Experimental verification of structural alerts for the protein binding of cyclic compounds acting as Michael acceptors

Abstract

This study outlines how a combination of and in vitro data can be used to define the applicability domain of selected structural alerts within the protein binding profilers of the Organisation for Economic Co-operation (OECD) Quantitative Structure-Activity Relationship (QSAR) Toolbox. Thirty chemicals containing a cyclic moiety were profiled for reactivity using the OECD and Optimised Approach based on Structural Indices Set (OASIS) protein binding profilers. The profiling results identified 22 of the chemicals as being reactive towards proteins. Analysis of the experimentally data showed 19 of these chemicals to be reactive. Subsequent analysis allowed refinements to be suggested to improve the applicability domain of the structural alerts investigated. The accurate definition of the applicability domain for structural alerts within in silico profilers is important due to their use in chemical category in predictive and regulatory toxicology.

Development of a Fragment-Based in Silico Profiler for Michael Addition Thiol Reactivity

“…There have been many attempts to relate predict the reactivity and toxicity of chemicals known to act via Michael addition both experimentally ( in chemico ) and computationally ( in silico ). − In chemico approaches involve either the determination of the kinetic rate constant or, more typically, spectrophotometric methods that involve determination of the concentration of the electrophile required to deplete a model nucleophile such as glutathione . In contrast, in silico methods, such as the works of Mulliner et al and Schwobel et al, use quantum mechanical methods to calculate the energy of activation for these types of electrophilic reactions, enabling the experimental rate values to be predicted using simple quantitative structure activity models. , Furthermore, such in silico methods have been applied for the prediction of toxicity data where covalent protein binding is the MIE.…”

A scheme to evaluate structural alerts to predict toxicity – Assessing confidence by characterising uncertainties

“…To be accurate, structural alerts must encode this information to avoid over-prediction. The definition of the domain of alerts is assisted by consideration of all data, for instance in chemico data have been utilised to define the domains of a number of reactive mechanisms associated with skin sensitisation ( Richarz et al, 2014 ; Rodriguez-Sanchez et al (2013) ; Nelms et al (2013) ).…”

COSMOS next generation – A public knowledge base leveraging chemical and biological data to support the regulatory assessment of chemicals

“…One of the new additions to the COSMOS NG is the ability to profile and group compounds by categories and pathways. Well-known chemical categories or mode-of-action (MoA) chemotypes are available for mutagenesis [66] , genotoxic carcinogens [67] , [68] , DNA binders [69] , [70] , [71] , protein binders [72] , [73] , [74] , [75] , [76] , [77] , [78] , [79] , liver toxicity [80] , [81] , [82] , [83] , [84] , [85] , [86] , [87] and DART structural rules [88] . If the structure matches any of the categories defined by chemotype fragment, the structure will be associated with particular categories or rules.…”