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      HIT: linking herbal active ingredients to targets

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          Abstract

          The information of protein targets and small molecule has been highly valued by biomedical and pharmaceutical research. Several protein target databases are available online for FDA-approved drugs as well as the promising precursors that have largely facilitated the mechanistic study and subsequent research for drug discovery. However, those related resources regarding to herbal active ingredients, although being unusually valued as a precious resource for new drug development, is rarely found. In this article, a comprehensive and fully curated database for Herb Ingredients’ Targets (HIT, http://lifecenter.sgst.cn/hit/) has been constructed to complement above resources. Those herbal ingredients with protein target information were carefully curated. The molecular target information involves those proteins being directly/indirectly activated/inhibited, protein binders and enzymes whose substrates or products are those compounds. Those up/down regulated genes are also included under the treatment of individual ingredients. In addition, the experimental condition, observed bioactivity and various references are provided as well for user's reference. Derived from more than 3250 literatures, it currently contains 5208 entries about 1301 known protein targets (221 of them are described as direct targets) affected by 586 herbal compounds from more than 1300 reputable Chinese herbs, overlapping with 280 therapeutic targets from Therapeutic Targets Database (TTD), and 445 protein targets from DrugBank corresponding to 1488 drug agents. The database can be queried via keyword search or similarity search. Crosslinks have been made to TTD, DrugBank, KEGG, PDB, Uniprot, Pfam, NCBI, TCM-ID and other databases.

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          Most cited references15

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          Benchmarking sets for molecular docking.

          Ligand enrichment among top-ranking hits is a key metric of molecular docking. To avoid bias, decoys should resemble ligands physically, so that enrichment is not simply a separation of gross features, yet be chemically distinct from them, so that they are unlikely to be binders. We have assembled a directory of useful decoys (DUD), with 2950 ligands for 40 different targets. Every ligand has 36 decoy molecules that are physically similar but topologically distinct, leading to a database of 98,266 compounds. For most targets, enrichment was at least half a log better with uncorrected databases such as the MDDR than with DUD, evidence of bias in the former. These calculations also allowed 40x40 cross-docking, where the enrichments of each ligand set could be compared for all 40 targets, enabling a specificity metric for the docking screens. DUD is freely available online as a benchmarking set for docking at http://blaster.docking.org/dud/.
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            Update of TTD: Therapeutic Target Database

            Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp.
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              TarFisDock: a web server for identifying drug targets with docking approach

              TarFisDock is a web-based tool for automating the procedure of searching for small molecule–protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand–protein docking program. In contrast to conventional ligand–protein docking, reverse ligand–protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand–protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at .
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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2011
                January 2011
                20 November 2010
                20 November 2010
                : 39
                : Database issue , Database issue
                : D1055-D1059
                Affiliations
                1State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, 2Shanghai Center for Bioinformation Technology, 100 Qinzhou Road, Shanghai 200235, 3School of Life Sciences and Technology, Tongji University, Shanghai 200092, China, 4NUS Graduate School for Integrative Sciences and Engineering, Singapore, 117456, 5Bioinformatics and Drug Design Group, Center for Computational Science and Engineering, Department of Pharmacy, National University of Singapore, Singapore, 117543 and 6Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
                Author notes
                *To whom correspondence should be addressed. Tel: +86 21 5406 5003; Fax: +86 21 5406 5058; Email: zwcao@ 123456tongji.edu.cn
                Correspondence may also be addressed to Yixue Li. Tel: +86 21 5406 5001; Fax: +86 21 5406 5058; Email: yxli@ 123456scbit.org
                Article
                gkq1165
                10.1093/nar/gkq1165
                3013727
                21097881
                868fed3a-dd33-4d34-984f-431ee97c8ce7
                © The Author(s) 2010. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 August 2010
                : 29 October 2010
                : 31 October 2010
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                Genetics
                Genetics

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