Abstract

The present disclosure relates to a flavanone derivative compound useful in the treatment or alleviation of fibrosis and medical use thereof.

IPC Classes  ?

• C07D 311/32 - 2, 3-Dihydro derivatives, e.g. flavanones
• A61K 31/353 - 3,4-Dihydrobenzopyrans, e.g. chroman, catechin
• A61P 43/00 - Drugs for specific purposes, not provided for in groups
• A61P 11/00 - Drugs for disorders of the respiratory system
• A61P 1/16 - Drugs for disorders of the alimentary tract or the digestive system for liver or gallbladder disorders, e.g. hepatoprotective agents, cholagogues, litholytics

Abstract

The present invention relates to a composition comprising a peony extract for preventing, alleviating, or treating muscular dystrophy. The composition comprising a peony extract can be used to reduce muscle damage and HMGB1 levels, inhibit the HMGB1-TLR4-NFkB signaling, or lower cytokine and chemokine levels, thereby effectively preventing, alleviating, or treating muscular dystrophy.

IPC Classes  ?

• A61K 36/65 - Paeoniaceae (Peony family), e.g. Chinese peony
• A61P 21/04 - Drugs for disorders of the muscular or neuromuscular system for myasthenia gravis
• A23L 33/105 - Plant extracts, their artificial duplicates or their derivatives

Abstract

Disclosed is a method for predicting medicinal effects wherein medicinal effects of novel compounds are predicted by generating three types of feature data from acquired medicinal substance data, training a neural network model, and then applying acquired new compound data to the neural network model, and the use of the present disclosure mitigates the bottleneck effect of deep learning models and thus the present disclosure can be used to perform a large-scale natural compound study and can perform a preliminary screening of compounds for a large number of candidate medicinal substances, with a high accuracy of medicinal effect prediction.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G06N 3/08 - Learning methods
• G06N 3/04 - Architecture, e.g. interconnection topology

Abstract

The present invention relates to a composition comprising an Atractylodes macrocephala and Agastache rugosa mixed extract for alleviating fatigue or enhancing exercise performance. The composition comprising an Atractylodes macrocephala and Agastache rugosa mixed extract as an active ingredient, according to the present invention, increases the expression of PGC-1 alpha and enhances exercise performance through a decrease in serum, muscular lactic acid, and serum lactate dehydrogenase levels following physical activities, thereby effectively alleviating accumulated fatigue and enhancing exercise performance and, as such, can be applied to a food composition, a pharmaceutical composition, and a cosmetic composition for alleviating fatigue or enhancing exercise performance and to a pharmaceutical composition for preventing or treating disease associated with fatigue or exercise performance.

IPC Classes  ?

• A23L 33/105 - Plant extracts, their artificial duplicates or their derivatives
• A23L 19/00 - Products from fruits or vegetablesPreparation or treatment thereof
• A23L 5/20 - Removal of unwanted matter, e.g. deodorisation or detoxification
• A61K 36/284 - Atractylodes
• A61K 36/532 - Agastache, e.g. giant hyssop
• A61P 21/00 - Drugs for disorders of the muscular or neuromuscular system
• A61P 43/00 - Drugs for specific purposes, not provided for in groups

Abstract

The present invention relates to a method for predicting health effects of phytochemicals by using integrated analysis based on molecular networks, chemical properties, and ethnopharmacological evidences, and a system therefor. Specifically, a method for predicting health effects of phytochemicals, using integrated analysis based on molecular networks, chemical properties, and ethnopharmacological evidences according to the present invention does not utilizes individual information separately, but analyzes the information in an integrated manner and as such, can analyze and predict health effects of phytochemicals on a mass scale with high reliability. Therefore, the method and a system therefor can be advantageously used to develop drugs that utilize phytochemicals having useful functions.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• G16H 20/90 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to alternative medicines, e.g. homeopathy or oriental medicines
• G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
• G16C 20/50 - Molecular design, e.g. of drugs

Abstract

The present invention relates to a method for predicting a pharmacological effect of a natural compound using a phenotype-centered network analysis, and a system therefor. Specifically, the method for predicting a pharmacological effect of a natural compound using a phenotype vector of a plant, according to the present invention, enables a large-scale analysis of a potential pharmacological effect of a natural compound to be conducted, not on the basis of insufficient molecular information of the natural compound, but on the basis of abundant information associated with a phenotype of a plant, and thus the method and the system therefor may be usefully employed in the development of a drug using a natural compound having a high level of safety as a result of the long-term use thereof.

IPC Classes  ?

• G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• G16C 20/50 - Molecular design, e.g. of drugs
• G16C 20/30 - Prediction of properties of chemical compounds, compositions or mixtures

Abstract

Gentianae Macrophyllae RadixGentianae Macrophyllae Radix as an active ingredient. The method of the present invention promotes AMPK activity; inhibits fat accumulation, fat granulation, lipogenesis transcription factor SREBP-1c activity, and lipogenic enzyme expression; and reduces body weight, fat tissue and liver tissue weight, blood glucose, triglycerides, and cholesterol content, and thus may be effectively used for preventing or treating metabolic diseases such as obesity, diabetes, hypertriglyceridemia, hypercholesterolemia, and the like.

IPC Classes  ?

• A61K 36/515 - Gentiana
• A23L 33/105 - Plant extracts, their artificial duplicates or their derivatives

Abstract

The present invention relates to a composition for preventing, alleviating or treating stress diseases, containing a Platycodon grandiflorum extract as an active ingredient and, more specifically, to a food composition for preventing or alleviating stress diseases or a pharmaceutical composition for preventing and treating stress diseases, both of which contain a Platycodon grandiflorum extract and a Citrus aurantium extract as active ingredients. A method of the present invention is usable in the preparation of: an agent for treating depression and anxiety, which are stress diseases with few side effects because of the use of a natural material; and a health functional food having effects of alleviating depression, anxiety, and fatigue, which are stress diseases.

IPC Classes  ?

• A23L 33/105 - Plant extracts, their artificial duplicates or their derivatives
• A61K 36/346 - Platycodon
• A61K 36/752 - Citrus, e.g. lime, orange or lemon
• A61P 25/24 - Antidepressants
• A61P 25/22 - Anxiolytics