TCMBank:最大的草药,化学成分,向蛋白质和与情报文本挖掘相关疾病之间的桥梁
Qiujie Lv1, Guanxing Chen1, Haohuai He1
1Artificial Intelligence Medical Research Center, School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University Shenzhen Guangdong 518107 P. R. China chenyuchian@mail.sysu.edu.cn.
TCMBank是一个新的,全面的中国传统医学 (TCM) 数据数据库,解决了人工智能辅助药物发现的挑战. 它可以更快地识别癌症和阿尔茨海默氏症等疾病的潜在新疗法.
科学领域:
- 计算生物学是一种计算生物学.
- 药理学 药理学是指药理学的学科.
- 生物信息学是一种生物信息学.
- 药物发现 药物发现
背景情况:
- 传统中医 (TCM) 是现代药物发现的宝贵资源.
- 人工智能辅助药物发现 (AIDD) 面临着标准化TCM数据和域外故障的挑战.
- 之前已经开发了TCM数据库,如TCM数据库@台湾.
研究的目的:
- 开发TCMBank,这是最大的系统,免费的TCM数据库.
- 整合多样化的数据源,提供关于草药,成分,目标和疾病的标准化信息.
- 创建一个使用TCMBank的AIDD协议,用于识别潜在的药物线索和重新使用现有的药物.
主要方法:
- 开发了TCMBank,整合了9192种草药,61,966种成分,15,179个目标和32,529种疾病,并与它们建立了对对关系.
- 集成的3D结构信息和智能文档识别模块用于PubChem.的持续文献更新.
- 创建了一个基于集体学习的药物发现协议,由TCMBank大数据驱动.
主要成果:
- TCMBank为TCM相关信息提供了一个标准化,广泛的资源.
- 该数据库促进了TCM组件与生物标/疾病之间的文献驱动的关系映射.
- 使用开发的协议和数据库,证明了对结直肠癌和阿尔茨海默病的加速药物发现.
结论:
- 在TCM药物发现中,TCMBank解决了关键数据标准化和AIDD挑战.
- 数据库和协议加速了对分子机制的理解,并确定了新的治疗策略.
- 对于药物发现和TCM研究的研究人员来说,TCMBank是一个有价值的,免费的资源.
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