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Identification and Characterization of Antimicrobial Peptides with Therapeutic Potential

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ISBN: 9783038424628 9783038424635 Year: Pages: X, 280 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Therapeutics
Added to DOAB on : 2017-12-27 08:54:14
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Antimicrobial peptides are key defense molecules adopted by all life forms to prevent infection. They also have other beneficial effects such as boosting immune response, anticancer, and wound healing. The antiviral effects of antimicrobial peptides have laid the foundations for developing new agents to combat seasonal Flu, HIV-1, RSV, Zika, and Ebola. This eBook is constructed to systematically deal with antimicrobial peptides from a variety of natural sources, including fungi, plants, and animals (insects, fish, amphibians, birds, and reptiles). It covers peptide discovery, antimicrobial activity, 3D structure, mechanisms of action and potential applications. Naturally Occurring Antimicrobial Peptides, an eBook published by the journal Pharmaceuticals, provides a helpful introduction to newcomers and refreshes the minds of veterans.

Special Protein Molecules Computational Identification

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ISBN: 9783038970439 9783038970446 Year: Pages: VIII, 296 Language: english
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Medical technology
Added to DOAB on : 2018-08-09 12:10:11
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It is time consuming and costly to detect new molecules of some special proteins. These special proteins include cytokines, enzymes, cell-penetrating peptides, anticancer peptides, cancer lectins, G-protein-coupled receptors, etc. Researchers often employ computer programs to list some candidates, and to validate the candidates with molecular experiments. These computer programs are key to possible savings on wet experiment costs. Software results with high false positive will lead to high costs in the validation process.In this Special Issue, we focus on these computer program approaches and algorithms. Some "golden features" from protein primary sequences have been proposed for these problems, such as Chou’s PseAAC (pseudo amino acid composition). PseAAC has been tried on nearly all kinds of protein identification, together with SVM (support vector machines, a type of classifier). However, I prefer special features, and classification methods should be proposed for special protein molecules. "Golden features" cannot work well on all kinds of proteins. I hope that submissions will focus on a type of special protein molecule, collect related data sets, obtain better prediction performance (especially low false positives), and develop user-friendly software tools or web servers.

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