Validating a Predictive Structure-Property Relationship by Discovery of Novel Polymers which Reduce Bacterial Biofilm Formation.
Adam A DundasOlutoba SanniJean-Frédéric DubernGeorgios DimitrakisAndrew L HookDerek J IrvinePaul WilliamsMorgan R AlexanderPublished in: Advanced materials (Deerfield Beach, Fla.) (2019)
Synthetic materials are an everyday component of modern healthcare yet often fail routinely as a consequence of medical-device-centered infections. The incidence rate for catheter-associated urinary tract infections is between 3% and 7% for each day of use, which means that infection is inevitable when resident for sufficient time. The O'Neill Review on antimicrobial resistance estimates that, left unchecked, ten million people will die annually from drug-resistant infections by 2050. Development of biomaterials resistant to bacterial colonization can play an important role in reducing device-associated infections. However, rational design of new biomaterials is hindered by the lack of quantitative structure-activity relationships (QSARs). Here, the development of a predictive QSAR is reported for bacterial biofilm formation on a range of polymers, using calculated molecular descriptors of monomer units to discover and exemplify novel, biofilm-resistant (meth-)acrylate-based polymers. These predictions are validated successfully by the synthesis of new monomers which are polymerized to create coatings found to be resistant to biofilm formation by six different bacterial pathogens: Pseudomonas aeruginosa, Proteus mirabilis, Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus.
Keyphrases
- biofilm formation
- pseudomonas aeruginosa
- escherichia coli
- staphylococcus aureus
- drug resistant
- antimicrobial resistance
- klebsiella pneumoniae
- multidrug resistant
- acinetobacter baumannii
- candida albicans
- healthcare
- cystic fibrosis
- urinary tract infection
- gram negative
- risk factors
- molecular docking
- high resolution
- patient safety
- molecular dynamics
- high throughput
- single molecule
- health information
- tandem mass spectrometry
- tissue engineering
- single cell