ADAPTABLE: a web platform for antimicrobial peptides
Résumé
Antimicrobial peptides (AMPs) are small molecules produced by all living
systems, which can be considered part of the innate immune response to
pathogens. Due to their extraordinary variety of biological and chemical
activities (antibacterial, antibiofilm, antiviral, antifungal, antiparasitic,
anticancer, anti-inflammatory, immunomodulatory...), they have received
significant attention, especially as candidate drugs to face the threat of superbacteria. The study of their multiple modes of action requires a deep
understanding of their properties, which are often hidden in their sequence.
We present a web platform, ADAPTABLE (http://gec.u-picardie.fr/adaptable),
able to cluster sequence-related peptides after collection, uniformization and
data-merging of most of the main databases available on the web. Our
methodology is the only one standardizing modified amino acids, often a key
feature for the activity of AMPs. ADAPTABLE is a flexible tool that allows the
researcher to tailor the analysis by choosing among a variety of optional
parameters (covering multiple chemical and biological features and including
target organisms and standardized experimental activity concentration against
them). The performed clustering can highlight the potential properties of already
existing and/or user-supplied peptides.
In the era of antimicrobial resistance, ADAPTABLE can assist the research
community in the complex field of AMPs. With thousands of existing sequences
and hundreds discovered every year, a unifying and standardizing platform is
urgently needed to combine a large amount of information, currently scattered
among different web-resources (more than 25 AMPs, chemical and
microbiological databases). ADAPTABLE provides tools that can be used to: i)
design new peptides using motifs responsible for the specificity towards a
specific organism; ii) predict several properties of a generic peptide sequence;
iii) discover new potential activities of pre-existing sequences not yet tested
experimentally; iv) generate an optimal scaffold for drug design, thanks to the
mathematical analysis of the clustered families.