1558 results about "Drug target" patented technology

Methods are provided for diagnosis and prognosis of disease by analyzing expression of a set of genes obtained from single cell analysis. Classification allows optimization of treatment, and determination of whether on whether to proceed with a specific therapy, and how to optimize dose, choice of treatment, and the like. Single cell analysis also provides for the identification and development of therapies which target mutations and / or pathways in disease-state cells.

The present invention provides methods for identifying targets of a drug in a cell by comparing (i) the effects of the drug on a wild-type cell, (ii) the effects on a wild-type cell of modifications to a putative target of the drug, and (iii) the effects of the drug on a wild-type cell which has had the putative target modified of the drug. In various embodiments, the effects on the cell can be determined by measuring gene expression, protein abundances, protein activities, or a combination of such measurements. In various embodiments, modifications to a putative target in the cell can be made by modifications to the genes encoding the target, modification to abundances of RNAs encoding the target, modifications to abundances of target proteins, or modifications to activities of the target proteins. The present invention also provides methods for drug development based on the methods for identifying drug targets.

Immunogenic compositions and prophylactic or therapeutic vaccines for use in protecting and treating against human cytomegalovirus (CMV) are disclosed. Subunit vaccines comprising a human CMV protein complex comprising pUL128 or pUL130, and nucleic acid vaccines comprising at least one nucleic acid encoding a CMV protein complex comprising pUL128 or pUL130 are described. Also disclosed are therapeutic antibodies reactive against a CMV protein complex comprising pUL128 or pUL130, as well as methods for screening compounds that inhibit CMV infection of epithelial and endothelial cells, methods for immunizing a subject against CMV infection, methods for determining the capability of neutralizing antibodies to inhibit human CMV infection of cell types other than fibroblasts, and methods of diminishing an CMV infection.

The present invention is directed to a novel Afx response element comprising the nucleotide sequence AACATGTT, said nucleotide sequence having a DNA binding site for the human fork head transkription factor Afx. The invention also relates to the use of the Afx response element in the screening for genes as diabetes drug targets and in the bioinformatic analysis of the human genome, said genes in turn being useful in other screening methods for compounds modifying the insulin receptor signaling pathway. A further aspect of the invention is a vector construct comprising the novel nucleotide sequence, a host cell transformed with said vector construct as well as the fusion protein expressed by said host cell.

A nucleic acid probe or a novel set of such probes in a microarray is provided. The probe or probe set is useful in the prognosis of patients with clear cell renal cell carcinoma (CC-RCC), wherein aggressive and non-agressive CC-RCC tumor types are characterized by differential expression profiles of genes that hybridize with one or more of these probes. Microarrays and kits

The present invention provides users with cloud-based high throughput computing system for integrative analyses of next generation sequencing genomic data, such that human cancer biomarkers and drug targets can be accurately and quickly identified. Advantageously, the present invention harness a comprehensive systematic analysis pipelines for all types of next generation sequencing genomic data, advanced genomic variants calling algorithms and modeling, variant data correlation and integration, and identification of cancer specific biomarkers and therapeutic targets. Thus, the present invention will aid users so that less of their time and efforts are required in order to obtain precisely the desired information for which they are analyzing.

This invention relates to the methods for the identification and isolation of cancer stem cells from cultured cancer cell lines. Cell line-derived cancer stem cells isolated using the present methods may be useful, for example, in assays to screen compounds for anti-cancer stem cell activity and in target discovery methods for identifying novel expressed genes and druggable targets. The invention also relates to the screening of compounds for activity against cell line-derived cancer stem cells.

Systems and methods are described herein for disease knowledge modeling and clinical treatment decision support, and the prioritization of possible treatment options based on tumor or other disease biomarkers. Disease or indication information, including identification of biomolecular entities associated with the indication may be culled through text data mining to create a knowledge model of the indication. In some embodiments, the knowledge model may comprise a network of associations between molecular entities, including such drug targets and biomakers, genes, pathways. The model may be combined with patient-specific variant information and historical treatment records to identify and prioritize treatment decisions and allow for the prediction of disease drivers and provide treatment options tailored to a patient's genetic data.

In order to identify genes that can serve as indicators for predicting the effectiveness of drug treatments in cancers and provide novel methods for predicting the effectiveness of treatments with drugs targeting said genes, transcriptome sequencing was performed of diffuse-type gastric cancer. As a result, in-frame fusion transcripts between the CEP55 gene and the RET gene were identified. It was also found that said gene fusions induce activation of RET protein, thereby causing canceration of cells. Further, it was demonstrated that the RET protein activation and canceration caused by said gene fusion can be suppressed by using a RET tyrosine kinase inhibitor, and that treatments with a RET tyrosine kinase inhibitor are effective in patients with detection of said gene fusion.

The present invention provides nucleic acid arrays and methods of using the same for detecting or monitoring expression profiles of drug target genes. Non-limiting examples of drug target genes include kinase genes, phosphatase genes, protease genes, G-protein coupled receptor genes, nuclear hormone receptor genes, and ion channel genes. The present invention also provides methods of using nucleic acid arrays for the identification or validation of drugs or drug targets. In one embodiment, a nucleic acid array of the present invention is concentrated with probes for drug target genes. These probes constitute a substantial portion of all of the polynucleotide probes that are stably attached to the nucleic acid array, and can hybridize under stringent or nucleic acid array hybridization conditions to the tiling sequences selected from Attachment C, or the complements thereof.

Provided herein are methods and systems for introducing nucleic acid manipulation agents into single cells. Such high throughput delivery of nucleic acid manipulation reagents into single cells and subsequent genetic manipulation of such cells allow for large scale genetic analysis that can be useful, for example, for the study of biological pathways and drug target discovery.

Methods are provided for diagnosis and prognosis of disease by analyzing expression of a set of genes obtained from single cell analysis. Classification allows optimization of treatment, and determination of whether on whether to proceed with a specific therapy, and how to optimize dose, choice of treatment, and the like. Single cell analysis also provides for the identification and development of therapies which target mutations and / or pathways in disease-state cells.

The invention discloses a construction and prediction method of an integrated drug target prediction system. The method comprises the following steps of: analyzing a protein crystal structure database; selecting the protein bound with the drug-like ligand small molecule or the protein with the small molecule ligand binding potential as a target point, and building a crystal structure database of targets; for these targets, collecting the information of the targets related to diseases, the biology type and the active small molecule ligand information, and integrating a comprehensive target screening database composed of an active site database, a pharmacophore database, a small molecular compound database and a target basic information database. Based on the comprehensive target screening database, the construction of the integrated drug target prediction system is realized through a script program or a PipelinePilot flow, and the probability of target prediction accuracy of the method is provided. The method provided by the invention exerts the three above technical advantages to provide the probability of target prediction, thereby providing effective basis for further experimental verification.

A method and apparatus (100) of treating tissue adjacent a bodily conduit using thermotherapy, while preventing obstructions of the bodily conduit due to edema, includes injection of a drug-encapsulated within a heat-sensitive carrier, such as a liposome, within a region of tissue to be treated. The heat produced by the energy-emitting source (110) heats a portion of the tissue surrounding the bodily conduit to a temperature of approximately 43° C. for a time sufficient to destroy the heated portion of the tissue. In addition, the heat produced by the energy-emitting source (110) activates the heat-sensitive carrier to activate the release of the encapsulated drug and the drug targets the tissue to be heated. The focused energy of the energy-emitting source together with the compression acting on the target area can assist in delivering drugs to the target area so that a natural stent has a long term efficacy.

The invention discloses a built-in drug target interaction prediction method based on a heterogeneous network. The built-in drug target interaction prediction method includes the steps: based on the assumption that a chemically similar drug can often interact with a similar target, combining a drug-drug similarity network, a target-target similarity network, and a drug-target interaction network into a drug-target heterogeneous network; using a starting-node-based migrating sequence, constructing a neural network classification model, taking the migrating sequence as input of the neural network classification model, training the classification model and learning to obtain vector representation of all nodes; and for prediction of drug-target interaction, giving a pair of drug-target pairs,extracting vector representation of the corresponding drug and target from the node vectors obtained from learning, performing Hadamard product operation on the two vectors, and taking the obtained result as the input of a random forest classifier to obtain the final prediction result. According to the experimental verification, the built-in drug target interaction prediction method based on a heterogeneous network has preferable prediction effect and applicability.

The invention relates to a method for screening drug target genes based on a CRISPR / Cas9 high-throughput technology. The method comprises the steps of firstly establishing a sgRNA library; secondly packaging the sgRNA library by using slow viruses, and collecting the viruses; thirdly screening the sgRNA library in a cancer cell line; fourthly extracting cells obtained by screening and genome DNA of the cells before screening; and finally enriching sgRNA in genome DNA. Compared with the prior art, the method has the advantages that a CRISPR / Cas cell screening process is improved, the virus infection efficiency is determined with a simple and convenient method by utilizing puromycin resistance of infected cells, and MOI values of the viruses are determined; more importantly, a virus packaging method is greatly optimized, so that the virus packaging efficiency is improved to be more than 5 times that of a conventional method, and large-scale drug target screening cost can be greatly reduced; and the method is used for promoting industrialization of cancer drug target screening.

The invention discloses a drug repositioning method based on multi-information fusion and a random walk model. According to the method, disease-target-drug heterogeneous network is constructed through integrating existing disease data, drug data, target data, disease-drug associated data, disease-gene associated data and drug-target associated data; the basic random walk model is extended to the constructed heterogeneous network; and candidate therapeutic drugs are recommended for diseases through effectively utilizing global network information. The method disclosed by the invention is simple and effective; and compared with other methods and proved by tests on a standard data set, the method has good prediction performance in the aspect of drug repositioning.

The present invention provides novel methods of treating HIV infections employing small molecule inhibitors identified by chemical library (DIVERSet™ library). These small molecule inhibitors may specifically bind to HIV-1 capsid protein thereby interfering with capsid assembly. The small molecule inhibitors of the present invention can be potential drug targets in the treatment of HIV infection.

Methods of screening candidate agents to identify potential therapeutic agents for the treatment of a neurodegenerative disease, such as Huntington's Disease and Parkinson's Disease and methods for identifying a mutation in, or changes in expression of, a gene associated with neurodegenerative disease, such as Huntington's Disease and Parkinson's Disease, are provided.

A method for screening of compounds for binding differentiation at various drug target binding sites is used with a device measuring the enthalpy of reaction for the binding. The method includes merging test ligand with target compound and merging test ligand with target compound in the presence of at least one blocking agent. A first heat of reaction is detected for the merged test ligand and target compound solution and a second heat of reaction is detected for the merged test ligand and target compound solution in the presence of a blocking agent. The two heats of reaction are compared to determine whether a reaction has occurred.

The invention discloses a small molecule drug virtual screening method based on deep migration learning and application thereof. A source domain is used as an input to be trained, converged and derived to obtain a weight matrix; a target domain is input into an improvement tool to serve as the initialization weight of the target domain; fine adjustment, training and convergence are conducted on the initialization weight and data in the target domain sequentially; a biological activity value of interaction of a lead compound and a drug target in the target domain is predicted, a target domain molecular fingerprint and a predicted value are obtained, and an evaluation index root mean square error and a correlation coefficient of a predicted result are output; the target domain is subjected to fine adjustment by repeating above steps, and the weight matrix of the source domain helps the target domain build a model. According to the small molecule drug virtual screening method and the application thereof, the effective virtual screening model can still be obtained under the condition that the information of a known active ligand sample is insufficient, and does not need to rely on a large number of data samples.

The present invention relates to novel drug targets for pathogenic bacteria. Accordingly, the invention provides purified protein comprising the amino acid sequence set forth in SEQ ID NO: 2. The invention also provides biochemical and biophysical characteristics of the polypeptides of the invention.

The invention provides a novel integrated structure and system-based approach for drug target prediction that enables the large-scale discovery of new targets for existing drugs Novel computer-readable storage media and computer systems are also provided. Methods and systems of the invention use novel sequence order-independent structure alignment, hierarchical clustering, and probabilistic sequence similarity techniques to construct a probabilistic pocket ensemble (PPE) that captures even promiscuous structural features of different binding sites for a drug on known targets. The drug's PPE is combined with an approximation of the drug delivery profile to facilitate large-scale prediction of novel drug- protein interactions with several applications to biological research and drug development.

Provided are means for the direct and continuous connection of a catheter to the lumen of any tubular anatomical structure, or ductus, without medically significant leakage. A port implanted at the body surface with piping to a periductal collar allows drug or radionuclide delivery that bypasses the upstream lumen. The port allows injection, infusion, or attachment of an automatic ambulatory pump. A superparamagnetic nanoparticle carrier-bound drug, for example, can be introduced into the lumen to pass downstream until the carrier particles, with or without the drug still bound, are drawn into the lumen wall by a magnetized jacket surrounding the ductus. Such constitutes a method of drug targeting whereby a segment of a vessel or the territory supplied by a branch of that segment can be circumscribed for exposure to the drug. A jacket with side-entry connector positioned in surrounding relation to a lesion requiring treatment can itself be magnetized.