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ABSTRACT: We previously performed a lipid vesicle-based, high-throughput screen on a 26-residue combinatorial peptide library that was designed de novo to yield membrane permeabilizing peptides that fold into β-sheets. The most active and soluble library members that were identified permeabilized lipid vesicles detectably, but not with high potency. Nonetheless, they were broad-spectrum, membrane-permeabilizing antibiotics with minimum sterilizing activity at low μM concentrations. In an expansion of that work, we recently performed an iterative screen in which an active consensus sequence from that first generation library was used as a template to design a second generation library which was then screened against lipid vesicles at very high stringency. Compared to the consensus sequence from the first library, the most active second generation peptides are highly potent, equilibrium pore-formers in synthetic lipid vesicles. Here we use these first and second generation families of peptides to test the hypothesis that a large increase in potency in bacteria-like lipid vesicles will correlate with a large improvement in antimicrobial activity. The results do not support the hypothesis. Despite a 20-fold increase in potency against bacteria-like lipid vesicles, the second generation peptides are only slightly more active against bacteria, and at the same time, are also more toxic against mammalian cells. The results suggest that a "pipeline" strategy towards the optimization of antimicrobial peptides could begin with a vesicle-based screen for identifying families with broad-spectrum activity, but will also need to include screening or optimization steps that are done under conditions that are more directly relevant to possible therapeutic applications. © 2013 Wiley Periodicals, Inc. Biopolymers, 2013.
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ABSTRACT: We previously reported the development of a highly accurate statistical algorithm for identifying β-barrel outer membrane proteins or transmembrane β-barrels (TMBBs), from genomic sequence data of Gram-negative bacteria (Freeman,T.C. and Wimley,W.C. (2010) Bioinformatics, 26, 1965-1974). We have now applied this identification algorithm to all available Gram-negative bacterial genomes (over 600 chromosomes) and have constructed a publicly available, searchable, up-to-date, database of all proteins in these genomes. For each protein in the database, there is information on (i) β-barrel membrane protein probability for identification of β-barrels, (ii) β-strand and β-hairpin propensity for structure and topology prediction, (iii) signal sequence score because most TMBBs are secreted through the inner membrane translocon and, thus, have a signal sequence, and (iv) transmembrane α-helix predictions, for reducing false positive predictions. This information is sufficient for the accurate identification of most β-barrel membrane proteins in these genomes. In the database there are nearly 50 000 predicted TMBBs (out of 1.9 million total putative proteins). Of those, more than 15 000 are 'hypothetical' or 'putative' proteins, not previously identified as TMBBs. This wealth of genomic information is not available anywhere else. The TMBB genomic database is available at http://beta-barrel.tulane.edu/. email@example.com.
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