Synthetic antimicrobial peptides generation using recurrent neural networks

Synthetic antimicrobial peptides generation using recurrent neural networks

Abstract The antimicrobial peptides (AMPs) have taken importance in the development of new antibiotics because of their role as an inhibitor, not only of bacteria but also of viruses, fungi and parasites, among others. Since the discovery of AMPs, thousands have been reported, however, many of them are not suitable for therapeutic applications due to their long amino acid sequences, low antimicrobial potency and high production costs. In this work, we propose to use recurrent neural networks (RNN) with LSTM cells in order to generate more potent and economical peptides. We perform different experiments generating synthetic AMPs between 12 and 20 amino acids. The results show that we can use RNN and improve the generation process compared with the template method.

Saved in:
Bibliographic Details
Main Authors: Vélez,Andrés, Mera,Carlos, Orduz,Sergio, Branch,John W.
Format: Digital revista
Language:English
Published: Universidad Nacional de Colombia 2021
Online Access:http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532021000100210
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:scielo:S0012-73532021000100210
record_format ojs
spelling oai:scielo:S0012-735320210001002102021-06-03Synthetic antimicrobial peptides generation using recurrent neural networksVélez,AndrésMera,CarlosOrduz,SergioBranch,John W. antimicrobial resistance synthetic peptides virtual screening deep learning Abstract The antimicrobial peptides (AMPs) have taken importance in the development of new antibiotics because of their role as an inhibitor, not only of bacteria but also of viruses, fungi and parasites, among others. Since the discovery of AMPs, thousands have been reported, however, many of them are not suitable for therapeutic applications due to their long amino acid sequences, low antimicrobial potency and high production costs. In this work, we propose to use recurrent neural networks (RNN) with LSTM cells in order to generate more potent and economical peptides. We perform different experiments generating synthetic AMPs between 12 and 20 amino acids. The results show that we can use RNN and improve the generation process compared with the template method.info:eu-repo/semantics/openAccessUniversidad Nacional de ColombiaDYNA v.88 n.216 20212021-03-01info:eu-repo/semantics/articletext/htmlhttp://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532021000100210en10.15446/dyna.v88n216.88799
institution SCIELO
collection OJS
country Colombia
countrycode CO
component Revista
access En linea
databasecode rev-scielo-co
tag revista
region America del Sur
libraryname SciELO
language English
format Digital
author Vélez,Andrés
Mera,Carlos
Orduz,Sergio
Branch,John W.
spellingShingle Vélez,Andrés
Mera,Carlos
Orduz,Sergio
Branch,John W.
Synthetic antimicrobial peptides generation using recurrent neural networks
author_facet Vélez,Andrés
Mera,Carlos
Orduz,Sergio
Branch,John W.
author_sort Vélez,Andrés
title Synthetic antimicrobial peptides generation using recurrent neural networks
title_short Synthetic antimicrobial peptides generation using recurrent neural networks
title_full Synthetic antimicrobial peptides generation using recurrent neural networks
title_fullStr Synthetic antimicrobial peptides generation using recurrent neural networks
title_full_unstemmed Synthetic antimicrobial peptides generation using recurrent neural networks
title_sort synthetic antimicrobial peptides generation using recurrent neural networks
description Abstract The antimicrobial peptides (AMPs) have taken importance in the development of new antibiotics because of their role as an inhibitor, not only of bacteria but also of viruses, fungi and parasites, among others. Since the discovery of AMPs, thousands have been reported, however, many of them are not suitable for therapeutic applications due to their long amino acid sequences, low antimicrobial potency and high production costs. In this work, we propose to use recurrent neural networks (RNN) with LSTM cells in order to generate more potent and economical peptides. We perform different experiments generating synthetic AMPs between 12 and 20 amino acids. The results show that we can use RNN and improve the generation process compared with the template method.
publisher Universidad Nacional de Colombia
publishDate 2021
url http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532021000100210
work_keys_str_mv AT velezandres syntheticantimicrobialpeptidesgenerationusingrecurrentneuralnetworks
AT meracarlos syntheticantimicrobialpeptidesgenerationusingrecurrentneuralnetworks
AT orduzsergio syntheticantimicrobialpeptidesgenerationusingrecurrentneuralnetworks
AT branchjohnw syntheticantimicrobialpeptidesgenerationusingrecurrentneuralnetworks
_version_ 1755932763810168832

Similar Items