Improvement of antibacterial therapeutic proteins using AI
Lead Participant:
EVOLVERE BIOSCIENCES LTD
Abstract
Common injuries and illnesses that were once easily treatable are becoming more dangerous and killing once again. This is because of drug-resistant infections which are undermining modern medicine. In 2019, 1.2 million people died directly as a result of drug-resistant infections. Furthermore, current small-molecule antibiotics lead to acute and chronic side effects as a result of toxicity to human cells and disruptions to the gut microbiome.
Evolvere BioSciences aims to redesign antibacterial medicines for the 21st century. The core technology that we have engineered to achieve this aim is a platform that rapidly generates antibacterial medicines engineered to minimise the emergence of resistance, have minimal short-term and long-term side effects and have low-dose pharmacokinetics. This platform is built on technology that enables the identification of conserved, accessible, and expressed epitopes on the bacterial outer surface. We use a combination of wet lab evolution techniques and deep learning bioinformatics to identify proteins that bind to these motifs and predict how the bacteria may evolve resistance which would allow us to engineer proteins that limit the likelihood of bacterial escape. We then create bifunctional proteins that target and kill bacteria. Our platform technology can produce novel antibacterials against any target bacteria. Our proteins target various components of the bacterial outer surface, such as the cell wall, lipids, and outer membrane proteins. We anticipate our antibacterials to have fewer side effects by being specific only to bacterial components on the group of target bacteria. In a further enhancement of our platform, we incorporate deep learning and generative AI to design proteins that are increasingly humanised to further reduce side effects and have increased solubility to enable rapid lower-cost protein production. Additionally, we would like to employ our epitope identification technology in a separate development pipeline to develop bacterial vaccines or, in combination with generative AI, antibodies. Through targeted bacteria selection and improved standard of care, we can not only pick the most commercially tractable clinical indications for our lead pipelines but also build a multi-asset company for long-term commercial success. This means we believe our solution may solve both the scientific and economic hurdles in the antibiotic space.
Evolvere BioSciences aims to redesign antibacterial medicines for the 21st century. The core technology that we have engineered to achieve this aim is a platform that rapidly generates antibacterial medicines engineered to minimise the emergence of resistance, have minimal short-term and long-term side effects and have low-dose pharmacokinetics. This platform is built on technology that enables the identification of conserved, accessible, and expressed epitopes on the bacterial outer surface. We use a combination of wet lab evolution techniques and deep learning bioinformatics to identify proteins that bind to these motifs and predict how the bacteria may evolve resistance which would allow us to engineer proteins that limit the likelihood of bacterial escape. We then create bifunctional proteins that target and kill bacteria. Our platform technology can produce novel antibacterials against any target bacteria. Our proteins target various components of the bacterial outer surface, such as the cell wall, lipids, and outer membrane proteins. We anticipate our antibacterials to have fewer side effects by being specific only to bacterial components on the group of target bacteria. In a further enhancement of our platform, we incorporate deep learning and generative AI to design proteins that are increasingly humanised to further reduce side effects and have increased solubility to enable rapid lower-cost protein production. Additionally, we would like to employ our epitope identification technology in a separate development pipeline to develop bacterial vaccines or, in combination with generative AI, antibodies. Through targeted bacteria selection and improved standard of care, we can not only pick the most commercially tractable clinical indications for our lead pipelines but also build a multi-asset company for long-term commercial success. This means we believe our solution may solve both the scientific and economic hurdles in the antibiotic space.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| EVOLVERE BIOSCIENCES LTD | £50,000 | £ 50,000 |
People |
ORCID iD |