Current Computer-Aided Drug Design

Subhash C. Basak
Departments of Chemistry, Biochemistry & Molecular Biology University of Minnesota Duluth
Duluth, MN 55811
USA

Back

Machine Learning in the Rational Design of Antimicrobial Peptides

Author(s): Paola Rondon-Villarreal, Daniel A. Sierra, Rodrigo Torres.

Abstract:

One of the most important public health issues is the microbial and bacterial resistance to conventional antibiotics by pathogen microorganisms. In recent years, many researches have been focused on the development of new antibiotics. Among these, antimicrobial peptides (AMPs) have raised as a promising alternative to combat antibioticresistant microorganisms. For this reason, many theoretical efforts have been done in the development of new computational tools for the rational design of both better and effective AMPs. In this review, we present an overview of the rational design of AMPs using machine learning techniques and new research fields.

Keywords: Antimicrobial peptides, classification, descriptors, machine learning, QSAR, rational design.

Order Reprints Order Eprints Rights & PermissionsPrintExport

Article Details

VOLUME: 10
ISSUE: 3
Year: 2014
Page: [183 - 190]
Pages: 8
DOI: 10.2174/1573409910666140624124807
Price: $58