Combining Topology and Sequence Design for the Discovery of Potent Antimicrobial Peptide Dendrimers against Multidrug-ResistantPseudomonas aeruginosa

Peptide Dendrimer-Based Antibacterial Agents: Synthesis and Applications

Pathogenic bacteria cause the deaths of millions of people every year. With the development of antibiotics, hundreds and thousands of people's lives have been saved. Nevertheless, bacteria can develop resistance to antibiotics, rendering them insensitive to antibiotics over time. Peptides containing specific amino acids can be used as antibacterial agents; however, they can be easily degraded by proteases in vivo. To address these issues, branched peptide dendrimers are now being considered as good antibacterial agents due to their high efficacy, resistance to protease degradation, and low cytotoxicity. The ease with which peptide dendrimers can be synthesized and modified makes them accessible for use in various biological and nonbiological fields. That is, peptide dendrimers hold a promising future as antibacterial agents with prolonged efficacy without bacterial resistance development. Their in vivo stability and multivalence allow them to effectively target multi-drug-resistant strains and prevent biofilm formation. Thus, it is interesting to have an overview of the development and applications of peptide dendrimers in antibacterial research, including the possibility of employing machine learning approaches for the design of AMPs and dendrimers. This review summarizes the synthesis and applications of peptide dendrimers as antibacterial agents. The challenges and perspectives of using peptide dendrimers as the antibacterial agents are also discussed.

Antimicrobial Peptide-Peptoid Hybrids with and without Membrane Disruption

Among synthetic analogues of antimicrobial peptides (AMPs) under investigation to address antimicrobial resistance, peptoids (N-alkylated oligoglycines) have been reported to act both by membrane disruption and on intracellular targets. Here we gradually introduced peptoid units into the membrane-disruptive undecapeptide KKLLKLLKLLL to test a possible transition toward intracellular targeting. We found that selected hybrids containing up to five peptoid units retained the parent AMP's α-helical folding, membrane disruption, and antimicrobial effects against Gram-negative bacteria including multidrug-resistant (MDR) strains of Pseudomonas aeruginosa and Klebsiella pneumoniae while showing reduced hemolysis and cell toxicities. Furthermore, some hybrids containing as few as three peptoid units as well as the full peptoid lost folding, membrane disruption, hemolysis, and cytotoxicity but displayed strong antibacterial activity under dilute medium conditions typical for proline-rich antimicrobial peptides (PrAMPs), pointing to intracellular targeting. These findings parallel previous reports that partially helical amphiphilic peptoids are privileged oligomers for antibiotic development.

Comparative Study of the U(VI) Adsorption by Hybrid Silica-Hyperbranched Poly(ethylene imine) Nanoparticles and Xerogels

Two different silica conformations (xerogels and nanoparticles), both formed by the mediation of dendritic poly (ethylene imine), were tested at low pHs for problematic uranyl cation sorption. The effect of crucial factors, i.e., temperature, electrostatic forces, adsorbent composition, accessibility of the pollutant to the dendritic cavities, and MW of the organic matrix, was investigated to determine the optimum formulation for water purification under these conditions. This was attained with the aid of UV-visible and FTIR spectroscopy, dynamic light scattering (DLS), ζ-potential, liquid nitrogen (LN₂) porosimetry, thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). Results highlighted that both adsorbents have extraordinary sorption capacities. Xerogels are cost-effective since they approximate the performance of nanoparticles with much less organic content. Both adsorbents could be used in the form of dispersions. The xerogels, though, are more practicable materials since they may penetrate the pores of a metal or ceramic solid substrate in the form of a precursor gel-forming solution, producing composite purification devices.

Dendritic Polymers in Tissue Engineering: Contributions of PAMAM, PPI PEG and PEI to Injury Restoration and Bioactive Scaffold Evolution

The capability of radially polymerized bio-dendrimers and hyperbranched polymers for medical applications is well established. Perhaps the most important implementations are those that involve interactions with the regenerative mechanisms of cells. In general, they are non-toxic or exhibit very low toxicity. Thus, they allow unhindered and, in many cases, faster cell proliferation, a property that renders them ideal materials for tissue engineering scaffolds. Their resemblance to proteins permits the synthesis of derivatives that mimic collagen and elastin or are capable of biomimetic hydroxy apatite production. Due to their distinctive architecture (core, internal branches, terminal groups), dendritic polymers may play many roles. The internal cavities may host cell differentiation genes and antimicrobial protection drugs. Suitable terminal groups may modify the surface chemistry of cells and modulate the external membrane charge promoting cell adhesion and tissue assembly. They may also induce polymer cross-linking for healing implementation in the eyes, skin, and internal organ wounds. The review highlights all the different categories of hard and soft tissues that may be remediated with their contribution. The reader will also be exposed to the incorporation of methods for establishment of biomaterials, functionalization strategies, and the synthetic paths for organizing assemblies from biocompatible building blocks and natural metabolites.

Machine Learning Guided Discovery of Non-Hemolytic Membrane Disruptive Anticancer Peptides

Most antimicrobial peptides (AMPs) and anticancer peptides (ACPs) fold into membrane disruptive cationic amphiphilic α-helices, many of which are however also unpredictably hemolytic and toxic. Here we exploited the ability of recurrent neural networks (RNN) to distinguish active from inactive and non-hemolytic from hemolytic AMPs and ACPs to discover new non-hemolytic ACPs. Our discovery pipeline involved: 1) sequence generation using either a generative RNN or a genetic algorithm, 2) RNN classification for activity and hemolysis, 3) selection for sequence novelty, helicity and amphiphilicity, and 4) synthesis and testing. Experimental evaluation of thirty-three peptides resulted in eleven active ACPs, four of which were non-hemolytic, with properties resembling those of the natural ACP lasioglossin III. These experiments show the first example of direct machine learning guided discovery of non-hemolytic ACPs.

Optimizing Antimicrobial Peptide Dendrimers in Chemical Space

We used nearest-neighbor searches in chemical space to improve the activity of the antimicrobial peptide dendrimer (AMPD) G3KL and identified dendrimer T7, which has an expanded activity range against Gram-negative pathogenic bacteria including Klebsiellae pneumoniae, increased serum stability, and promising activity in an in vivo infection model against a multidrug-resistant strain of Acinetobacter baumannii. Imaging, spectroscopic studies, and a structural model from molecular dynamics simulations suggest that T7 acts through membrane disruption. These experiments provide the first example of using virtual screening in the field of dendrimers and show that dendrimer size does not limit the activity of AMPDs.

Synthesis of Mannosylated Glycodendrimers and Evaluation against BC2L-A Lectin from Burkholderia Cenocepacia

Chronic colonization of lungs by opportunist bacteria is the major cause of mortality for cystic fibrosis patients. Among these pathogens, Burkholderia cenocepacia is responsible for cepacia syndrome, a deadly exacerbation of infection that is the main cause of poor outcomes of lung transplantation. This bacterium contains three soluble carbohydrate-binding proteins, including the B. cenocepacia lectin A (BC2L-A), which is proposed to bind to oligomannose-type N-glycan structures to adhere to host tissues. In this work, several mannosylated glycoclusters and glycodendrimers with valencies ranging from four to 24 were prepared and their interactions with BC2L-A were thermodynamically characterized by isothermal titration calorimetry. The results show that a 24-valent structure binds to BC2L-A at nanomolar concentration, which makes this compound the highest affinity monodisperse ligand for this lectin.