Zhang Chenyang, Mou Minjie, Zhou Ying, Zhang Wei, Lian Xichen, Shi Shuiyang, Lu Mingkun, Sun Huaicheng, Li Fengcheng, Wang Yunxia, Zeng Zhenyu, Li Zhaorong, Zhang Bing, Qiu Yunqing, Zhu Feng, Gao Jianqing
College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, 79 QingChun Road, Hangzhou, Zhejiang 310000, China.
Brief Bioinform. 2022 Sep 20;23(5). doi: 10.1093/bib/bbac160.
In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns about their clinical toxicities. Therefore, the biological activities of DIG on physiologically relevant target are widely demanded by both clinical investigation and pharmaceutical industry. However, such activity data are not available in any existing pharmaceutical knowledge base, and their potentials in predicting the DIG-target interaction have not been evaluated yet. In this study, the comprehensive assessment and analysis on the biological activities of DIGs were therefore conducted. First, the largest number of DIGs and DFMs were systematically curated and confirmed based on all drugs approved by US Food and Drug Administration. Second, comprehensive activities for both DIGs and DFMs were provided for the first time to pharmaceutical community. Third, the biological targets of each DIG and formulation were fully referenced to available databases that described their pharmaceutical/biological characteristics. Finally, a variety of popular artificial intelligence techniques were used to assess the predictive potential of DIGs' activity data, which was the first evaluation on the possibility to predict DIG's activity. As the activities of DIGs are critical for current pharmaceutical studies, this work is expected to have significant implications for the future practice of drug discovery and precision medicine.
在药物制剂(DFM)中,按质量计的主要成分并非活性药物成分(API),而是药物非活性成分(DIGs)。DIGs的浓度可比API所能达到的浓度高得多,这引发了人们对其临床毒性的极大关注。因此,临床研究和制药行业都广泛需要了解DIGs对生理相关靶点的生物学活性。然而,任何现有的药学知识库中都没有此类活性数据,而且它们在预测DIG-靶点相互作用方面的潜力尚未得到评估。因此,在本研究中,对DIGs的生物学活性进行了全面评估和分析。首先,基于美国食品药品监督管理局批准的所有药物,系统地整理并确认了数量最多的DIGs和DFMs。其次,首次向药学界提供了DIGs和DFMs的综合活性数据。第三,每个DIG和制剂的生物学靶点都充分参考了描述其药学/生物学特性的可用数据库。最后,使用了多种流行的人工智能技术来评估DIGs活性数据的预测潜力,这是对预测DIG活性可能性的首次评估。由于DIGs的活性对当前的药学研究至关重要,预计这项工作将对未来的药物发现和精准医学实践产生重大影响。