Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools

Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble to act as alternatives to antibiotics that are either no longer effective or used as drugs of last resort. Machine learning tools allow the straightforward in silico identification of non-hemolytic antimicrobial peptides. Here, we utilized a number of these tools to rank the best peptides from two libraries: 1) 8192 peptides with sequence bhxxbhbGAL, where b is the basic amino acid R or K, h is a hydrophobic amino acid, i.e. G, A, L, F, I, V, Y, or W and x is Q, S, A, or V; and 2) 512 peptides with sequence RWhxbhRGWL, where b and h are as for the first library and x is Q, S, A, or G. The top 100 sequences from each library, as well as 10 peptides predicted to be active but hemolytic (for a total of 220 peptides), were SPOT synthesized and their IC