A chemo-centric view of human health and disease

Efforts to compile the phenotypic effects of drugs and environmental chemicals offer the opportunity to adopt a chemo-centric view of human health that does not require detailed mechanistic information. Here we consider thousands of chemicals and analyse the relationship of their structures with adverse and therapeutic responses. Our study includes molecules related to the aetiology of 934 health-threatening conditions and used to treat 835 diseases. We first identify chemical moieties that could be independently associated with each phenotypic effect. Using these fragments, we build accurate predictors for approximately 400 clinical phenotypes, finding many privileged and liable structures. Finally, we connect two diseases if they relate to similar chemical structures. The resulting networks of human conditions are able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning, and show a remarkable coincidence with clinical observations

Carcinogenicity prediction of noncongeneric chemicals by augmented top priority fragment classification

Carcinogenicity prediction is an important process that can be performed to cut down experimental costs and save animal lives. The current reliability of the results is however disputed. Here, a blind exercise in carcinogenicity category assessment is performed using augmented top priority fragment classification. The procedure analyses the applicability domain of the dataset, allocates in clusters the compounds using a leading molecular fragment, and a similarity measure. The exercise is applied to three compound datasets derived from the Lois Gold Carcinogenic Database. The results, showing good agreement with experimental data, are compared with published ones. A final discussion on our viewpoint on the possibilities that the carcinogenicity modelling of chemical compounds offers is presented

A History of the Molecular Initiating Event

The adverse outcome pathway (AOP) framework provides an alternative to traditional $\textit{in vivo}$ experiments for the risk assessment of chemicals. AOPs consist of a number of key events (KEs) linked by key event relationships across a range of biological organization backed by scientific evidence. The first KE in the pathway is the molecular initiating event (MIE)-the initial chemical trigger that starts an AOP. Over the past 3 years the AOP conceptual framework has gained a large amount of momentum in toxicology as an alternative to animal methods, and so the MIE has come into the spotlight. What is an MIE? How can MIEs be measured or predicted? What research is currently contributing to our understanding of MIEs? In this Perspective we outline answers to these key questions.The authors acknowledge financial support from Unilever

Determination of Toxicant Mode of Action by Augmented Top Priority Fragment Class

Theor. models can be an efficient tool to assess compd. toxicity as an alternative to exptl. detns. Their application must follow some requirements that include the possibility of understanding the rationale that supports the prediction; here, the detn. of the mode of action (MOA) is important. A combination of similarity and reactivity anal. has been applied to group chem. compds. with the aim at selecting groups that share structure and electronic state. The model is not based on exptl. data but only on structural features. The result is a no. of groups that contains similar compds. with similar reactivity and, possibly, similar MOA. The comparison of these groups to the exptl. detd. MOAs available for the EPAFHAM database permits the discussion of the validity of both the model and the exptl. data