Cel
While conventionally effects of a chemical structure on a biological system have been determined for individual compounds, one at a time, it is now becoming apparent that biological effects of compound combination are not additive, but often conditional (antagonistic or synergistic) in nature. This phenomenon is of relevance both in the medicinal context (where drugs can be combined to have a synergistic effect), as well as the area of toxicology (where the simultaneous application of compounds shows a toxicity that is non-additive). However, it is not yet clear how to model, and anticipate, which compound combinations show this type of effect.
Hence, in this work I will derive models of synergistic compound combinations, which will be prospectively validated in experiments. Furthermore, I will describe how to capture the effect of a chemical structure on a biological system on multiple levels, namely by considering structural features of the compound, its bioactivity profile, and pathway annotations and their relationship to the phenotypic effect observed. By integrating the data generated in a biologically meaningful way, this allows us to generate predictive models for the bioactivity of compound combinations. The relevance of this work ranges from the question which drugs can be combined in a synergistic manner and which combinations should rather be avoided to the safety assessment of chemicals. Hence, with this work I will be able to improve upon the current state-of-the-art in bioactivity data integration and modelling approaches, as well as deliver concrete models for the bioactivity assessment of compound combinations.
Dziedzina nauki
Zaproszenie do składania wniosków
ERC-2013-StG
Zobacz inne projekty w ramach tego zaproszenia
System finansowania
ERC-SG - ERC Starting GrantInstytucja przyjmująca
CB2 1TN Cambridge
Zjednoczone Królestwo