TY - JOUR
T1 - Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides
AU - Rodríguez-Cerdeira, Carmen
AU - Molares-Vila, Alberto
AU - Sánchez-Cárdenas, Carlos Daniel
AU - Velásquez-Bámaca, Jimmy Steven
AU - Martínez-Herrera, Erick
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/3
Y1 - 2023/3
N2 - Antifungal peptides (AFPs) comprise a group of substances with a broad spectrum of activities and complex action mechanisms. They develop in nature via an evolutionary process resulting from the interactions between hosts and pathogens. The AFP database is experimentally verified and curated from research articles, patents, and public databases. In this review, we compile information about the primary databases and bioinformatics tools that have been used in the discovery of AFPs during the last 15 years. We focus on the classification and prediction of AFPs using different physicochemical properties, such as polarity, hydrophobicity, hydrophilicity, mass, acidic, basic, and isoelectric indices, and other structural properties. Another method for discovering AFPs is the implementation of a peptidomic approach and bioinformatics filtering, which gave rise to a new family of peptides that exhibit a broad spectrum of antimicrobial activity against Candida albicans with low hemolytic effects. The application of machine intelligence in the sphere of biological sciences has led to the development of automated tools. The progress made in this area has also paved the way for producing new drugs more quickly and effectively. However, we also identified that further advancements are still needed to complete the AFP libraries.
AB - Antifungal peptides (AFPs) comprise a group of substances with a broad spectrum of activities and complex action mechanisms. They develop in nature via an evolutionary process resulting from the interactions between hosts and pathogens. The AFP database is experimentally verified and curated from research articles, patents, and public databases. In this review, we compile information about the primary databases and bioinformatics tools that have been used in the discovery of AFPs during the last 15 years. We focus on the classification and prediction of AFPs using different physicochemical properties, such as polarity, hydrophobicity, hydrophilicity, mass, acidic, basic, and isoelectric indices, and other structural properties. Another method for discovering AFPs is the implementation of a peptidomic approach and bioinformatics filtering, which gave rise to a new family of peptides that exhibit a broad spectrum of antimicrobial activity against Candida albicans with low hemolytic effects. The application of machine intelligence in the sphere of biological sciences has led to the development of automated tools. The progress made in this area has also paved the way for producing new drugs more quickly and effectively. However, we also identified that further advancements are still needed to complete the AFP libraries.
KW - antifungal peptides
KW - bioinformatics tools
KW - computational tools
KW - databases
UR - http://www.scopus.com/inward/record.url?scp=85152649822&partnerID=8YFLogxK
U2 - 10.3390/antibiotics12030566
DO - 10.3390/antibiotics12030566
M3 - Artículo de revisión
C2 - 36978434
AN - SCOPUS:85152649822
SN - 2079-6382
VL - 12
JO - Antibiotics
JF - Antibiotics
IS - 3
M1 - 566
ER -