Antimicrobial peptides (AMPs) are ubiquitous amongst living organisms and are part of the innate immune system with the ability to kill pathogens directly or indirectly by modulating the immune system. AMPs have potential as a novel therapeutic against bacteria due to their quick-acting mechanism of action that prevents bacteria from developing resistance. Additionally, there is a dire need for therapeutics with activity specifically against gram-negative bacterial infections that are dangerous and difficult to treat. Development of new antibiotics has slowed in recent years and novel therapeutics like AMPs with a focus against gram-negative bacteria are needed. We designed 8 novel AMPs, termed PHNX peptides, using ab initio computational design (database filtering technology on APD3 dataset of natural AMPs against gram negative bacteria as described by Wang et al.) and assessed their theoretical function using published machine learning algorithms as well as measured their activity in our laboratory. These AMPs were tested and demonstrated greater activity against gramnegative MDR Escherichia coli than MRSA (Methicillin Resistant Staphylococcus aureus) bacteria and showed low hemolytic activity against human red-blood cells.