Olivier Taboureau

Adverse outcome pathways: opportunities, limitations and open questions

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field.

Association between chemical pattern in breast milk and congenital cryptorchidism: modelling of complex human exposures

During the past four decades, there has been an increase in the incidence rate of male reproductive disorders in some, but not all, Western countries. The observed increase in the prevalence of male reproductive disorders is suspected to be ascribable to environmental factors as the increase has been too rapid to be explained by genetics alone. To study the association between complex chemical exposures of humans and congenital cryptorchidism, the most common malformation of the male genitalia, we measured 121 environmental chemicals with suspected or known endocrine disrupting properties in 130 breast milk samples from Danish and Finnish mothers. Half the newborns were healthy controls, whereas the other half was boys with congenital cryptorchidism. The measured chemicals included polychlorinated biphenyls (PCBs), polybrominated diphenyl-ethers, dioxins (OCDD/PCDFs), phthalates, polybrominated biphenyls and organochlorine pesticides. Computational analysis of the data was performed using logistic regression and three multivariate machine learning classifiers. Furthermore, we performed systems biology analysis to explore the chemical influence on a molecular level. After correction for multiple testing, exposure to nine chemicals was significantly different between the cases and controls in the Danish cohort, but not in the Finnish cohort. The multivariate analysis indicated that Danish samples exhibited a stronger correlation between chemical exposure patterns in breast milk and cryptorchidism than Finnish samples. Moreover, PCBs were indicated as having a protective effect within the Danish cohort, which was supported by molecular data recovered through systems biology. Our results lend further support to the hypothesis that the mixture of environmental chemicals may contribute to observed adverse trends in male reproductive health.

Identification of LasR ligands through a virtual screening approach

With the widespread occurrence of bacterial resistance to antibiotics, the development of new strategies beyond conventional treatments is a pursuit taken by public health institutions worldwide. LasR, a transcription factor that controls quorum sensing in Pseudomonas aeruginosa, has emerged as an attractive therapeutic target for the next generation of antimicrobial agents. In the present study, a virtual screening workflow combining pharmacophore‐ and structure‐based approaches was used to identify new LasR ligands. Five novel inducers and three inhibitors of LasR activity were validated experimentally by use of a cell‐based assay. Interestingly, these compounds are molecularly distinct from the native signal molecule, N‐3‐oxododecanoyl‐L‐homoserine lactone (OHN), and may serve as lead structures for the design of new drugs. The binding modes of these compounds to the OHN binding site in LasR were predicted and used to identify the key interactions that contribute to the induction and inhibition of LasR activity.

Human Environmental Disease Network: A computational model to assess toxicology of contaminants.

During the past decades, many epidemiological, toxicological and biological studies have been performed to assess the role of environmental chemicals as potential toxicants associated with diverse human disorders. However, the relationships between diseases based on chemical exposure rarely have been studied by computational biology. We developed a human environmental disease network (EDN) to explore and suggest novel disease-disease and chemical-disease relationships. The presented scored EDN model is built upon the integration of systems biology and chemical toxicology using information on chemical contaminants and their disease relationships reported in the TDDB database. The resulting human EDN takes into consideration the level of evidence of the toxicant-disease relationships, allowing inclusion of some degrees of significance in the disease-disease associations. Such a network can be used to identify uncharacterized connections between diseases. Examples are discussed for type 2 diabetes (T2D). Additionally, this computational model allows confirmation of already known links between chemicals and diseases (e.g., between bisphenol A and behavioral disorders) and also reveals unexpected associations between chemicals and diseases (e.g., between chlordane and olfactory alteration), thus predicting which chemicals may be risk factors to human health. The proposed human EDN model allows exploration of common biological mechanisms of diseases associated with chemical exposure, helping us to gain insight into disease etiology and comorbidity. This computational approach is an alternative to animal testing supporting the 3R concept.

Network-based Approaches in Pharmacology

In drug discovery, network‐based approaches are expected to spotlight our understanding of drug action across multiple layers of information. On one hand, network pharmacology considers the drug response in the context of a cellular or phenotypic network. On the other hand, a chemical‐based network is a promising alternative for characterizing the chemical space. Both can provide complementary support for the development of rational drug design and better knowledge of the mechanisms underlying the multiple actions of drugs. Recent progress in both concepts is discussed here. In addition, a network‐based approach using drug‐target‐therapy data is introduced as an example.

Solid‐Phase Synthesis and Biological Evaluation of N‐Dipeptido L‐Homoserine Lactones as Quorum Sensing Activators

Bacteria use small signaling molecules to communicate in a process termed “quorum sensing” (QS), which enables the coordination of survival strategies, such as production of virulence factors and biofilm formation. In Gram‐negative bacteria, these signaling molecules are a series of N‐acylated L‐homoserine lactones. With the goal of identifying non‐native compounds capable of modulating bacterial QS, a virtual library of N‐dipeptido L‐homoserine lactones was screened in silico with two different crystal structures of LasR. The 30 most promising hits were synthesized on HMBA‐functionalized PEGA resin and released through an efficient acid‐mediated cyclative release mechanism. Subsequent screening for modulation of QS in Pseudomonas aeruginosa and E. coli identified six moderately strong activators. A follow‐up library designed from the preliminary derived structure–activity relationships was synthesized and evaluated for their ability to activate the QS system in this bacterium. This resulted in the identification of another six QS activators (two with low micromolar activity) thus illuminating structural features required for QS modulation.

Chemical biology databases: from aggregation, curation to representation

Systems chemical biology offers a novel way of approaching drug discovery by developing models that consider the global physiological environment of protein targets and their perturbations by drugs. However, the integration of all these data needs curation and standardization with an appropriate representation in order to get relevant interpretations. In this mini review, we present some databases and services, which integrated together with computational tools and data standardization, could assist scientists in decision making during the different drug development process.

A systems biology approach to predictive developmental neurotoxicity of a larvicide used in the prevention of Zika virus transmission

&NA; The need to prevent developmental brain disorders has led to an increased interest in efficient neurotoxicity testing. When an epidemic of microcephaly occurred in Brazil, Zika virus infection was soon identified as the likely culprit. However, the pathogenesis appeared to be complex, and a larvicide used to control mosquitoes responsible for transmission of the virus was soon suggested as an important causative factor. Yet, it is challenging to identify relevant and efficient tests that are also in line with ethical research defined by the 3Rs rule (Replacement, Reduction and Refinement). Especially in an acute situation like the microcephaly epidemic, where little toxicity documentation is available, new and innovative alternative methods, whether in vitro or in silico, must be considered. We have developed a network‐based model using an integrative systems biology approach to explore the potential developmental neurotoxicity, and we applied this method to examine the larvicide pyriproxyfen widely used in the prevention of Zika virus transmission. Our computational model covered a wide range of possible pathways providing mechanistic hypotheses between pyriproxyfen and neurological disorders via protein complexes, thus adding to the plausibility of pyriproxyfen neurotoxicity. Although providing only tentative evidence and comparisons with retinoic acid, our computational systems biology approach is rapid and inexpensive. The case study of pyriproxyfen illustrates its usefulness as an initial or screening step in the assessment of toxicity potentials of chemicals with incompletely known toxic properties. HighlightsProtein affinities were used for assessment of developmental neurotoxicity potential.An integrative systems biology approach was applied in this in silico DNT analysis.The approach was used to assess the pyriproxyfen larvicide used in mosquito control.Pyriproxyfen has neurotoxicity potentials similar to retinoic acid.In silico testing offers clear advantages in efficiency and wide pathway coverage.

Pharmacometabolomics Informs About Pharmacokinetic Profile of Methylphenidate

Carboxylesterase 1 (CES1) metabolizes methylphenidate and other drugs. CES1 gene variation only partially explains pharmacokinetic (PK) variability. Biomarkers predicting the PKs of drugs metabolized by CES1 are needed. We identified lipids in plasma from 44 healthy subjects that correlated with CES1 activity as determined by PK parameters of methylphenidate including a ceramide (q valueu2009=u20090.001) and a phosphatidylcholine (q valueu2009=u20090.005). Carriers of the CES1 143E allele had decreased methylphenidate metabolism and altered concentration of this phosphatidylcholine (q valueu2009=u20090.040) and several high polyunsaturated fatty acid lipids (PUFAs). The half‐maximal inhibitory concentration (IC50) values of chenodeoxycholate and taurocholate were 13.55 and 19.51 μM, respectively, consistent with a physiological significance. In silico analysis suggested that bile acid inhibition of CES1 involved both binding to the active and superficial sites of the enzyme. We initiated identification of metabolites predicting PKs of drugs metabolized by CES1 and suggest lipids to regulate or be regulated by this enzyme.