De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria
Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics to combat bacterial resistance to conventional drugs. The design of de novo AMPs with high therapeutic indexes, low cost of synthesis, high resistance to proteases and high bioavailability remains a challeng...
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doaj-43a817c4693e4e8bba1a64e1e77fc0112020-11-25T01:22:54ZengMDPI AGPharmaceuticals1424-82472019-06-011228210.3390/ph12020082ph12020082De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative BacteriaBoris Vishnepolsky0George Zaalishvili1Margarita Karapetian2Tornike Nasrashvili3Nato Kuljanishvili4Andrei Gabrielian5Alex Rosenthal6Darrell E. Hurt7Michael Tartakovsky8Maya Grigolava9Malak Pirtskhalava10Ivane Beritashvili Center of Experimental Biomedicine, 0160 Tbilisi, GeorgiaLabarotory of Animal Molecular Biology, Agricultural University of Georgia, 240 David Aghmashenebeli Alley, 0159 Tbilisi, GeorgiaLabarotory of Animal Molecular Biology, Agricultural University of Georgia, 240 David Aghmashenebeli Alley, 0159 Tbilisi, GeorgiaLabarotory of Animal Molecular Biology, Agricultural University of Georgia, 240 David Aghmashenebeli Alley, 0159 Tbilisi, GeorgiaLabarotory of Animal Molecular Biology, Agricultural University of Georgia, 240 David Aghmashenebeli Alley, 0159 Tbilisi, GeorgiaOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USAOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USAOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USAOffice of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USAIvane Beritashvili Center of Experimental Biomedicine, 0160 Tbilisi, GeorgiaIvane Beritashvili Center of Experimental Biomedicine, 0160 Tbilisi, GeorgiaAntimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics to combat bacterial resistance to conventional drugs. The design of de novo AMPs with high therapeutic indexes, low cost of synthesis, high resistance to proteases and high bioavailability remains a challenge. Such design requires computational modeling of antimicrobial properties. Currently, most computational methods cannot accurately calculate antimicrobial potency against particular strains of bacterial pathogens. We developed a tool for AMP prediction (Special Prediction (SP) tool) and made it available on our Web site (https://dbaasp.org/prediction). Based on this tool, a simple algorithm for the design of de novo AMPs (DSP) was created. We used DSP to design short peptides with high therapeutic indexes against gram-negative bacteria. The predicted peptides have been synthesized and tested in vitro against a panel of gram-negative bacteria, including drug resistant ones. Predicted activity against <i>Escherichia coli ATCC 25922</i> was experimentally confirmed for 14 out of 15 peptides. Further improvements for designed peptides included the synthesis of D-enantiomers, which are traditionally used to increase resistance against proteases. One synthetic D-peptide (SP15D) possesses one of the lowest values of minimum inhibitory concentration (MIC) among all DBAASP database short peptides at the time of the submission of this article, while being highly stable against proteases and having a high therapeutic index. The mode of anti-bacterial action, assessed by fluorescence microscopy, shows that SP15D acts similarly to cell penetrating peptides. SP15D can be considered a promising candidate for the development of peptide antibiotics. We plan further exploratory studies with the SP tool, aiming at finding peptides which are active against other pathogenic organisms.https://www.mdpi.com/1424-8247/12/2/82antimicrobial peptidespredictive modelsdrug design |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Boris Vishnepolsky George Zaalishvili Margarita Karapetian Tornike Nasrashvili Nato Kuljanishvili Andrei Gabrielian Alex Rosenthal Darrell E. Hurt Michael Tartakovsky Maya Grigolava Malak Pirtskhalava |
spellingShingle |
Boris Vishnepolsky George Zaalishvili Margarita Karapetian Tornike Nasrashvili Nato Kuljanishvili Andrei Gabrielian Alex Rosenthal Darrell E. Hurt Michael Tartakovsky Maya Grigolava Malak Pirtskhalava De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria Pharmaceuticals antimicrobial peptides predictive models drug design |
author_facet |
Boris Vishnepolsky George Zaalishvili Margarita Karapetian Tornike Nasrashvili Nato Kuljanishvili Andrei Gabrielian Alex Rosenthal Darrell E. Hurt Michael Tartakovsky Maya Grigolava Malak Pirtskhalava |
author_sort |
Boris Vishnepolsky |
title |
De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria |
title_short |
De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria |
title_full |
De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria |
title_fullStr |
De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria |
title_full_unstemmed |
De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria |
title_sort |
de novo design and in vitro testing of antimicrobial peptides against gram-negative bacteria |
publisher |
MDPI AG |
series |
Pharmaceuticals |
issn |
1424-8247 |
publishDate |
2019-06-01 |
description |
Antimicrobial peptides (AMPs) have been identified as a potentially new class of antibiotics to combat bacterial resistance to conventional drugs. The design of de novo AMPs with high therapeutic indexes, low cost of synthesis, high resistance to proteases and high bioavailability remains a challenge. Such design requires computational modeling of antimicrobial properties. Currently, most computational methods cannot accurately calculate antimicrobial potency against particular strains of bacterial pathogens. We developed a tool for AMP prediction (Special Prediction (SP) tool) and made it available on our Web site (https://dbaasp.org/prediction). Based on this tool, a simple algorithm for the design of de novo AMPs (DSP) was created. We used DSP to design short peptides with high therapeutic indexes against gram-negative bacteria. The predicted peptides have been synthesized and tested in vitro against a panel of gram-negative bacteria, including drug resistant ones. Predicted activity against <i>Escherichia coli ATCC 25922</i> was experimentally confirmed for 14 out of 15 peptides. Further improvements for designed peptides included the synthesis of D-enantiomers, which are traditionally used to increase resistance against proteases. One synthetic D-peptide (SP15D) possesses one of the lowest values of minimum inhibitory concentration (MIC) among all DBAASP database short peptides at the time of the submission of this article, while being highly stable against proteases and having a high therapeutic index. The mode of anti-bacterial action, assessed by fluorescence microscopy, shows that SP15D acts similarly to cell penetrating peptides. SP15D can be considered a promising candidate for the development of peptide antibiotics. We plan further exploratory studies with the SP tool, aiming at finding peptides which are active against other pathogenic organisms. |
topic |
antimicrobial peptides predictive models drug design |
url |
https://www.mdpi.com/1424-8247/12/2/82 |
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