Large scale ab initio modeling of structurally uncharacterized antimicrobial peptides reveals known and novel folds

DRESIS: the first comprehensive landscape of drug resistance information

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named 'DRESIS' was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/.

Computational Methods and Tools in Antimicrobial Peptide Research

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.

Investigation of the structure-activity relationship in ponericin L1 from Neoponera goeldii

Naturally derived antimicrobial peptides have been an area of great interest because of high selectivity against bacterial targets over host cells and the limited development of bacterial resistance to these molecules throughout evolution. There are also a significant number of venom-derived peptides that exhibit antimicrobial activity in addition to activity against mammals or other organisms. Many venom peptides share the same net cationic, amphiphilic nature as host-defense peptides, making them an attractive target for development as potential antibacterial agents. The peptide ponericin L1 derived from Neoponera goeldii was used as a model to investigate the role of cationic residues and net charge on peptide activity. Using a combination of spectroscopic and microbiological approaches, the role of cationic residues and net charge on antibacterial activity, lipid bilayer interactions, and bilayer and membrane permeabilization were investigated. The L1 peptide and derivatives all showed enhanced binding to lipid vesicles containing anionic lipids, but still bound to zwitterionic vesicles. None of the derivatives were especially effective at permeabilizing lipid bilayers in model vesicles, in-tact Escherichia coli, or human red blood cells. Taken together the results indicate that the lack of facial amphiphilicity regarding charge segregation may impact the ability of the L1 peptides to effectively permeabilize bilayers despite effective binding. Additionally, increasing the net charge of the peptide by replacing the lone anionic residue with either Gln or Lys dramatically improved efficacy against several bacterial strains without increasing hemolytic activity.

Effect of helical kink in antimicrobial peptides on membrane pore formation

Every cell is protected by a semipermeable membrane. Peptides with the right properties, for example Antimicrobial peptides (AMPs), can disrupt this protective barrier by formation of leaky pores. Unfortunately, matching peptide properties with their ability to selectively form pores in bacterial membranes remains elusive. In particular, the proline/glycine kink in helical peptides was reported to both increase and decrease antimicrobial activity. We used computer simulations and fluorescence experiments to show that a kink in helices affects the formation of membrane pores by stabilizing toroidal pores but disrupting barrel-stave pores. The position of the proline/glycine kink in the sequence further controls the specific structure of toroidal pore. Moreover, we demonstrate that two helical peptides can form a kink-like connection with similar behavior as one long helical peptide with a kink. The provided molecular-level insight can be utilized for design and modification of pore-forming antibacterial peptides or toxins.

Structure and Function in Antimicrobial Piscidins: Histidine Position, Directionality of Membrane Insertion, and pH-Dependent Permeabilization

Piscidins are histidine-enriched antimicrobial peptides that interact with lipid bilayers as amphipathic α-helices. Their activity at acidic and basic pH in vivo makes them promising templates for biomedical applications. This study focuses on p1 and p3, both 22-residue-long piscidins with 68% sequence identity. They share three histidines (H3, H4, and H11), but p1, which is significantly more permeabilizing, has a fourth histidine (H17). This study investigates how variations in amphipathic character associated with histidines affect the permeabilization properties of p1 and p3. First, we show that the permeabilization ability of p3, but not p1, is strongly inhibited at pH 6.0 when the conserved histidines are partially charged and H17 is predominantly neutral. Second, our neutron diffraction measurements performed at low water content and neutral pH indicate that the average conformation of p1 is highly tilted, with its C-terminus extending into the opposite leaflet. In contrast, p3 is surface bound with its N-terminal end tilted toward the bilayer interior. The deeper membrane insertion of p1 correlates with its behavior at full hydration: an enhanced ability to tilt, bury its histidines and C-terminus, induce membrane thinning and defects, and alter membrane conductance and viscoelastic properties. Furthermore, its pH-resiliency relates to the neutral state favored by H17. Overall, these results provide mechanistic insights into how differences in the histidine content and amphipathicity of peptides can elicit different directionality of membrane insertion and pH-dependent permeabilization. This work features complementary methods, including dye leakage assays, NMR-monitored titrations, X-ray and neutron diffraction, oriented CD, molecular dynamics, electrochemical impedance spectroscopy, surface plasmon resonance, and quartz crystal microbalance with dissipation.

Computational Evolution of Threonine-Rich β-Hairpin Peptides Mimicking Specificity and Affinity of Antibodies

The development of recognition molecules with antibody-like properties is of great value to the biotechnological and bioanalytical communities. The recognition molecules presented here are peptides with a strong tendency to form β-hairpin structures, stabilized by alternate threonines, which are located at one face of the peptide. Amino acids at the other face of the peptide are available for interaction with the target molecule. Using this scaffold, we demonstrate that recognition molecules can efficiently be designed in silico toward four structurally unrelated proteins, GFP, IL-1β, IL-2, and IL-6. On solid support, 10 different antibody-mimetic recognition molecules were synthesized. They displayed high affinity and no cross-reactivity, as observed by fluorescence microscopy. Stabilized variants were readily obtained by incorporation of azido acids and propargylglycine followed by cyclization via the Cu(I)-catalyzed alkyne-azide cycloaddition reaction. As this new class of antibody mimics can be designed toward essentially any protein, the concept is believed to be useful to a wide range of technologies. Here, their use in protein separation and in the detection of proteins in a sandwich-type assay is demonstrated.