Development of Antimicrobial Peptide Prediction Tool for Aquaculture Industries

Abstract

Microbial diseases in fish, plant, animal and human are rising constantly; thus, discovery of their antidote is imperative. The use of antibiotic in aquaculture further compounds the problem by development of resistance and consequent consumer health risk by bio-magnification. Antimicrobial peptides (AMPs) have been highly promising as natural alternative to chemical antibiotics. Though AMPs are molecules of innate immune defense of all advance eukaryotic organisms, fish being heavily dependent on their innate immune defense has been a good source of AMPs with much wider applicability. Machine learning-based prediction method using wet laboratory-validated fish AMP can accelerate the AMP discovery using available fish genomic and proteomic data. Earlier AMP prediction servers are based on multi-phyla/species data, and we report here the world's first AMP prediction server in fishes. It is freely accessible at http://webapp.cabgrid.res.in/fishamp/ . A total of 151 AMPs related to fish collected from various databases and published literature were taken for this study. For model development and prediction, N-terminus residues, C-terminus residues and full sequences were considered. Best models were with kernels polynomial-2, linear and radial basis function with accuracy of 97, 99 and 97 %, respectively. We found that performance of support vector machine-based models is superior to artificial neural network. This in silico approach can drastically reduce the time and cost of AMP discovery. This accelerated discovery of lead AMP molecules having potential wider applications in diverse area like fish and human health as substitute of antibiotics, immunomodulator, antitumor, vaccine adjuvant and inactivator, and also for packaged food can be of much importance for industries.

Rice Husk Silica Enhances Innate Immune in Zebrafish (Danio rerio) and Improves Resistance to Aeromonas hydrophila and Streptococcus iniae Infection

“…Thus, the development of alternatives to antibiotics for biocontrol in aquaculture is quite important and urgent. Alternative strategies to antibiotics, such as vaccines [5], antimicrobial peptides [6], probiotics [7,8], natural extracts, and their bioactive compounds [9,10], have been developed as antimicrobials or immunostimulators for disease control in aquaculture. Although some alternatives are workable for disease control in the laboratory, they are difficult to apply practically in aquaculture due to their high cost and lack of ease of use.…”

Cytotoxicity and antimicrobial activity of synthetic peptides alone or in combination with conventional antimicrobials against fish pathogenic bacteria

“…Due to the requirement for novel antimicrobials in aquaculture, as a result of widespread resistance to many important antibiotics, and consequent consumer health risk by bio‐magnification (Gautam et al . 2016), several attempts have been made to explore new, environmentally friendly antimicrobial drugs from natural sources, including virus (Culot et al . 2019), plant (Devi et al .…”

iDEF-PseRAAC: Identifying the Defensin Peptide by Using Reduced Amino Acid Composition Descriptor

“…The SVM model have better predictive power because they can reduce noise on the dataset. The basic idea of SVM is to construct an N -dimensional space hyperplane based on finite sequence sample information, and then map the feature vector X~ in the input space to the high-dimensional Hilbert space through the kernel function, 34,35 so as to infer which category belongs to the same species. 36 The trained SVM can be speculated which category they belong to.…”

“…And 4 types of kernel functions can be chosen for prediction in the software, including linear functions, polynomial functions, S-shaped functions, and radial basis functions (RBFs). 20 The best classification hyperplane was obtained by RBF, 36 which was shown as follows 34 :…”