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Theoretical simulations and site-directed mutagenesis experiments examine the binding site of ochratoxin A (OTA) within domain of 2A of human serum albumin. R257 plays an important role in the binding of the isocoumarin ring of OTA by serving as a proton acceptor and stabilizing the binding through the creation of an ion pair with the phenoxide group on OTA.

Isothermal calorimetry (ITC) is used to study the binding of ochratoxin (OTA) and its O-methyl derivative (MOA). The calculations of the equilibrium geometry of the monoanion and dianion of OTA reveal only small structural changes among the lowest energy conformers.

Computational molecular models of chemicals interacting with biomolecular targets provides toxicologists a valuable, affordable, and sustainable source of in silico molecular level information that augments, enriches, and complements in vitro and in vivo efforts. From a molecular biophysical ansatz, we describe how 3D molecular modeling methods used to numerically evaluate the classical pair-wise potential at the chemical/biological interface can inform mechanism of action and the dose-response paradigm of modern toxicology. With an emphasis on molecular docking, 3D-QSAR and pharmacophore/toxicophore approaches, we demonstrate how these methods can be integrated with chemoinformatic and toxicogenomic efforts into a tiered computational toxicology workflow. We describe generalized protocols in which 3D computational molecular modeling is used to enhance our ability to predict and model the most relevant toxicokinetic, metabolic, and molecular toxicological endpoints, thereby accelerating the computational toxicology-driven basis of modern risk assessment while providing a starting point for rational sustainable molecular design.

This chapter provides an overview of computational models that describe various aspects of the source-to-health effect continuum. Fate and transport models describe the release, transportation, and transformation of chemicals from sources of emission throughout the general environment. Exposure models integrate the microenvironmental concentrations with the amount of time an individual spends in these microenvironments to estimate the intensity, frequency, and duration of contact with environmental chemicals. Physiologically based pharmacokinetic (PBPK) models incorporate mechanistic biological information to predict chemical-specific absorption, distribution, metabolism, and excretion. Values of parameters in PBPK models can be measured in vitro, in vivo, or estimated using computational molecular modeling. Computational modeling is also used to predict the respiratory tract dosimetry of inhaled gases and particulates [computational fluid dynamics (CFD) models], to describe the normal and xenobiotic-perturbed behaviors of signaling pathways, and to analyze the growth kinetics of preneoplastic lesions and predict tumor incidence (clonal growth models).