Antifungal Peptide Modeling, Folding and Mimetic Design

The antifungal peptides represent diverse structures for drug design. Unfortunately, they provide inferior drug candidates because of their low oral bioavailability, potential immunogenicity, poor in vivo metabolic stability and high molecular weight. Recent efforts have focused on the creation o...

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Bibliographic Details
Main Author: Moradi, Shoeib
Format: Thesis
Language:English
English
Published: 2009
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/9822/1/FBSB_2009_30_A.pdf
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Summary:The antifungal peptides represent diverse structures for drug design. Unfortunately, they provide inferior drug candidates because of their low oral bioavailability, potential immunogenicity, poor in vivo metabolic stability and high molecular weight. Recent efforts have focused on the creation of non-natural peptide mimetics. Their artificial backbone makes most peptidomimetics resistant to degradative enzymes, thus, increasing the stability of peptidomimetic drugs in the body. In the present study, four antifungal peptidomimetics structures named C1 to C4 were designed based on the antifungal decapeptide crystallized structure of Pep-1 using bioinformatics tools. Structures C1 and C2 belong to the N-terminal part of Pep-1 and C3 and C4 belong to the C-terminal amino acid sequence part of Pep-1. Minimum inhibitory concentrations (MIC) of these structures were estimated against Aspergillus niger N402, Candida albicans ATCC 10231, and Saccharomyces cerevisiae PTCC 5052. Structures C2 and C1 showed more potent antifungal activities against these fungal strains compared to C3 and C4, respectively. This demonstrated that the N-terminal part is more potent for antifungal activity and indicated that the N-terminal part of antifungal peptides is more active and important for antifungal activity than the C-terminal. Structure C2 was demonstrated to be more active against these microorganisms and could be used as a potential target for future antifungal peptidomimetics studies. Important factors/descriptors of 63 antifungal peptides have been studied using Artificial Neural Network (ANN). The most important factors determined were amino acid number 1 (S1), Log P, and their α-helix contents. This is the first study on the structure of C1 to C4 peptidomimetics on Aspergillus niger N402, Candida albicans ATCC 10231, and Saccharomyces cerevisiae PTCC 5052.