DRAMP newly added peptides with reported activities against: SARS-CoV-2.
We are responsible for maintaining the website daily and updating the database regularly. The updated information will be written in the Update page. Last updated on 2023-11-4.
231486 opens since May 20 2013.
Institute of Medical and Pharmaceutical Biotechnology, Jiangsu Industrial Technology Research Institute.
DRAMP(Data repository of antimicrobial peptides) is an open-access and manually curated database harboring diverse annotations of AMPs including sequences, structures, activities, physicochemical, patent, clinical and reference information. The clinical dataset also includes information on the clinical trial phase, therapeutic applications, company and preclinical or clinical AMP literature sources.
DRAMP currently contains 22528 entries, 6105 of which are general AMPs (containing natural and synthetic AMPs), 16110 patent AMPs and 96 AMPs in drug development (preclinical or clinical stage). In the late update, we added 217 stapled antimicrobial peptides belonging to specific AMPs.
For the purpose of expanding the scope of AMPs design, DRAMP also holds 5909 candidate AMPs which are screened by some platforms whose antibacterial activities haven't been assayed. Such candidate AMPs are seen as an individule part and the total 22259 entries do not include them.
Data in the DRAMP is made available under an CCBY 4.0 License. You are entitled to access and use the services and download or extract data. The free services are offered for the purpose of providing access to summarized data, analytics, metadata, and bulk downloads. If you need the data from the DRAMP for research, please cite the article of original author for general and clinical AMPs, or obtain the authorization for patent AMPs.
We will conduct data mining and design work based on data collected of DRAMP, as those data are valuable for guiding develment and optimization of AMP-drugs. Prediction function based on computational strategies is also expected in our database. We will set out to establish Some high-efficient classifiers.
To all regular downloads, please cite our publications. If you find some errors in the website, please send an email to firstname.lastname@example.org.
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