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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Format: | Thesis |
Language: | English English |
Published: |
2009
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Online Access: | http://psasir.upm.edu.my/id/eprint/9822/1/FBSB_2009_30_A.pdf http://psasir.upm.edu.my/id/eprint/9822/ |
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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. |
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