Biofilm is a complex microbial enviroment where these microbes used to communicate and co-operate with other cells via releasing and resposding to small diffusible signal molecules. Biofilm inhibiting peptides (BIPs) can inhibit multiple steps independently including quorum sensing, inhibition of cell adhesion to the other cells and surfaces, activation of genes responsible for motility, down-regulation of genes responsible for production of EPS and causing direct bacterial killing. Presently, most of the available bioinformatics tools largely predict antimicrobial peptides and none of them have their focus as BIPs. Therefore, we have developed a machine learning based tool for the identification of novel and effective biofilm inhibitory peptides (BIPs).


Other section/tools have been incorporated in the webserver to provide wide range of analysis.:
  • Peptide prediction: In this section, user can submit peptide of 4-45 amino acid length and can predict the biofilm inhibitory property of peptides.
  • Protein Scan: This tool enables user to identify biofilm inhibitory short regions in a full length protein/amino acid sequence. Here user can select desired length of peptide for prediction.
  • BIP Mapping: To assist user mapping experimentally validated biofilm inhibitory peptides on its query sequence, we have provided this tool. In this tool user can get the query mapped with biofilm inhibitory peptides and links to related assay in BaAMP database.
  • Similarity Search: In contrast to the BIP mapping module where exact matches with experimental data is seen, this tool performs Smith Watermann search of query sequence in database of experimentally validated biofilm inhibitory peptides.