Healthcare relies on a ready supply of antibiotics, from treating infections to making operations safer. Antibiotic resistance is a real threat, so the search is on for the next generation of drugs. Researchers at Ingenza are investigating a new antimicrobial peptide, called epidermicin, which is shown to rapidly kill the superbug MRSA. They want to develop an efficient, scalable system capable of producing hundreds of milligrams of epidermicin from one litre of bacteria, enabling optimisation of the peptide properties. Researchers have to rely on experience to propose new variants, limiting how many can be tested.
Advanced simulation techniques at the Hartree Centre have been used to help to observe how the epidermicin peptide unfolds in the membrane and find which parts of the peptide sequence are crucial for antimicrobial activity. Through in silico experiments, a range of designs can be tested, allowing accurate predictions of changes in interaction strength as well as varying the composition of model membrane to mimic different bacteria. The team have accumulated experimental and computational data for the system and can use data analytics and machine learning to analyse large sets of antimicrobial peptides, revealing common sequence motifs. These can be used to suggest changes to the epidermicin sequence likely to enhance its antimicrobial character.
Completed as part of the Innovation Return on Research (IROR) programme, our in silico modelling capabilities have enabled screening of candidate peptides prior to expensive laboratory preparation and testing. This complements Ingenza’s core expertise of high throughput production of peptides. Working collaboratively, we can significantly reduce the time and cost of bringing novel drug designs to market. With the challenge of antibiotic resistance, these savings are more important than ever.
"This collaboration has enabled us to adapt and observe the molecular modes of actions of entirely novel antimicrobial compounds at unprecedented levels of detail - enabling improved rational design and accelerated lead discovery. Ingenza’s R&D capabilities have been advanced considerably through the computational input and expertise of the STFC team."
Ian Fotheringham, Ingenza
At a glance
- Advanced simulation techniques enable researchers to understand how drugs interact at molecular level
- Data analytics and machine learning capabilities help to analyse large sets of data
- Ability to screen potential peptides prior to expensive laboratory testing
- Reducing time and cost associated with bringing new drug designs to market
- Improved design and accelerated lead discovery