多味中药活性成分-靶点网络药理学知识图谱数据

本数据集系统整理了川芎、当归、白芍、熟地、人参、茯苓、白术、甘草8味常用中药的216个活性成分，涵盖分子ID、SMILES结构、理化性质（分子量、LogP、氢键供体/受体、口服生物利用度、Caco-2渗透性、BBB渗透性、类药性、半衰期）、作用靶点列表、药理作用及关键靶点功能描述。每个成分的靶点经过去重处理，共涉及数千个人源靶点。数据基于TCMSP数据库，经过清洗、标准化和规则化处理（靶点去重、Lipinski规则符合数计算、药理作用归类、关键靶点功能注释），形成结构化的多靶点关联数据。该数据集可直接用于中药活性成分的虚拟筛选、多靶点机制解析、网络药理学建模及药物重定位研究。This dataset systematically curates 216 active ingredients derived from 8 commonly used traditional Chinese medicines (TCMs), namely Chuanxiong Rhizoma (Ligusticum chuanxiong), Angelica sinensis (Danggui), Paeonia lactiflora (Baishao), Rehmannia glutinosa preparata (Shudi), Panax ginseng (Renshen), Poria cocos (Fuling), Atractylodes macrocephala (Baizhu), and Glycyrrhiza uralensis (Gancao). It contains molecular identifiers, SMILES structures, physiochemical properties including molecular weight, LogP, hydrogen bond donors and acceptors, oral bioavailability, Caco-2 permeability, blood-brain barrier (BBB) permeability, drug-likeness, and half-life, lists of action targets, pharmacological effects, and functional descriptions of key targets. Targets for each ingredient have been deduplicated, involving thousands of human-derived targets in total. Developed based on the TCMSP database, this dataset has undergone data cleaning, standardization and regularization processing, including target deduplication, calculation of Lipinski's Rule of Five compliance, classification of pharmacological actions, and functional annotation of key targets, thus forming structured multi-target association data. This dataset can be directly utilized for virtual screening of TCM active ingredients, multi-target mechanism elucidation, network pharmacology modeling, and drug repurposing research.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于多味中药活性成分与靶点之间关系的网络药理学知识图谱，由企业数据构成，目前处于知识产权登记公示阶段。它旨在通过知识图谱形式整合中药活性成分和靶点的相互作用，为网络药理学研究提供结构化数据支持。