Exploring pharmacological active ingredients of traditional Chinese medicine by pharmacotranscriptomic map in ITCM

Abstract

With the emergence of high-throughput technologies, computational screening based on gene expression profiles has become one of the most effective methods for drug discovery. More importantly, profile-based approaches remarkably enhance novel drug–disease pair discovery without relying on drug- or disease-specific prior knowledge, which has been widely used in modern medicine. However, profile-based systematic screening of active ingredients of traditional Chinese medicine (TCM) has been scarcely performed due to inadequate pharmacotranscriptomic data. Here, we develop the largest-to-date online TCM active ingredients-based pharmacotranscriptomic platform integrated traditional Chinese medicine (ITCM) for the effective screening of active ingredients. First, we performed unified high-throughput experiments and constructed the largest data repository of 496 representative active ingredients, which was five times larger than the previous one built by our team. The transcriptome-based multi-scale analysis was also performed to elucidate their mechanism. Then, we developed six state-of-art signature search methods to screen active ingredients and determine the optimal signature size for all methods. Moreover, we integrated them into a screening strategy, TCM-Query, to identify the potential active ingredients for the special disease. In addition, we also comprehensively collected the TCM-related resource by literature mining. Finally, we applied ITCM to an active ingredient bavachinin, and two diseases, including prostate cancer and COVID-19, to demonstrate the power of drug discovery. ITCM was aimed to comprehensively explore the active ingredients of TCM and boost studies of pharmacological action and drug discovery. ITCM is available at http://itcm.biotcm.net.

Depicting the regulatory role of JZOL on TRP channels in the treatment of Acute Bronchitis based on the combination of clinical trials, computational analysis and in vivo experiments

“…Last but not least, in order to observe the regulatory effects of JZOL on TRP channels from a deeper perspective, we have collected transcriptomes for both the representative herbs and compounds in JZOL from ITCM database and previous studies 38,39 . These datasets included the transcriptomes of common compounds in TCM on MCF-7 cell lines and the transcriptomes of common herbs on THP-1 cell lines, respectively, providing transcriptional-level evidence for the influences of representative compounds or herbs of JZOL on the biomolecules of TRP channels to some extent.…”

Pan-cancer analysis of prognostic and immunological role of IL4I1 in human tumors: a bulk omics research and single cell sequencing validation

“…Recently several computational approaches have been proposed to rapidly screen drug candidates for drug discovery. For example, ITCM database to screen the active ingredients in herbal medicines against tumours [ 38 ] and COIMMR to reveal the contribution of herbal ingredients to human cancers through immune microenvironment and metabolic reprogramming [ 39 ]. However, in this paper the active ingredients of herbal medicines were not investigated for corresponding studies on IL4I1, which may be a limitation in our study.…”

Clinical multi-omics reveals the role of Tuomin Zhiti Decoction Intervention in Allergic Rhinitis from the perspective of biological network

“…In addition, validation of regulation of TZD on antigen process related pathways and biomolecules were conducted based on several public datasets. Firstly, based on ITCM database 68 , which recorded expression of MCF-7 cell lines after the intervention of compounds from usual herbs, transcriptomics data of certain compounds of herbs in TZD were collected. After estimating the potential effects on antigen process and T-helper cell related biological process, 21 compounds belonging to herbs of TZD were kept for further statistical analysis.…”