AMPs, also known as host defense peptides, are a class of evolutionary conserved molecules that form an important component in the innate immune system . These molecules are usually made of 12 to 50 amino acid residues, and they typically possess certain properties, including cationicity, 30-50% hydropho-bicity, and amphiphilicity. They exhibit good antimicrobial activity against a broad range of bacteria, viruses, fungi, and parasites. In addition, they have an inherent low risk of developing antimicrobial resistance (AMR), largely attributed to their underlying rapid membrane permeabilising activity . Such broad-spectrum and rapid antimicrobial activity has prompted researchers to consider AMPs as a potential remedy to the growing problem of AMR, which is a major global health threat . Nonetheless, there has so far been a lack of success in translating AMP-based therapy to clinical use, due to challenges such as complex structure-activity relationship (SAR), drug toxicity, instability in host and infective environment, and low financial incentives . Owing to the complex SAR and the costly and timeconsuming process of wet-lab experiments associated with AMP investigations, many researchers have proposed computational approaches, including molecular dynamics (MD) simulations and machine learning (ML) algorithms, to accelerate the discovery and development of potential AMPs for clinical use .