilloma viruses 16 and 18 are coated with an HPV16 antibody and an HPV18 antigen, acridinium ester is used for marking the HPV16 antigen and the HPV18 antibody, an in-vitro diagnostic kit for detecting the neutralizing antibodies of the human papilloma viruses 16 and 18 is established on the basis, and a chemiluminescence immunoassay method is combined for analysis. The bigeminy immunoassay kit for quantitative detection of the HPV antibody is high in sensitivity, good in specificity, simple and convenient to operate and appropriate in price.

The present disclosure encompasses novel anti-NGF antibodies, antigen binding proteins and polynucleotides encoding the same. The disclosure further provides use of the novel antibodies, antigen binding proteins and / or nucleotide of the invention for the treatment of NGF related disorders, particularly in for the management of pain.

The invention belongs to the field of biological medicine, and provides a method and a model for predicting the antibody-antigen binding possibility based on expansion convolution and a channel attention mechanism and application of the method and the model. According to the method, antibody-antigen binding possibility prediction is carried out based on expansion convolution and a channel attention mechanism, a deep learning model is constructed by collecting a training data set, expansion convolution is introduced in training to expand a receptive field, and feature expression ability is enhanced in combination with the channel attention mechanism, so that efficient prediction is realized. According to the method, the receptive field is effectively expanded through expansion convolution to capture long sequence dependence, key features are self-adaptively enhanced in combination with a channel attention mechanism, the prediction accuracy is remarkably improved under the condition of limited labeled data, and the method can be widely applied to the fields of antibody screening, drug design, immunotherapy and the like.