Literature DB >> 30800727

Amino Acid Composition Determines Peptide Activity Spectrum and Hot-Spot-Based Design of Merecidin.

Xiuqing Wang1,2, Biswajit Mishra1, Tamara Lushnikova1, Jayaram Lakshmaiah Narayana1, Guangshun Wang1.   

Abstract

There is a great interest in developing the only human cathelicidin into therapeutic molecules. The major antimicrobial region of human LL-37 corresponds to residues 17-32. The resultant peptide GF-17 shows a broad spectrum of antimicrobial activity against both Gram-positive and negative bacteria. By reducing the hydrophobic content, we previously succeeded in converting the broad-spectrum GF-17 to two narrow-spectrum peptides (GF-17d3 and KR-12) with activity against Gram-negative bacteria. This study demonstrates that substitution of multiple basic amino acids by hydrophobic alanines makes a broad-spectrum peptide 17BIPHE2 (designed based on GF-17d3) active against Staphylococcal pathogens but not other bacteria tested. Taken together, our results reveal distinct charge and hydrophobic requirements for peptides to kill Gram-positive or Gram-negative bacteria. This finding is in line with the bioinformatics analysis of the peptides in the Antimicrobial Peptide Database (http://aps.unmc.edu/AP). In addition, a hot spot arginine is identified and used to design merecidin with reduced toxicity to human cells. Merecidin protects wax moth larvae (Galleria mellonella) from the infection of methicillin-resistant S. aureus USA300. These new selective peptides constitute interesting candidates for future development.

Entities:  

Keywords:  Antimicrobial peptides; cathelicidin; charge; hydrophobic content; peptide design

Year:  2018        PMID: 30800727      PMCID: PMC6379907          DOI: 10.1002/adbi.201700259

Source DB:  PubMed          Journal:  Adv Biosyst


  10 in total

1.  The antimicrobial peptide database provides a platform for decoding the design principles of naturally occurring antimicrobial peptides.

Authors:  Guangshun Wang
Journal:  Protein Sci       Date:  2019-08-10       Impact factor: 6.725

2.  Resistome of Staphylococcus aureus in Response to Human Cathelicidin LL-37 and Its Engineered Antimicrobial Peptides.

Authors:  Radha M Golla; Biswajit Mishra; Xiangli Dang; Jayaram Lakshmaiah Narayana; Amy Li; Libin Xu; Guangshun Wang
Journal:  ACS Infect Dis       Date:  2020-05-11       Impact factor: 5.084

3.  Modulation of antimicrobial potency of human cathelicidin peptides against the ESKAPE pathogens and in vivo efficacy in a murine catheter-associated biofilm model.

Authors:  Jayaram Lakshmaiah Narayana; Biswajit Mishra; Tamara Lushnikova; Radha M Golla; Guangshun Wang
Journal:  Biochim Biophys Acta Biomembr       Date:  2019-07-15       Impact factor: 3.747

4.  Machine Learning Prediction of Antimicrobial Peptides.

Authors:  Guangshun Wang; Iosif I Vaisman; Monique L van Hoek
Journal:  Methods Mol Biol       Date:  2022

5.  Short and Robust Anti-Infective Lipopeptides Engineered Based on the Minimal Antimicrobial Peptide KR12 of Human LL-37.

Authors:  Jayaram Lakshmaiah Narayana; Radha Golla; Biswajit Mishra; Xiuqing Wang; Tamara Lushnikova; Yingxia Zhang; Atul Verma; Vikas Kumar; Jingwei Xie; Guangshun Wang
Journal:  ACS Infect Dis       Date:  2021-04-23       Impact factor: 5.578

6.  Temporin-Like Peptides Show Antimicrobial and Anti-Biofilm Activities against Streptococcus mutans with Reduced Hemolysis.

Authors:  Hanqi Wei; Zhipeng Xie; Xiuchuan Tan; Ran Guo; Yanting Song; Xi Xie; Rong Wang; Lushuang Li; Manchuriga Wang; Yingxia Zhang
Journal:  Molecules       Date:  2020-12-04       Impact factor: 4.411

Review 7.  The Potential of Human Peptide LL-37 as an Antimicrobial and Anti-Biofilm Agent.

Authors:  Kylen E Ridyard; Joerg Overhage
Journal:  Antibiotics (Basel)       Date:  2021-05-29

8.  Bioinformatic Analysis of 1000 Amphibian Antimicrobial Peptides Uncovers Multiple Length-Dependent Correlations for Peptide Design and Prediction.

Authors:  Guangshun Wang
Journal:  Antibiotics (Basel)       Date:  2020-08-07

9.  Sequence Permutation Generates Peptides with Different Antimicrobial and Antibiofilm Activities.

Authors:  Biswajit Mishra; Jayaram Lakshmaiah Narayana; Tamara Lushnikova; Yingxia Zhang; Radha M Golla; D Zarena; Guangshun Wang
Journal:  Pharmaceuticals (Basel)       Date:  2020-09-25

10.  Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features.

Authors:  Onkar Singh; Wen-Lian Hsu; Emily Chia-Yu Su
Journal:  BMC Bioinformatics       Date:  2021-07-30       Impact factor: 3.169

  10 in total

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