Classification of Antimicrobial Peptides by Using the p-spectrum Kernel and Support Vector Machines

Abstract

In the last decades, antibiotic resistance of pathogenic microorganisms constitutes a great problem of public health at global level. Multidrug-resistant bacteria cannot be controlled with the existing medications causing thousands of deaths every year. In the fight against these bacteria, antimicrobial peptides have appeared as a promising solution as therapeutic agents against pathogens. For this reason, rational design of these chemical compounds have been explored by the scientific community in order to achieve significant improvements that could lead to the discovery of new antibacterial medicine. In this sense, the present work proposes the use of the p-spectrum kernel with support vector machines to classify antimicrobial peptides, thus considering only the information of the order of the amino acids inside the peptide sequences. The results were satisfactory and suggest that this information should be considered in the rational design of antimicrobial peptides.