Bisphenol A binding promiscuity: A virtual journey through the universe of proteins.

Elena Lo Piparo

doi:10.14573/altex.1906141

Abstract

Significant efforts are currently being made to move toxicity testing from animal experimentation to human relevant, mechanism-based approaches. In this context, the identification of molecular target(s) responsible for mechanisms of action is an essential step. Inspired by the recent concept of polypharmacology (the ability of drugs to interact with multiple targets) we argue that whole proteome virtual screening might become a breakthrough tool in toxicology reflecting the real complexity of chemical-biological interactions. Therefore, we investigated the value of performing ligand-protein binding prediction screening across the full proteome to identify new mechanisms of action for food chemicals. We applied the new approach to make a broader comparison between bisphenol A (BPA) (food-packaging chemical) and the endogenous estrogen, 17β-estradiol (EST). Applying a novel high-throughput ligand-protein binding prediction tool (BioGPS) by the Amazon Web Services (AWS) cloud (to speed-up the calculation), we investigated the value of performing in silico screening across the full proteome (all human and rodent x-ray protein structures available in the Protein Data Bank). The strong correlation between in silico predictions and available in vitro data demonstrates the high predictive power of the method used. The most striking results obtained was that BPA was predicted to bind to many more proteins than the ones already known, most of which were common to EST. Our findings provide a new and unprecedented insight on the complexity of chemical-protein interactions, highlighting the binding promiscuity of BPA and its broader similarity compared to the female sex hormone, EST.

Highlights

Our study exploits recent discoveries in supercomputer-based drug design to support the new paradigm under development in the field of toxicology
As reported for drugs, for which polypharmacology, i.e., the ability of drugs to interact with multiple targets, seems to be more a rule than an exception (Ellingson et al, 2014), xenobiotics may interact with multiple targets, potentially triggering several molecular initiating events (MIEs) that lead to adverse outcomes
We first assessed the known interaction between bisphenol A (BPA) or EST and the estrogen receptor α (ERα)

Summary

Introduction

Our study exploits recent discoveries in supercomputer-based drug design to support the new paradigm under development in the field of toxicology. Exploring alternative approaches to animal experimentation is inducing a revolution, moving from black box high-dose animal studies towards more mechanistic, human-relevant approaches. This is illustrated by the concept of adverse outcome pathways (AOPs), consisting of a framework linking molecular initiating events (MIEs) (based on chemical-target interactions) to a sequence of molecular, cellular, anatomical and functional events, leading to an adverse effect (Burden et al, 2015). It is thought that AOPs will transform risk assessment of chemicals, placing more emphasis on the integration of mechanistic information. As reported for drugs, for which polypharmacology, i.e., the ability of drugs to interact with multiple targets, seems to be more a rule than an exception (Ellingson et al, 2014), xenobiotics may interact with multiple targets, potentially triggering several MIEs that lead to adverse outcomes

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