Machine learning in the rational design of antimicrobial peptides

Current Computer-aided Drug Design
Paola Rondón-VillarrealR 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.

Citations

Aug 10, 2019·Critical Reviews in Clinical Laboratory Sciences·Adriana Barreto-SantamaríaHernando Curtidor
Aug 12, 2017·Small·Max PillongGisbert Schneider
Feb 5, 2021·ACS Nano·Marcelo D T TorresCesar de la Fuente-Nunez
May 17, 2019·Current Opinion in Colloid & Interface Science·Michelle W LeeGerard C L Wong
Jun 25, 2021·Journal of Chemical Information and Modeling·Pietro G A AronicaChandra S Verma
Sep 24, 2021·The Journal of General Virology·Hovakim ZakaryanGuangshun Wang
Aug 24, 2018··M. Stanley FujimotoMark J. Clement

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