Database of Antimicrobial Activity and Structure of Peptides (DBAASP) is the manually-curated database. It has been developed to provide the scientific community with the information and analytical resources for designing antimicrobial compounds with a high therapeutic index.
Antimicrobial peptides (AMP) represent ancient defense molecules widespread in all life forms, from multicellular organisms to bacterial cells, that play a primary role in killing invading pathogens such as bacteria, fungi, parasites, and viruses. Recent studies show that some AMPs are active against pathogens resistant to conventional antibiotics. Hence, AMPs are used widely in medicine, food preservation, and agriculture.
The structure-activity relationship study to reveal peptide physicochemical parameters important for its antimicrobial activity and high therapeutic index requires thorough information on the structure (chemical, 3D), and the activity of experimentally tested natural and artificial peptides. This type of information includes posttranslational modifications (chemical groups bound to the N and C termini of peptide; bonds; one particular amino acid modifications) and 3D structures of peptides, their antimicrobial and hemolytic (cytotoxic) activities, and experimental conditions for their activity evaluation.
DBAASP provides users with information on the detailed structure (chemical, 3D) and antimicrobial activity of peptides against particular target species. The database contains information on ribosomal, non-ribosomal, and synthetic peptides that show antimicrobial activity as Monomers, Multimers, and Multi-Peptides.
DBAASP offers data on synergistic activities. Data includes the combined activity of the specific peptide from the database with another peptide or antimicrobial against the particular target strain. The data is represented as the FICI (Fractional Inhibitory Concentration Index) value.
Benefits and Features
DBAASP is the depository for the necessary information for structure-activity relationship study.
Prediction service allows revealing whether the queried peptides have antimicrobial potential based on their amino acid sequence information only. The tools help to create the task-oriented design of the new antibiotics with high accuracy of prediction and consequently reduce production costs.
DBAASP offers users to search for activities of peptides by particular target species and obtain the search results as the ranking list of activity values.
DBAASP allows forming of experimentally validated positive (AMP) or negative (non-AMP) sets of peptides against particular target species. Consequently, DBAASP provides a machine-learning-based prediction tool and an effective method for designing new antibiotics.
Malak Pirtskhalava, Anthony A Amstrong, Maia Grigolava, Mindia Chubinidze, Evgenia Alimbarashvili, Boris Vishnepolsky, Andrei Gabrielian, Alex Rosenthal, Darrell E Hurt, Michael Tartakovsky, DBAASP v3: database of antimicrobial/cytotoxic activity and structure of peptides as a resource for development of new therapeutics, Nucleic Acids Research, Volume 49, Issue D1, 8 January 2021, Pages D288–D297, https://doi.org/10.1093/nar/gkaa991