AbstractsBiology & Animal Science

The chemical and computational biology of inflammation

by Benjamin Gavin Small

Institution: University of Manchester
Year: 2012
Keywords: Chemical Biology; Evolutionary Optimisation; Systems Pharmacology; Network Map
Record ID: 1396311
Full text PDF: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:153797


Non-communicable diseases (NCD) such as cancer, heart disease and cerebrovascularinjury are dependent on or aggravated by inflammation. Their prevention and treatment isarguably one of the greatest challenges to medicine in the 21st century. The pleiotropic,proinflammatory cytokine; interleukin-1 beta (IL-1b) is a primary, causative messenger ofinflammation. Lipopolysaccharide (LPS) induction of IL-1b expression via toll-likereceptor 4 (TLR4) in myeloid cells is a robust experimental model of inflammation and isdriven in large part via p38-MAPK and NF-kB signaling networks. The control ofsignaling networks involved in IL-1b expression is distributed and highly complex, so toperturb intracellular networks effectively it is often necessary to modulate several stepssimultaneously. However, the number of possible permutations for intervention leads to acombinatorial explosion in the experiments that would have to be performed in a completeanalysis. We used a multi-objective evolutionary algorithm (EA) to optimise reagentcombinations from a dynamic chemical library of 33 compounds with established orpredicted targets in the regulatory network controlling IL-1β expression. The EAconverged on excellent solutions within 11 generations during which we studied just 550combinations out of the potential search space of ~ 9 billion. The top five reagents with thegreatest contribution to combinatorial effects throughout the EA were then optimised pairwisewith respect to their concentrations, using an adaptive, dose matrix search protocol.A p38a MAPK inhibitor (30 ± 10% inhibition alone) with either an inhibitor of IkB kinase(12 ± 9 % inhibition alone) or a chelator of poorly liganded iron (19 ± 8 % inhibitionalone) yielded synergistic inhibition (59 ± 5 % and 59 ± 4 % respectively, n=7, p≤0.04 forboth combinations, tested by one way ANOVA with Tukey’s multiple test correction) ofmacrophage IL-1b expression.Utilising the above data, in conjunction with the literature, an LPS-directed transcriptionalmap of IL-1b expression was constructed. Transcription factors (TF) targeted by thesignaling networks coalesce at precise nucleotide binding elements within the IL-1bregulatory DNA. Constitutive binding of PU.1 and C/EBP-b TF’s are obligate for IL-1bexpression. The findings in this thesis suggest that PU.1 and C/EBP-b TF’s form scaffoldsfacilitating dynamic control exerted by other TF’s, as exemplified by c-Jun. Similarly,evidence is emerging that epigenetic factors, such as the hetero-euchromatin balance, arealso important in the relative transcriptional efficacy in different cell types.Evolutionary searches provide a powerful and general approach to the discovery of novelcombinations of pharmacological agents with potentially greater therapeutic indices thanthose of single drugs. Similarly, construction of signaling network maps aid theelucidation of pharmacological mechanism and are mandatory precursors to thedevelopment of dynamic models. The symbiosis of both approaches has provided furtherinsight into the mechanisms responsible…