Generic placeholder image

Current Computer-Aided Drug Design


ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Machine Learning in the Rational Design of Antimicrobial Peptides

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

Volume 10, Issue 3, 2014

Page: [183 - 190] Pages: 8

DOI: 10.2174/1573409910666140624124807

Price: $65


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.

Next »

Rights & Permissions Print Export Cite as
© 2023 Bentham Science Publishers | Privacy Policy