In order to meet the challenges posed by a pathways-based approach to risk assessment, an in-depth understanding of certain biological processes is required at a molecular level.  The molecular initiating event (MIE), which we define as the initial interaction between a molecule and a biomolecule or biosystem that can be linked to an outcome via a pathway, is a key anchor to advancing our understanding of which pathways are perturbed by exposure to a chemical.   By considering the MIE as two molecules interacting at an atomic level to cause an effect, we can use fundamental chemistry to predict whether an interaction is likely through in silico methods and in chemico assays.  Alternatively, we can identify the MIE by investigating the biological response of a chemical in panels of in vitro assays and work down the levels of biological organization to predict the original MIE.  Both of these approaches form the basis of our research activities in this area. Coverage of a broad chemical and biological space by any kind of pathways identification tool is essential to not only enable identification of activation of toxicologically relevant pathways for more detailed characterisation, but also to give confidence in absence of any off-target effects.  The selection of appropriate assays to provide this coverage is a key focus area. Developing alerts linking chemical structure to biological response at the sub-cellular level is a complex task that requires diverse experimental inputs and informatics data mining. However, the advantage of predicting effects at sub-cellular and cellular level is that you are not extrapolating knowledge through higher levels of biological organization to what would be considered a traditional apical endpoint; hence biological complexity is reduced and predictions more robust.  We currently have a research programme with Professor Jonathan Goodman at the University of Cambridge investigating the development of such predictions. Predicting the ability of a novel chemical to bind to a broad panel of receptors in silico is computationally challenging and the majority of existing available tools are only suited to efficacy screening of single receptors against multiple ligands.  In an attempt to address this gap we co-sponsored (with Dow Agrochemicals) an NC3Rs CRACK-IT challenge to academia and small to medium enterprises to develop a tool to ‘target off-targets’.  We also have a project with the Research Centre for Eco Environmental Sciences (RCEES, Beijing) to use high performance computing clusters to develop molecular dynamic receptor models; importantly these will be validated by quality experimental data generated at RCEES and from other research including collaborations with the United States Environmental Protection Agency (EPA) and Prof. Sergey Piletsky (University of Leicester). Through the development and integration of biology and chemistry-based technologies, prediction of MIE interactions and their associated pathways is made possible by the inherent structure that pathways based approaches present.  For Unilever this also provides an opportunity to apply MIE level knowledge further than humans and attempting to translate it into the various environmental species that we seek to protect. Latest presentation MIES and mitochondrial toxicity – the applied view Latest publication Allen TE, Goodman J, Gutsell S, Russell PJ (2014) Defining molecular initiating events in the adverse outcome pathway framework for risk assessment,Chemical Research in Toxicology, 27(12), 2100-12

Dr. Paul Russell