Accelerating the Discovery and Design of Antimicrobial Peptides with Artificial Intelligence.

Methods Mol Biol

Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV-IPN), Unidad de Genómica Avanzada, Laboratorio Nacional de Genómica para la Biodiversidad (Langebio), Irapuato, Guanajuato, Mexico.

Published: September 2023

Peptides modulate many processes of human physiology targeting ion channels, protein receptors, or enzymes. They represent valuable starting points for the development of new biologics against communicable and non-communicable disorders. However, turning native peptide ligands into druggable materials requires high selectivity and efficacy, predictable metabolism, and good safety profiles. Machine learning models have gradually emerged as cost-effective and time-saving solutions to predict and generate new proteins with optimal properties. In this chapter, we will discuss the evolution and applications of predictive modeling and generative modeling to discover and design safe and effective antimicrobial peptides. We will also present their current limitations and suggest future research directions, applicable to peptide drug design campaigns.

Download full-text PDF

Source
http://dx.doi.org/10.1007/978-1-0716-3441-7_18DOI Listing

Publication Analysis

Top Keywords

antimicrobial peptides
8
accelerating discovery
4
discovery design
4
design antimicrobial
4
peptides artificial
4
artificial intelligence
4
intelligence peptides
4
peptides modulate
4
modulate processes
4
processes human
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!