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      TCMBank: bridges between the largest herbal medicines, chemical ingredients, target proteins, and associated diseases with intelligence text mining

      research-article
      a , a , a , a , b , c , a , a , d , e , f ,
      Chemical Science
      The Royal Society of Chemistry

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          Abstract

          Traditional Chinese Medicine (TCM) has long been viewed as a precious source of modern drug discovery. AI-assisted drug discovery (AIDD) has been investigated extensively. However, there are still two challenges in applying AIDD to guide TCM drug discovery: the lack of a large amount of standardized TCM-related information and AIDD is prone to pathological failures in out-of-domain data. We have released TCM Database@Taiwan in 2011, and it has been widely disseminated and used. Now, we developed TCMBank, the largest systematic free TCM database, which is an extension of TCM Database@Taiwan. TCMBank contains 9192 herbs, 61 966 ingredients (unduplicated), 15 179 targets, 32 529 diseases, and their pairwise relationships. By integrating multiple data sources, TCMBank provides 3D structure information of ingredients and provides a standard list and detailed information on herbs, ingredients, targets and diseases. TCMBank has an intelligent document identification module that continuously adds TCM-related information retrieved from the literature in PubChem. In addition, driven by TCMBank big data, we developed an ensemble learning-based drug discovery protocol for identifying potential leads and drug repurposing. We take colorectal cancer and Alzheimer's disease as examples to demonstrate how to accelerate drug discovery by artificial intelligence. Using TCMBank, researchers can view literature-driven relationship mapping between herbs/ingredients and genes/diseases, allowing the understanding of molecular action mechanisms for ingredients and identification of new potentially effective treatments. TCMBank is available at https://TCMBank.CN/.

          Abstract

          We developed TCMBank which contains 9192 herbs, 61 966 unduplicated ingredients, 15 179 targets, 32 529 diseases, and their pairwise relationships. We developed an ensemble learning-based drug discovery protocol for identifying potential lead.

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          Most cited references33

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          DrugBank 5.0: a major update to the DrugBank database for 2018

          Abstract DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year’s update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education.
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            PubChem 2019 update: improved access to chemical data

            Abstract PubChem (https://pubchem.ncbi.nlm.nih.gov) is a key chemical information resource for the biomedical research community. Substantial improvements were made in the past few years. New data content was added, including spectral information, scientific articles mentioning chemicals, and information for food and agricultural chemicals. PubChem released new web interfaces, such as PubChem Target View page, Sources page, Bioactivity dyad pages and Patent View page. PubChem also released a major update to PubChem Widgets and introduced a new programmatic access interface, called PUG-View. This paper describes these new developments in PubChem.
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              Ensembl 2020

              Abstract The Ensembl (https://www.ensembl.org) is a system for generating and distributing genome annotation such as genes, variation, regulation and comparative genomics across the vertebrate subphylum and key model organisms. The Ensembl annotation pipeline is capable of integrating experimental and reference data from multiple providers into a single integrated resource. Here, we present 94 newly annotated and re-annotated genomes, bringing the total number of genomes offered by Ensembl to 227. This represents the single largest expansion of the resource since its inception. We also detail our continued efforts to improve human annotation, developments in our epigenome analysis and display, a new tool for imputing causal genes from genome-wide association studies and visualisation of variation within a 3D protein model. Finally, we present information on our new website. Both software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license) and data updates made available four times a year.
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                Author and article information

                Journal
                Chem Sci
                Chem Sci
                SC
                CSHCBM
                Chemical Science
                The Royal Society of Chemistry
                2041-6520
                2041-6539
                8 August 2023
                11 October 2023
                8 August 2023
                : 14
                : 39
                : 10684-10701
                Affiliations
                [a ] Artificial Intelligence Medical Research Center, School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University Shenzhen Guangdong 518107 P. R. China chenyuchian@ 123456mail.sysu.edu.cn
                [b ] Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University Guangzhou Guangdong 510655 P. R. China
                [c ] Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University Guangzhou Guangdong 510655 P. R. China
                [d ] Department of Medical Research, China Medical University Hospital Taichung 40447 Taiwan
                [e ] Department of Bioinformatics and Medical Engineering, Asia University Taichung 41354 Taiwan
                [f ] Guangdong L-Med Medicine Biotechnology Co., Ltd Meizhou Guangdong 514699 P. R. China
                Author notes
                [†]

                Equal contribution.

                Author information
                https://orcid.org/0000-0003-4979-7906
                https://orcid.org/0000-0002-4435-0884
                https://orcid.org/0000-0003-3831-3996
                https://orcid.org/0000-0002-8195-2526
                https://orcid.org/0000-0002-4971-8852
                https://orcid.org/0009-0003-7567-9935
                https://orcid.org/0000-0001-9213-9832
                Article
                d3sc02139d
                10.1039/d3sc02139d
                10566508
                37829020
                959135fd-f66b-4e0f-833b-9e818f5b65c4
                This journal is © The Royal Society of Chemistry
                History
                : 26 April 2023
                : 30 July 2023
                Page count
                Pages: 18
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: Grant No. 62176272
                Funded by: Special Project for Research and Development in Key areas of Guangdong Province, doi 10.13039/501100015956;
                Award ID: 2020B1111100001
                Categories
                Chemistry
                Custom metadata
                Paginated Article

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