In vitro platform for identification and MOA determination of anti-biofilm agents (CMPG)
Our in vitro screening platform has currently been optimized for nine
different bacterial species, relevant for environmental, medical and industrial
contaminations, and includes Staphylococcus
aureus, Pseudomonas aeruginosa, Escherichia coli and Salmonella enterica. In addition to single-species biofilms, also
multi-species biofilms are being studied.
Anti-biofilm agents (CMPG)
In this project we aim to identify novel, innovative and broad applicable anti-biofilm compounds, active in many different growth conditions. Additionally all compounds are selected to only influence the biofilm, without affecting the planktonic (free-living) mode of growth of the bacteria. In this way the micro-organisms experience a reduced selective pressure which can prevent, or at least slow down, the development of resistance to the compounds. As such, the compounds identified in this project will have a broad applicability and have potential to be used as a prophylactic for longer time periods. Currently five different compound families have been identified with potent, specific anti-biofilm activity. For all identified compounds molecular pathways involved in their mode of action have been determined.
An overview of the
bioinformatics software previously developed by prof. K. Marchal can be found
Relevant bio- and
chemoinformatics software under development at DTAI can be found at:
NSPDK is a graph kernel with state-of-the-art generalization performance on a wide range of bio- and chemoinformatics tasks. The kernel is based on exact matching between pairs of small ball-shaped subgraphs. The use of fast graph invariant procedures allows a speed-up of several orders of magnitude for Gram matrix computations when compared with kernels based on soft matching or more complex subgraph definition.
DMax Chemistry Assistant is a data mining tool for QSAR, compound screening data analysis, and virtual screening.