Dataset Information

Fine-Tuning of Alkaline Residues on the Hydrophilic Face Provides a Non-toxic Cationic α-Helical Antimicrobial Peptide Against Antibiotic-Resistant ESKAPE Pathogens.

ABSTRACT: Antibiotic-resistant ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) has become a serious threat to public health worldwide. Cationic α-helical antimicrobial peptides (CαAMPs) have attracted much attention as promising solutions in post-antibiotic era. However, strong hemolytic activity and in vivo inefficacy have hindered their pharmaceutical development. Here, we attempt to address these obstacles by investigating BmKn2 and BmKn2-7, two scorpion-derived CαAMPs with the same hydrophobic face and a distinct hydrophilic face. Through structural comparison, mutant design and functional analyses, we found that while keeping the hydrophobic face unchanged, increasing the number of alkaline residues (i.e., Lys + Arg residues) on the hydrophilic face of BmKn2 reduces the hemolytic activity and broadens the antimicrobial spectrum. Strikingly, when keeping the total number of alkaline residues constant, increasing the number of Lys residues on the hydrophilic face of BmKn2-7 significantly reduces the hemolytic activity but does not influence the antimicrobial activity. BmKn2-7K, a mutant of BmKn2-7 in which all of the Arg residues on the hydrophilic face were replaced with Lys, showed the lowest hemolytic activity and potent antimicrobial activity against antibiotic-resistant ESKAPE pathogens. Moreover, in vivo experiments indicate that BmKn2-7K displays potent antimicrobial efficacy against both the penicillin-resistant S. aureus and the carbapenem- and multidrug-resistant A. baumannii, and is non-toxic at the antimicrobial dosages. Taken together, our work highlights the significant functional disparity of Lys vs Arg in the scorpion-derived antimicrobial peptide BmKn2-7, and provides a promising lead molecule for drug development against ESKAPE pathogens.

SUBMITTER: Luo X

PROVIDER: S-EPMC8319832 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:To create a dataset of PSMs that does not exhibit tryptic bias, we selected PSMs with a uniform distribution of amino acids at the C-terminal peptide positions from two datasets: MassIVE-KB [Wang2018] and PROSPECT [Shouman2022]. The MassIVE-KB dataset contains 30 million PSMs and consists entirely of data generated using trypsin; hence, only a small proportion of the MassIVE-KB peptides do not end in K or R, corresponding to those that appear at the C-terminus of the corresponding protein. The PROSPECT dataset is a collection of 61 million PSMs generated from synthetic peptides. To avoid overrepresentation of some peptides in this dataset, we randomly selected at most 100 PSMs per unique peptide, similar to the processing that was done during the creation of the MassIVE-KB dataset. This pre-selection step reduced the size of the PROSPECT dataset to 12.6 million PSMs. Finally, to create a non-enzymatic dataset containing 1 million peptides, we selected 50,000 PSMs for each canonical amino acid. These PSMs were selected at random from MassIVE-KB, then supplemented as necessary from PROSPECT to obtain the desired count (see Yilmaz et al. [Yilmaz2023] Supplementary Table S1). This dataset contained PSMs from 247,859 unique peptides, which were randomly split into training, validation and test sets in the ratio 80/10/10. FTP directory contains the mgf files corresponding to train, validation and test splits. [Wang2018] M. Wang, J. Wang, J. Carver, B. Pullman, S. Won Cha, N. Bandeira, "Assembling the Community-Scale Discoverable Human Proteome", Cell Systems, Volume 7, Issue 4, 2018. [Shouman2022] O. Shouman, W. Gabriel, V. Giurcoiu, V. Sternlicht, M. Wilhelm, "PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics", NeurIPS Datasets and Benchmarks, 2022 [Yilmaz2023] M. Yilmaz*, W. Fondrie*, W. Bittremieux, R. Nelson, V. Ananth, S. Oh, and W. Noble,"Sequence-to-sequence translation from mass spectra to peptides with a transformer model", bioRxiv, 2023

Dataset Information

Fine-Tuning of Alkaline Residues on the Hydrophilic Face Provides a Non-toxic Cationic α-Helical Antimicrobial Peptide Against Antibiotic-Resistant ESKAPE Pathogens.

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