Abstract
Biofilms represent a multicellular growth state of bacteria that are intrinsically resistant to conventional antibiotics. It was recently shown that a synthetic immunomodulatory cationic peptide, 1018 (VRLIVAVRIWRR-NH2), exhibits broad-spectrum antibiofilm activity but the sequence determinants of antibiofilm peptides have not been systematically studied. In the present work, a peptide library consisting of 96 single amino acid substituted variants of 1018 was SPOT-synthesized on cellulose arrays and evaluated against methicillin resistant Staphylococcus aureus (MRSA) biofilms. This dataset was used to establish quantitative structure-activity relationship (QSAR) models relating the antibiofilm activity of these peptides to hundreds of molecular descriptors derived from their sequences. The developed 3D QSAR models then predicted the probability that a peptide would possess antibiofilm activity from a library of 100,000 virtual peptide sequences in silico. A subset of these variants were SPOT-synthesized and their activity assessed, revealing that the QSAR models resulted in ~85% prediction accuracy. Notably, peptide 3002 (ILVRWIRWRIQW-NH2) was identified that exhibited an 8-fold increased antibiofilm potency in vitro compared to 1018 and proved effective in vivo, significantly reducing abscess size in a chronic MRSA mouse infection model. This study demonstrates that QSAR modeling can successfully be used to identify antibiofilm specific peptides with therapeutic potential.
Highlights
Our group recently identified short cationic peptides with antibiofilm activity[5,6,7,8] that share many structural features with well-characterized antimicrobial peptides such as significant positive charge, large proportion of hydrophobic residues and amphipathicity[9,10]
We previously showed that the quantitative structure-activity relationship (QSAR) modeling of antimicrobial peptides relating structure to activity was quite accurate in classifying peptides with antibacterial activity towards planktonic cells[11]
A 96 peptide, SPOT-synthesized, single amino-acid substitution library of 1018 (Supplementary Table S1) was tested for activity against methicillin resistant Staphylococcus aureus (MRSA) biofilms revealing a distribution of antibiofilm activities ranging from slightly more active than the parent peptide, 25% vs. 31% residual biofilm, to completely inactive (Fig. 1a)
Summary
Our group recently identified short cationic peptides with antibiofilm activity[5,6,7,8] that share many structural features with well-characterized antimicrobial peptides such as significant positive charge, large proportion of hydrophobic residues and amphipathicity[9,10]. Previous publications have employed various sequence optimization strategies aimed at enhancing the overall potency of antimicrobial peptides[11,12] Most of these studies focused on small libraries of peptides in which modifications were made to remove residues that detracted from antibacterial activity (e.g. acidic and polar amino acids in the hydrophobic face) while maintaining basic and hydrophobic residues (especially Trp), known to contribute to overall potency. A molecular descriptor can be defined as the transformation of the chemical information within a given molecule (in this case a polypeptide sequence) into a set of numerical values based on the physico-chemical properties of the constituent amino acids and their relative positioning, which can be used to model the activities of interest[16] In this sense, the modeled structures take into account the exact composition of all atoms of the peptide in three-dimensional space.
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