James R. Rabinowitz

Molecular Modeling for Screening Environmental Chemicals for Estrogenicity: Use of the Toxicant-Target Approach

There is a paucity of relevant experimental information available for the evaluation of the potential health and environmental effects of many man made chemicals. Knowledge of the potential pathways for activity provides a rational basis for the extrapolations inherent in the preliminary evaluation of risk and the establishment of priorities for obtaining missing data for environmental chemicals. The differential step in many mechanisms of toxicity may be generalized as the interaction between a small molecule (a potential toxicant) and one or more macromolecular targets. An approach based on computation of the interaction between a potential molecular toxicant and a library of macromolecular targets of toxicity has been proposed for preliminary chemical screening. In the current study, the interaction between a series of environmentally relevant chemicals and models of the rat estrogen receptors (ER) was computed and the results compared to an experimental data set of their relative binding affinities. The experimental data set consists of 281 chemicals, selected from the U.S. EPAs Toxic Substances Control Act (TSCA) inventory, that were initially screened using the rat uterine cytosolic ER-competitive binding assay. Secondary analysis, using Lineweaver-Burk plots and slope replots, was applied to confirm that only 15 of these test chemicals were true competitive inhibitors of ER binding with experimental inhibition constants (K(i)) less than 100 microM. Two different rapid computational docking methods have been applied. Each provides a score that is a surrogate for the strength of the interaction between each ligand-receptor pair. Using the score that indicates the strongest interaction for each pair, without consideration of the geometry of binding between the toxicant and the target, all of the active molecules were discovered in the first 16% of the chemicals. When a filter is applied on the basis of the geometry of a simplified pharmacophore for binding to the ER, the results are improved, and all of the active molecules were discovered in the first 8% of the chemicals. In order to obtain no false negatives in the model that includes the pharmacophore filter, only 8 molecules are false positives. These results indicate that molecular docking algorithms that were designed to find the chemicals that act most strongly at a receptor (and therefore are potential pharmaceuticals) can efficiently separate weakly active chemicals from a library of primarily inactive chemicals. The advantage of using a pharmacophore filter suggests that the development of filters of this type for other receptors will prove valuable.

A Comparison of Calculated and Experimental Geometries for Crowded polycyclic Aromatic Hydrocarbons and their Metabolites

Abstract It has become useful to consider the subclass of PAHs with a crowded bay region because of similar biological activity within the subclass. Crowding in the bay region of a polycyclic aromatic hydrocarbon results in a twisted molecular geometry. The purpose of this study is to help gauge the utility of various computational methods for determining the molecular geometry of molecules in this subclass and their metabolites. The results from semi-empirical methods AM1 and PM3, ab initio Hartree-Fock methods and density functional methods will be compared to experimentally determined geometries for crowded PAHs. It will be seen that excellent geometries for all local minimum energy structures are obtained from semi-empirical methods. More exact and computationally extensive methods yield equivalent or somewhat better results only with good basis sets. However, methods disagree on the relative energies of the isomers of diol-epoxides.

The effect of electric field induced perturbation of the distribution of ions near the cell surface on migration of charged membrane components

Abstract It has been demonstrated that an externally applied electric field perturbs the distribution of some of the macromolecules in biological membranes. Various electrostatic, hydrodynamic and structural forces resulting from the external field influence the movement of intramembraneous particles. This study investigates one of those forces, that due to the polarization of the ion distribution near the cell surface. A model is proposed based on a continuous charge distribution and the electric field due to the polarization of the ion distribution is calculated at any point on the cell surface. Shortly after an external field (E0) is applied, parallel to the surface on which the cell is fixed, the field due to the ion distribution is −AE0 sin ′, at a point (a, θ′, φ′) where qaE0 ⪡ kT, a is the radius of the cell and q is the charge of an ion near the surface. From this model we found that for a 0·15 molar monovalent salt solution, A varies from 0·16 to 1·80 as the surface potential of the cell varies between 10 and 80 mV. For larger fields, qaE0 ≤ kT the angular dependence is more complicated but the general conclusions are still valid. Results for other salt solutions and slightly different models are also given. The advantage of using discrete charges and the difficulties of incorporating them into the model are discussed. It is concluded that the force due to ion distribution polarization will have a significant effect on the movement of charged membrane components and it offers a possible explanation for the movement of charged intramembraneous molecules in a direction not expected when considering only the external field.

The Effect of Crowding in the Bay/Fjord Region on the Structure and Reactivities of Polycyclic Aromatic Hydrocarbons and their Metabolites: Quantum Mechanical Studies

Abstract Polycyclic aromatic hydrocarbons with a crowded bay region, like benzo[c]phenanthrene, are nonplanar molecules with two helical structures. The bay region diol-epoxides of these PAHs retain the helical structure and therefore have twice as many possible conformations as the diol-epoxides of planar PAHs. Using quantum mechanical methods, it is shown that the conformation where the epoxide oxygen is near the distal ring is more stable than the conformation where it is away. The most stable syn- and anti- diastereomers for the diol-epoxides of five PAHs are computed. Computation of the electrostatic interaction between the epoxide group and the distal ring suggests that it provides the additional stabilization. Comparison is made between planar and nonplanar PAHs and between molecules where the crowding is due to a ring CH or a methyl group. These results suggest that the molecular electrostatic potential in the bay region can effect molecular reactivity.

DockScreen: A Database of In Silico Biomolecular Interactions to Support Computational Toxicology

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by molecular docking of more than 1000 chemicals into 150 protein targets and contains nearly 135 thousand unique ligand/target binding scores. Obtaining this dataset was achieved using eHiTS (Simbiosys Inc.), a fragment-based molecular docking approach with an exhaustive search algorithm, on a heterogeneous distributed high-performance computing framework. The chemical landscape covered in DockScreen comprises selected environmental and therapeutic chemicals. The target landscape covered in DockScreen was selected based on the availability of high-quality crystal structures that covered the assay space of phase I ToxCast in vitro assays. This in silico data provides continuous information that establishes a means for quantitatively comparing, on a structural biophysical basis, a chemical’s profile of biomolecular interactions. The combined minimum-score chemical/target matrix is provided.

Interactions between chlorinated dioxins and a positively charged molecular probe: New molecular interaction potential

Interaction with the ligand binding domain of receptors for natural chemicals present one potential mechanism for the biological effects of environmental chemicals. Evidence suggests that the electrostatic interaction between the ligand and the receptor is an important component for binding to some of the relevant receptors. The presence of charged residues near the binding site suggests that the charge distribution of the free ligand may be different from the charge distribution of the ligand as it approaches the binding domain of the protein. In this study a new type of potential is computed for a series of dibenzo‐p‐dioxin (dioxin) ligands. This quantum mechanically computed potential results from interaction between the ligand and a trimethyl ammonium probe at a set of grid points. This interaction potential is compared with the molecular electrostatic potential computed from the wave function of the isolated ligands. Three types of local minima are found: (1) above the oxygen; (2) above the conjugated ring; and (3) above the chlorine(s). The molecular electrostatic potential emphasizes the minima associated with the chlorine atoms and, in that potential, the minima associated with the oxygen atoms disappear with chlorination. In the new potential, the minima over the oxygen atoms are maintained even in tetrachlorodioxin. As chlorination is increased the differences between the two potentials increases. The new potential shows the influence of the π‐cation interaction, which is largest when there is little substitution on the ring. The presence of the probe induces a dipole component of 1 debye perpendicular to the plane of the ligand. Local minima in the interaction potential are then used as starting structures for the determination of the most stable ligand–probe complexes. The most stable structures are obtained from the minima associated with the oxygen atoms. These structures are stabilized by a hydrogen bond formation between the probe and the oxygen and the molecule is bent by 30° about the O(SINGLE BOND)O axis. For this series of molecules, the new potential retains some of the features that determine the hydrogen bond whereas the molecular electrostatic potential does not. © 1998 John Wiley & Sons, Inc. J Comput Chem 19: 673–684, 1998

Rapid experimental measurements of physicochemical properties to inform models and testing

The structures and physicochemical properties of chemicals are important for determining their potential toxicological effects, toxicokinetics, and route(s) of exposure. These data are needed to prioritize the risk for thousands of environmental chemicals, but experimental values are often lacking. In an attempt to efficiently fill data gaps in physicochemical property information, we generated new data for 200 structurally diverse compounds, which were rigorously selected from the USEPA ToxCast chemical library, and whose structures are available within the Distributed Structure-Searchable Toxicity Database (DSSTox). This pilot study evaluated rapid experimental methods to determine five physicochemical properties, including the log of the octanol:water partition coefficient (known as log(Kow) or logP), vapor pressure, water solubility, Henrys law constant, and the acid dissociation constant (pKa). For most compounds, experiments were successful for at least one property; log(Kow) yielded the largest return (176 values). It was determined that 77 ToxPrint structural features were enriched in chemicals with at least one measurement failure, indicating which features may have played a role in rapid method failures. To gauge consistency with traditional measurement methods, the new measurements were compared with previous measurements (where available). Since quantitative structure-activity/property relationship (QSAR/QSPR) models are used to fill gaps in physicochemical property information, 5 suites of QSPRs were evaluated for their predictive ability and chemical coverage or applicability domain of new experimental measurements. The ability to have accurate measurements of these properties will facilitate better exposure predictions in two ways: 1) direct input of these experimental measurements into exposure models; and 2) construction of QSPRs with a wider applicability domain, as their predicted physicochemical values can be used to parameterize exposure models in the absence of experimental data.