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Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides.

ABSTRACT: 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.

SUBMITTER: Rodriguez-Cerdeira C

PROVIDER: S-EPMC10044696 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides.

Rodríguez-Cerdeira Carmen C Molares-Vila Alberto A Sánchez-Cárdenas Carlos Daniel CD Velásquez-Bámaca Jimmy Steven JS Martínez-Herrera Erick E

Antibiotics (Basel, Switzerland) 20230313 3

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 ...[more]

PMID: 36978434

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Project description:Candida albicans, a ubiquitous opportunistic fungal pathogen, plays a pivotal role in human health and disease. As a commensal organism, it normally resides harmlessly within the human microbiota. However, under certain conditions, C. albicans can transition into a pathogenic state, leading to various infections collectively known as candidiasis. With the increasing prevalence of immunocompromised individuals and the widespread use of invasive medical procedures, candidiasis has become a significant public health concern. The emergence of drug-resistant strains further complicates treatment options, highlighting the urgent need for alternative therapeutic strategies. Antifungal peptides (AFPs) have gained considerable attention as potential candidates for combating Candida spp. infections. These naturally occurring peptides possess broad-spectrum antimicrobial activity, including specific efficacy against C. albicans. AFPs exhibit several advantageous properties, such as rapid killing kinetics, low propensity for resistance development, and diverse mechanisms of action, making them promising alternatives to conventional antifungal agents. In recent years, extensive research has focused on discovering and developing novel AFPs with improved efficacy and selectivity against Candida species. Advances in biotechnology and synthetic peptide design have enabled the modification and optimization of natural peptides, enhancing their stability, bioavailability, and therapeutic potential. Nevertheless, several challenges must be addressed before AFPs can be widely implemented in clinical practice. These include optimizing peptide stability, enhancing delivery methods, overcoming potential toxicity concerns, and conducting comprehensive preclinical and clinical studies. This commentary presents a short overview of candidemia and AFP; articles and reviews published in the last 10 years were searched on The National Library of Medicine (National Center for Biotechnology Information-NIH-PubMed). The terms used were C. albicans infections, antimicrobial peptides, antifungal peptides, antifungal peptides mechanisms of action, candidemia treatments and guidelines, synthetic peptides and their challenges, and antimicrobial peptides in clinical trials as the main ones. Older publications were cited if they brought some relevant concept or helped to bring a perspective into our narrative. Articles older than 20 years and those that appeared in PubMed but did not match our goal to bring updated information about using antifungal peptides as an alternative to C. albicans infections were not considered.

Project description:Among various delivery systems for vaccine and drug delivery, cell-penetrating peptides (CPPs) have been known as a potent delivery system because of their capability to penetrate cell membranes and deliver some types of cargoes into cells. Several CPPs were found in the proteome of viruses such as Tat originated from human immunodeficiency virus-1 (HIV-1), and VP22 derived from herpes simplex virus-1 (HSV-1). In the current study, a wide-range of CPPs was identified in the proteome of SARS-CoV-2, a new member of coronaviruses family, using in silico analyses. These CPPs may play a main role for high penetration of virus into cells and infection of host. At first, we submitted the proteome of SARS-CoV-2 to CellPPD web server that resulted in a huge number of CPPs with ten residues in length. Afterward, we submitted the predicted CPPs to C2Pred web server for evaluation of the probability of each peptide. Then, the uptake efficiency of each peptide was investigated using CPPred-RF and MLCPP web servers. Next, the physicochemical properties of the predicted CPPs including net charge, theoretical isoelectric point (pI), amphipathicity, molecular weight, and water solubility were calculated using protparam and pepcalc tools. In addition, the probability of membrane binding potential and cellular localization of each CPP were estimated by Boman index using APD3 web server, D factor, and TMHMM web server. On the other hand, the immunogenicity, toxicity, allergenicity, hemolytic potency, and half-life of CPPs were predicted using various web servers. Finally, the tertiary structure and the helical wheel projection of some CPPs were predicted by PEP-FOLD3 and Heliquest web servers, respectively. These CPPs were divided into: a) CPP containing tumor homing motif (RGD) and/or tumor penetrating motif (RXXR); b) CPP with the highest Boman index; c) CPP with high half-life (~100 hour) in mammalian cells, and d) CPP with +5.00 net charge. Based on the results, we found a large number of novel CPPs with various features. Some of these CPPs possess tumor-specific motifs which can be evaluated in cancer therapy. Furthermore, the novel and potent CPPs derived from SARS-CoV-2 may be used alone or conjugated to some sequences such as nuclear localization sequence (NLS) for vaccine and drug delivery.

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Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides.

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Bioinformatics Approaches Applied to the Discovery of Antifungal Peptides.

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