Welcome to Antimicrobial Peptide Prediction Server for Fishes

Antimicrobial peptides (AMPs) are the hosts' defence molecules that have been identified as an essential part of innate immunity in response to microbial challenges.The hydrophobic and hydrophilic sides of these evolutionary conserved, positively charged peptides enables the molecule to be soluble in aqueous environments and also enter the lipid rich membranes.These peptides, having broad spectrum of antimicrobial activity against microbes such as gram positive and negative bacteria, viruses, fungi, parasites etc ,mediate the antimicrobial function of innate immunity.AMPs are classified on the basis of their distribution, net charges and structures.

In the past years, developed antibiotics have been reported as resistant to microorganism. The continuous increase of pathogens as well as resistance against antibiotics have led the researchers to search for new antimicrobial compounds from diverse sources. Among these compounds, AntiMicrobial Peptides (AMPs) appears to be one of the most propitious candidate for clinical development in order to inhibit microbial activity because of their target specificity, speed of action and producing innate immunity in organism.

Antibiotics use in aquaculture is not preferred due to associated problem of resistance development and consumer health risk. Due to associated toxicity, carcinogenicity, sensitivity or bio-accumulation leading to adverse human health, many of antibiotics viz., Malachite green, Nitrofurans, floroquninolones etc are banned.

Antimicrobial peptides (AMPs), has been attracting extensive attention as natural alternative to chemical antibiotics. The present AMP prediction server is a computational tool specific for AMP prediction in aquaculture and developed using machine learning techniques viz., ANN and SVM.

The server has been developed for prediction for N-terminus residues, C-terminus residues and full sequences with accuracies 95%, 99% and 97%, respectively using SVM technique.

AMPs predicted through this server can be modified at genetic level for better antimicrobial activity to be used in industries. The species specific antimicrobial peptide prediction tool can aid in the discovery of unknown peptides sequences that may be effectual novel therapeutics.