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      DRAMP 2.0, an updated data repository of antimicrobial peptides

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          Abstract

          Data Repository of Antimicrobial Peptides (DRAMP, http://dramp.cpu-bioinfor.org/) is an open-access comprehensive database containing general, patent and clinical antimicrobial peptides (AMPs). Currently DRAMP has been updated to version 2.0, it contains a total of 19,899 entries (newly added 2,550 entries), including 5,084 general entries, 14,739 patent entries, and 76 clinical entries. The update covers new entries, structures, annotations, classifications and downloads. Compared with APD and CAMP, DRAMP contains 14,040 (70.56% in DRAMP) non-overlapping sequences. In order to facilitate users to trace original references, PubMed_ID of references have been contained in activity information. The data of DRAMP can be downloaded by dataset and activity, and the website source code is also available on dedicatedly designed download webpage. Although thousands of AMPs have been reported, only a few parts have entered clinical stage. In the paper, we described several AMPs in clinical trials, including their properties, indications and clinicaltrials.gov identifiers. Finally, we provide the applications of DRAMP in the development of AMPs.

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          Most cited references 49

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          Magainins, a class of antimicrobial peptides from Xenopus skin: isolation, characterization of two active forms, and partial cDNA sequence of a precursor.

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              BACTIBASE second release: a database and tool platform for bacteriocin characterization

              Background BACTIBASE is an integrated open-access database designed for the characterization of bacterial antimicrobial peptides, commonly known as bacteriocins. Description For its second release, BACTIBASE has been expanded and equipped with additional functions aimed at both casual and power users. The number of entries has been increased by 44% and includes data collected from published literature as well as high-throughput datasets. The database provides a manually curated annotation of bacteriocin sequences. Improvements brought to BACTIBASE include incorporation of various tools for bacteriocin analysis, such as homology search, multiple sequence alignments, Hidden Markov Models, molecular modelling and retrieval through our taxonomy Browser. Conclusion The provided features should make BACTIBASE a useful tool in food preservation or food safety applications and could have implications for the development of new drugs for medical use. BACTIBASE is available at http://bactibase.pfba-lab-tun.org.
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                Author and article information

                Contributors
                lao@cpu.edu.cn
                zhengh18@hotmail.com
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                13 August 2019
                13 August 2019
                2019
                : 6
                Affiliations
                [1 ]ISNI 0000 0000 9776 7793, GRID grid.254147.1, School of Life Science and Technology, , China Pharmaceutical University, ; Nanjing, 211100 P.R. China
                [2 ]ISNI 0000 0004 1761 0489, GRID grid.263826.b, State Key Laboratory of Bioelectronics, , Southeast University, ; Nanjing, 210096 P.R. China
                [3 ]ISNI 0000 0001 0348 3990, GRID grid.268099.c, School of Pharmaceutical Sciences, , Wenzhou Medical University, ; Wenzhou, 325000 P.R. China
                [4 ]ISNI 0000 0000 9776 7793, GRID grid.254147.1, The Engineering Research Center of Peptide Drug Discovery and Development, , China Pharmaceutical University, ; Nanjing, 211100 P.R. China
                Article
                154
                10.1038/s41597-019-0154-y
                6692298
                31409791
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX19_0665, No. SJKY19_0697 and No. SJCX18_0270), National Found for Fostering Talents of Basic Science (NFFTBS) (No. J1310032), and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).
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                © The Author(s) 2019

                protein databases, antimicrobial resistance

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