362 results about "Drug design" patented technology

In various embodiments, the systems and methods described herein relate to generative models. The generative models may be trained using machine learning approaches, with training sets comprising chemical compounds and biological or chemical information that relate to the chemical compounds. Deep learning architectures may be used. In various embodiments, the generative models are used to generate chemical compounds that have desired characteristics, e.g. activity against a selected target. The generative models may be used to generate chemical compounds that satisfy multiple requirements.

Peptides and peptidomimetics capable of modulating apoptosis through their interaction with cellular IAPs (inhibitor of apoptosis proteins) are disclosed. The peptides and mimetics are based on the N-terminal tetrapeptide of IAP-binding proteins, such as Smac/DIABLO, Hid, Grim and Reaper, which interact with a specific surface groove of IAP. Also disclosed are methods of using these peptides and peptidomimetics for therapeutic purposes and for rational drug design.

The present invention provides for the first time a quantum mechanics-based method for scoring protein-ligand interactions and binding affinity predictions, using quantum mechanical Hamiltonians and/or a combined quantum mechanical/molecular mechanical approach, and Poisson-Boltzmann (PB)-based solvation methods. Also provided is a method for using quantum mechanics to describe the enthalpic and solvation effects of binding. The method comprises comparing the calculated binding affinities to experimental values in order to measure the success of the method. The methods disclosed herein may further be used to score protein and drug or protein and inhibitor interactions. The present method can predict the free energy of binding of protein-ligand complexes with high accuracy so as to enable lead optimization, thus serving as a powerful tool in computational drug design.

The invention relates to a cancer predicting method and a drug design method. Specifically, the invention relates to a method for predicting cancer which is useful for the genetic diagnosis for evaluating the malignancy of cancer. The invention also relates to a method for designing a drug based on the result of the above prediction method.

Novel proteins that constitute modified forms of a Neisseria meningitidis surface antigen and encoding nucleic acids are provided. The modified surface proteins are characterized by having deletions of non-conserved amino acids, and thereby being capable of eliciting cross-protective immune responses against Neisseria meningitidis. The invention extends to the use of the modified surface antigens in diagnostics, in therapeutic and prophylactic vaccines and in the design and/or screening of medicaments. The modified surface antigens are particularly useful in vaccines which effectively immunize against a broader spectrum of N. meningitidis strains than would be expected from a corresponding wild-type surface antigen.

Provided herein are compounds and methods of using compounds that selectively inhibit binding to one or more docking domain regions of an extracellular signal-regulated kinase (ERK) to inhibit in a cell having an extracellular signal-regulated kinase activity. Such methods may be used to inhibit cell proliferation of a neoplastic cell, to treat a cancer and further may be used in conjunction with administration of an anticancer drug at a reduced dosage to treat a cancer with a concomitant reduction in toxicity to an individual receiving the treatment. Also provided is a method to design and screen for compounds to inhibit binding within the extracellular signal-regulated kinase docking domain region, using at least in part computer-aided drug design modeling.

In the present invention, the markers identified for liver fibrosis and cirrhosis and the microarray panel thereof comprise at least one of the following proteins/genes:

8 up-regulated genes such as

ANXA2; COL1A2; COL3A1; GSN; LDHB; LUM; PDGFRA and TIMP1.

13 down-regulated genes such as

ALB; ANPEP; APOF; AZGP1; BHMT C8A; CFHR4; CFHR5; COL18A1; FTCD; GYS2; ITIH1, and THRAP1.

9 therapeutic targets such as PDGFRA; S100A4; COL3A1; CCL19; DCN; DPT; APP; TNF; and INFG.

The present invention is capable of screening markers for the early warning of the occurrence for severe fibrosis or cirrhosis and potentially targets for drug design.

The invention discloses a method for preparing Eptifibatide with a solid phase method, which comprises the following steps of: 1) selecting Sieber resin to remove Fmoc, and obtaining H2N-Sieber resin; 2) adopting Fmoc/tBu solid phase method to couple and synthesize linear peptide Eptifibatide-Sieber resin with full protective lateral chains in sequence; 3) conducting solid phase oxidation to the resin, and obtaining oxidant peptide Eptifibatide-Sieber resin with full protective lateral chains; 4) cutting the resin and removing the lateral chain protection, and obtaining crude product of Eptifibatide; and 5) conducting separation and purification, and breeze drying by a freeze dryer, and obtaining refined Eptifibatide peptide. The technology is characterized by simple operation, easy post treatment, less investment of raw material, low cost, high yield and the like, and has considerable economical and practical value and wide application prospect in the field of polypeptide drug design and synthesis simultaneously.

The invention discloses a method for predicting the binding free energy of protein and ligand based on a progressive neural network, and belongs to the technical field of computer-aided drug design. The method comprises the steps: obtaining a pdb file from a PDBbind database, establishing local database, acquiring an amino acid molecule within 4.5 angstroms in the protein binding pocket by takingthe ligand molecule as a center, performing extended connectivity fingerprint calculation, carrying out SPLIF fingerprint calculation, searching for the number of salt bridges and hydrogen bonds between protein and ligand molecules, converting the structural information of the protein and the ligand into a one-dimensional tensor, and establishing a training set, a verification set and a test set;training the progressive neural network by using the training set; optimizing and searching hyper-parameters for prediction; through comparison with a molecular docking result, obtaining a higher Pearson correlation coefficient. According to the invention, the technical problem of how to convert a three-dimensional structure of protein and ligand molecules into tensors which are easy to calculateby a computer and input the tensors into the progressive neural network for training and optimization is solved, and the calculation rate and the prediction accuracy are greatly improved.

Polynucleotide molecules and the proteins encoded by the molecules, diagnostic and treatment methods for neurological disorders characterized by protein aggregation are provided. Genes are described herein that affect the misfolding of, and subsequent aggregation of, aggregation-prone proteins such as alpha-synuclein and have implications for the diagnosis and treatment of neurological diseases related to protein aggregation such as Parkinson's disease. Knockdown of expression of the genes described herein using RNAi results in alpha-synuclein protein aggregation in a C. elegans model of protein aggregation. Dopaminergic neuroprotection after exposure to the neurotoxin 6-OHDA or overexpression of alpha-synuclein may also be provided by overexpression of proteins. Knowledge of genes relating to protein misfolding and aggregation provides powerful means to develop diagnostic screening methods, mutation analysis and drug design information for the development of novel therapeutic and neuroprotective compounds to treat neurodegenerative diseases such as Parkinson's disease.

The present invention provides a molecular mark for determining liver fibrosis and cirrhosis and a micro-array system board thereof. The invention at least comprises one in 28 proteins or at least comprises one in the genes encoding these proteins. Among these proteins or genes, 8 members are upper regulatory genes, 13 members are lower regulatory genes, and the rest 9 members are treating target. The invention is a molecular mark with filtering capacity to warn the generation of severe liver fibrosis or cirrhosis. The molecular mark of the invention is also a target which has latent capacity for the medicament design.

The invention provides hepatocellular carcinoma-related klotho gene single-nucleotide polymorphism and its construction method and use. The hepatocellular carcinoma-related klotho gene single-nucleotide polymorphism and its construction method have the advantages that 1, through a detection method provided by the invention, polymorphism of a single nucleotide located in an exon 4 area of a human klotho gene can be detected fast and simply and it is diagnosed that if an individual has susceptibility of hepatocellular carcinoma so that the hepatocellular carcinoma-susceptible population screening and hepatocellular carcinoma prevention are promoted; 2, a T allele point of rs648202 is used as a drug design target point for drug screening so that an active molecule adjusting a klotho gene expression level is selected and development of a novel antitumor drug is promoted; 3, through primer sequences and HaeIII endonuclease provided by the invention, simple, efficient and specific detection of rs648202 polymorphism is realized; and 4, according to hepatocellular carcinoma-related klotho gene single-nucleotide polymorphism, a hepatocellular carcinoma genetic diagnosis kit can be constructed.

The present invention provides small molecules having high affinity to the ATP binding site of protein kinases, which are conjugated to apeptide or peptidomimetic moiety which mimics the substrate of PKB. The chimeric compounds according to the present invention preferably serve as PKB inhibitors with improved activity and selectivity. Novel ATP mimetic compounds, particularly isoquinoline derivatives, conjugated with peptides or peptidomimetics are useful as inhibitors of protein kinases for experimental, medical, and drug design purposes. Furthermore, pharmaceutical compositions comprising these protein kinase inhibitors, and methods of using such compositions for treatment and diagnosis of cancers, diabetes, cardiovascular pathologies, hemorrhagic shock, obesity, inflammatory diseases, diseases of the central nervous system, and autoimmune disease, are disclosed.

Methods and compositions for modulating aging genes or their targets for the treatment or prevention of senescence or symptoms thereof have been developed based on the discovery of naturally occurring inhibitory nucleic acids, in particular lin-4 miRNA, that downregulate genes involved in senescence, lifespan, or age-related disorders. Representative aging genes include, but are not limited to lin-4, lin-14, let-7, lin-28, egl-35 and lin-42. Methods for identifying modulators of aging genes and targets of aging genes are also provided. The disclosed compositions are useful as diagnostics. These can be used in assays to compare genes in normal individuals, with those who are aging well or who demonstrate early senescence, and with those who have age-related disorders such as Parkinson's and Alzheimer's. The genes can be used to study the pathways and mechanisms involved in aging and age-related disorders. These genes can be used as drug targets, or in drug design, to develop drugs that can inhibit one or more characteristics of senescence or age-related disorders. These compositions should be effective therapies for treating or slowing the effects of one or more symptoms or characteristics of age-related disorders resulting from activation or over-expression of aging genes. Compositions that alter the expression of particular aging genes affecting the insulin-like signal pathway are described. Suitable compositions described herein include, inhibitory nucleic acids and small molecules, in particular miRNA.

The present invention discloses a drug susceptibility prediction method based on a multi-similarity network. The method comprises the steps of: employing drug structure information to construct a drugsimilarity network, employing cell line gene expression profile data to construct a cell line similarity network after gene screening, and calculating a gene similarity network according to protein structure information; on this basis, establishing an association relation among drugs, the cell line and the genes, and performing three random walk in multiple networks formed by the constructed drugsimilarity network, the cell line similarity network and the gene similarity network to predict the drug susceptibility. On the basis of simpleness and practicability, the drug susceptibility prediction method based on a multi-similarity network can improve the drug susceptibility identification accuracy and can provide important reference for researchers to perform drug design.