(2bb) Synthesis, Characterization, and Analysis of Non-Linear Polymers for Medicine

Current Research

Antimicrobial resistance has become an increasing threat to both health and the economy, and the development of new antimicrobial agents is slowing. Cationic antimicrobial peptides (AMPs) are promising antibiotics, since they often disrupt anionic bacterial membranes irreversibly, they invoke less and slower resistance compared to conventional antibiotics. Yet, rapid clearance from kidney due to the small size of peptide, degradation by proteases, and toxicity to mammalian cells hinder their clinical application. Multiple delivery vehicles, including nanoparticles, liposomes, and polymers, have been investigated to overcome the aforementioned challenges and improve the biocompatibility of peptides without compromising significant efficacy.

Among the above strategies, conjugation of antimicrobial peptide to polymer scaffolds provides ample opportunities to modulate solution behavior (e.g., secondary structure, size, zeta potential, and morphology) and adjust their performance (e.g., bactericidal activity, proteolytic stability, and cytotoxicity). Advances in polymer chemistry allow the preparation of polymeric materials with an expansive range of compositions, molecular weights, and architectures to unlock the structure-property-performance relationships. As the simplest configuration, AMPs can be conjugated to the end of a long neutral hydrophilic poly(ethylene glycol) (PEG), resulting linear conjugates. The long polymer chain often wraps the peptide and results in lower toxicity and higher stability, but lower activity compared to the free peptide. To improve the biocompatibility without significantly compromising activity, non-linear architectures (e.g., star-shaped, comb-like, and hyperbranched) that enable attachment of multiple AMPs to one molecule have been studied. However, conjugates with cationic polymer cores still experience the trade-off between activity and toxicity, which limits their utility. Designing conjugates of AMPs and biocompatible neutral hydrophilic polymers (e.g., PEG) in non-linear architectures may hinder toxic interaction with mammalian cells and augment stability, while still maintaining the activity by presenting AMPs with high density. It is also possible that the hydrophobicity difference between PEG and AMPs may cause phase separation to form supramolecular structures with different morphologies, and that these may impact performance. Therein, it is also essential to understand the solution behavior of AMP-PEG with non-linear architectures to probe how AMPs are presented on the conjugates and by extension the changes in properties and performance.

We have prepared linear and star-shaped AMP-PEG conjugates with various arm numbers and arm lengths and found the conjugates with the highest peptide density to yield similar activity compared to the free peptide. Moreover, while unconjugated peptide fully degraded in 1 h upon treatment of enzyme, that conjugate retained 80% peptide content under the same conditions. In the future, we aim to copolymerize peptide monomers with PEG-based monomers to prepare comb-like conjugates with controlled peptide density, molecular weight, and monomer distribution. We plan to correlate their solution behavior (e.g., secondary structure, size, zeta potential, and morphology) to performance to learn how peptide presentation on conjugates with different architectures impacts antimicrobial performance and guide the future design. We are also interested in comparing star-shaped conjugates to comb-like conjugates with similar composition and molecular weight to systematically study the architectural effects on both properties and performance. We anticipate that the findings and methods used in this work can be extended to the design of more AMP-polymer conjugates in treating infectious diseases.

Future research interests

Building on my current research experience with synthesis and characterization of peptide and polymers as well as my master’s thesis work on microfluidic devices, I am interested in learning how to systematically design, synthesize, and characterize polymers with high throughput to build up database for non-linear polymers for drug delivery. In particular, I am looking forward to exploring the following possible directions:

1. Adapting microfluidic devices/microreactors to synthesize and characterize polymers with high throughput.

• Inspired by recent work on using robust setups with high throughput to prepare block copolymers, I am interested in adapting microfluidic devices to synthesize polymers with different architectures and/or compositions as vehicles to deliver therapeutic peptides. Combining with high throughput characterization of polymers will provide efficient workflow in lab and synthesis with high throughput for making comparisons among a large data set of polymer structure-property-performance relationships.

2. Using data science tools to correlate properties and performance of polymers in drug delivery.

• With my current experience on connecting properties to performance of antimicrobial polymers, I am interested in exploring how to build structure-property-performance relationships with machine learning tools. In particular, the performance-determining properties of polymers for drug delivery can be interrelated to balance the trade-off between efficacy and biocompatibility. Thus, learning how to use experimental data to build a model to pre-screen molecular designs will provide opportunities to predict the performance from their structures, and thereby accelerate development and implementation of critically needed new therapeutics.