The Antimicrobial Peptides (AMPs) have emerged as an alternative solution to fight against multi-drug-resistance infections. However, they have not been translated successfully to the therapeutic application as one would expect since its discovery in the early 1980s. Its limitations are the main reasons why there are many researchers that continue isolating and studying the AMPs. There is the conviction that this type of compounds will enter the marketplace as a valuable antimicrobial weapon in the next years.
During the last decade, the number of AMPs databases has increased thanks to the significant efforts made by researchers in the field. These databases hold thousands of naturally occurring examples and synthetic ones, providing valuable information regarding the structure and functions of AMPs. Particularly, we believe that there is an implicit knowledge that must be discovered and applied in the identification and design of novel antimicrobial agents that mimic the biological activity of AMPs.
- To integrate into one database information about the experimentally validated AMPs from different available sources.
- To extract structural regularities present in the integrated database of AMPs at the level of sequences and 3D structure of antimicrobial peptides.
- To derive new knowledge-based computational methods for the prediction of novel AMPs, using the discovered structural regularities.
- To develop an informatics tool that contributes to the identification and design of novel AMPs, using the knowledge-based computational methods and the integrated database.
Bioinformatics, 31 (15), pp. 2553-2559, 2015, ISSN: 1367-4803.