Rational design, structural characterisation, and functional evaluation of antimicrobial peptides from Rana palustris

Abstract

Antimicrobial resistance continues to rise, so new antibacterial agents with improved selectivity and novel mechanisms are needed. This project investigates skin antimicrobial peptides (AMPs) from the frog, Rana palustris, across three families: Temporin, Ranatuerin-2, and Palustrin-1, using an integrated workflow of discovery/confirmation, rational design, structural characterisation, and functional validation.

A new temporin member, Temporin-1PLb, was cloned and identified, and analogue libraries were generated through targeted substitutions, D-residue incorporation, truncation and motif grafting. Ranatuerin-2PLb and Palustrin-1c were further used as tunable scaffolds by editing cation density, hydrophobicity, chirality and the rana-box region. All peptides were verified by MS and RP-HPLC, and CD was used to track conformational changes in water and membrane-mimicking conditions.

Activities and mechanisms were assessed using MIC/MBC, MBIC/MBEC, time-kill kinetics, salt/serum interference, haemolysis and therapeutic index, plus membrane depolarisation, permeability staining and SYTO9/PI imaging. Overall, the peptides mainly showed envelope-linked behaviour, but stronger early membrane readouts did not always translate into faster CFU clearance, suggesting distinct lethal membrane behaviours among analogues. Under physiologically-relevant interference, Ca²⁺ and serum proteins were major constraints on activity.

At the lead level, D-R7/11 improved the potency–safety balance in the temporin set; R15K provided a more balanced profile on the ranatuerin scaffold while K-D R3A represented a safety-first direction; and P9K showed the most stable low MIC/MBC against Gram-negative bacteria and only slight, delayed MIC drift during serial passaging, indicating a milder short-term tolerance induction trend.

Thesis is embargoed until 31 July 2031.

Date of Award	Jul 2026
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Tianbao Chen (Supervisor), Mei Zhou (Supervisor) & Lei Wang (Supervisor)