Designing Endocrine Disruption Out of the Next Generation of Chemicals.

A central goal of green chemistry is to avoid hazard in the design of new chemicals. This objective is best achieved when information about a chemical's potential hazardous effects is obtained as early in the design process as feasible. Endocrine disruption is a type of hazard that to date has been inadequately addressed by both industrial and regulatory science. To aid chemists in avoiding this hazard, we propose an endocrine disruption testing protocol for use by chemists in the design of new chemicals. The Tiered Protocol for Endocrine Disruption (TiPED) has been created under the oversight of a scientific advisory committee composed of leading representatives from both green chemistry and the environmental health sciences. TiPED is conceived as a tool for new chemical design, thus it starts with a chemist theoretically at "the drawing board." It consists of five testing tiers ranging from broad in silico evaluation up through specific cell- and whole organism-based assays. To be effective at detecting endocrine disruption, a testing protocol must be able to measure potential hormone-like or hormone-inhibiting effects of chemicals, as well as the many possible interactions and signaling sequellae such chemicals may have with cell-based receptors. Accordingly, we have designed this protocol to broadly interrogate the endocrine system. The proposed protocol will not detect all possible mechanisms of endocrine disruption, because scientific understanding of these phenomena is advancing rapidly. To ensure that the protocol remains current, we have established a plan for incorporating new assays into the protocol as the science advances. In this paper we present the principles that should guide the science of testing new chemicals for endocrine disruption, as well as principles by which to evaluate individual assays for applicability, and laboratories for reliability. In a 'proof-of-principle' test, we ran 6 endocrine disrupting chemicals (EDCs) that act via different endocrinological mechanisms through the protocol using published literature. Each was identified as endocrine active by one or more tiers. We believe that this voluntary testing protocol will be a dynamic tool to facilitate efficient and early identification of potentially problematic chemicals, while ultimately reducing the risks to public health.

Spatial chemical distance based on atomic property fields.

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein-ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening.

Stabilization of G-quadruplex DNA with platinum(II) Schiff base complexes: luminescent probe and down-regulation of c-myc oncogene expression.

The interactions of a series of platinum(II) Schiff base complexes with c-myc G-quadruplex DNA were studied. Complex [PtL(1a)] (1 a; H(2)L(1a)=N,N'-bis(salicylidene)-4,5-methoxy-1,2-phenylenediamine) can moderately inhibit c-myc gene promoter activity in a cell-free system through stabilizing the G-quadruplex structure and can inhibit c-myc oncogene expression in cultured cells. The interaction between 1 a and G-quadruplex DNA has been examined by (1)H NMR spectroscopy. By using computer-aided structure-based drug design for hit-to-lead optimization, an in silico G-quadruplex DNA model has been constructed for docking-based virtual screening to develop new platinum(II) Schiff base complexes with improved inhibitory activities. Complex [PtL(3)] (3; H(2)L(3)=N,N'-bis{4-[1-(2-propylpiperidine)oxy]salicylidene}-4,5-methoxy-1,2-phenylenediamine) has been identified with a top score in the virtual screening. This complex was subsequently prepared and experimentally tested in vitro for its ability to stabilize or induce the formation of the c-myc G-quadruplex. The inhibitory activity of 3 (IC(50)=4.4 muM) is tenfold more than that of 1 a. The interaction between 1 a or 3 with c-myc G-quadruplex DNA has been examined by absorption titration, emission titration, molecular modeling, and NMR titration experiments, thus revealing that both 1 a and 3 bind c-myc G-quadruplex DNA through an external end-stacking mode at the 3' terminal face of the G-quadruplex. Such binding of G-quadruplex DNA with 3 is accompanied by up to an eightfold increase in the intensity of photoluminescence at lambda(max)=652 nm. Complex 3 also effectively down-regulated the expression of c-myc in human hepatocarcinoma cells.

Discovery of antiandrogen activity of nonsteroidal scaffolds of marketed drugs.

Finding good drug leads de novo from large chemical libraries, real or virtual, is not an easy task. High-throughput screening is often plagued by low hit rates and many leads that are toxic or exhibit poor bioavailability. Exploiting the secondary activity of marketed drugs, on the other hand, may help in generating drug leads that can be optimized for the observed side-effect target, while maintaining acceptable bioavailability and toxicity profiles. Here, we describe an efficient computational methodology to discover leads to a protein target from safe marketed drugs. We applied an in silico "drug repurposing" procedure for identification of nonsteroidal antagonists against the human androgen receptor (AR), using multiple predicted models of an antagonist-bound receptor. The library of marketed oral drugs was then docked into the best-performing models, and the 11 selected compounds with the highest docking score were tested in vitro for AR binding and antagonism of dihydrotestosterone-induced AR transactivation. The phenothiazine derivatives acetophenazine, fluphenazine, and periciazine, used clinically as antipsychotic drugs, were identified as weak AR antagonists. This in vitro biological activity correlated well with endocrine side effects observed in individuals taking these medications. Further computational optimization of phenothiazines, combined with in vitro screening, led to the identification of a nonsteroidal antiandrogen with improved AR antagonism and marked reduction in affinity for dopaminergic and serotonergic receptors that are the primary target of phenothiazine antipsychotics.

Large-scale prediction of protein geometry and stability changes for arbitrary single point mutations.

We have developed a method to both predict the geometry and the relative stability of point mutants that may be used for arbitrary mutations. The geometry optimization procedure was first tested on a new benchmark of 2141 ordered pairs of X-ray crystal structures of proteins that differ by a single point mutation, the largest data set to date. An empirical energy function, which includes terms representing the energy contributions of the folded and denatured proteins and uses the predicted mutant side chain conformation, was fit to a training set consisting of half of a diverse set of 1816 experimental stability values for single point mutations in 81 different proteins. The data included a substantial number of small to large residue mutations not considered by previous prediction studies. After removing 22 (approximately 2%) outliers, the stability calculation gave a standard deviation of 1.08 kcal/mol with a correlation coefficient of 0.82. The prediction method was then tested on the remaining half of the experimental data, giving a standard deviation of 1.10 kcal/mol and covariance of 0.66 for 97% of the test set. A regression fit of the energy function to a subset of 137 mutants, for which both native and mutant structures were available, gave a prediction error comparable to that for the complete training set with predicted side chain conformations. We found that about half of the variation is due to conformation-independent residue contributions. Finally, a fit to the experimental stability data using these residue parameters exclusively suggests guidelines for improving protein stability in the absence of detailed structure information.

Rapid boundary element solvation electrostatics calculations in folding simulations: successful folding of a 23-residue peptide.

Solvation effects play a profound role in the energetics of protein folding. While a continuum dielectric model of solvation may provide a sufficiently accurate estimate of the solvation effects, until now this model was too computationally expensive and unstable for folding simulations. Here we proposed a fast yet accurate and robust implementation of the boundary element solution of the Poisson equation, the REBEL algorithm. Using our earlier double-energy scheme, we included for the first time the mathematically rigorous continuous REBEL solvation term in our Biased Probability Monte Carlo (BPMC) simulations of the peptide folding. The free energy of a 23-residue beta beta alpha-peptide was then globally optimized with and without the solvation electrostatics contribution. An ensemble of beta beta alpha conformations was found at and near the global minimum of the energy function with the REBEL electrostatic solvation term. Much poorer correspondence to the native solution structure was found in the "control" simulations with a traditional method to account for solvation via a distance-dependent dielectric constant. Each simulation took less than 40 h (21 h without electrostatic solvation calculation) on a single Alpha 677 MHz CPU and involved more than 40,000 solvation energy evaluations. This work demonstrates for the first time that such a simulation can be performed in a realistic time frame. The proposed procedure may eliminate the energy evaluation accuracy bottleneck in folding simulations.

High-throughput docking for lead generation.

Recent improvements in flexible docking technology may lead to a bigger role for computational methods in lead discovery. Although fast and accurate computational prediction of binding affinities for an arbitrary molecule is still beyond the limits of current methods, the docking and screening procedures can select small sets of likely lead candidates from large libraries of either commercially or synthetically available compounds.

In silico discovery of novel retinoic acid receptor agonist structures.

BACKGROUND: Several Retinoic Acid Receptors (RAR) agonists have therapeutic activity against a variety of cancer types; however, unacceptable toxicity profiles have hindered the development of drugs. RAR agonists presenting novel structural and chemical features could therefore open new avenues for the discovery of leads against breast, lung and prostate cancer or leukemia. RESULTS: We have analysed the induced fit of the active site residues upon binding of a known ligand. The derived binding site models were used to dock over 150,000 molecules in silico (or virtually) to the structure of the receptor with the Internal Coordinates Mechanics (ICM) program. Thirty ligand candidates were tested in vitro. CONCLUSIONS: Two novel agonists resulting from the predicted receptor model were active at 50 nM. One of them displays novel structural features which may translate into the development of new ligands for cancer therapy.

Modeling, mutagenesis, and structural studies on the fully conserved phosphate-binding loop (loop 8) of triosephosphate isomerase: toward a new substrate specificity.

Loop 8 (residues 232-242) in triosephosphate isomerase (TIM) is a highly conserved loop that forms a tight binding pocket for the phosphate moiety of the substrate. Its sequence includes the fully conserved, solvent-exposed Leu238. The tight phosphate-binding pocket explains the high substrate specificity of TIM being limited to the in vivo substrates dihydroxyacetone-phosphate and D-glyceraldehyde-3-phosphate. Here we use the monomeric variant of trypanosomal TIM for exploring the structural consequences of shortening this loop. The mutagenesis, guided by extensive modeling calculations and followed up by crystallographic characterization, is aimed at widening the phosphate-binding pocket and, consequently, changing the substrate specificity. Two new variants were characterized. The crystal structures of these variants indicate that in monomeric forms of TIM, the Leu238 side-chain is nicely buried in a hydrophobic cluster. Monomeric forms of wild-type dimeric TIM are known to exist transiently as folding intermediates; our structural analysis suggests that in this monomeric form, Leu238 of loop 8 also adopts this completely buried conformation, which explains its full conservation across the evolution. The much wider phosphate-binding pocket of the new variant allows for the development of a new TIM variant with a different substrate specificity.

Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR.

Binding of the Tat protein to TAR RNA is necessary for viral replication of HIV-1. We screened the Available Chemicals Directory (ACD) to identify ligands to bind to a TAR RNA structure using a four-step docking procedure: rigid docking first, followed by three steps of flexible docking using a pseudobrownian Monte Carlo minimization in torsion angle space with progressively more detailed conformational sampling on a progressively smaller list of top-ranking compounds. To validate the procedure, we successfully docked ligands for five RNA complexes of known structure. For ranking ligands according to binding avidity, an empirical binding free energy function was developed which accounts, in particular, for solvation, isomerization free energy, and changes in conformational entropy. System-specific parameters for the function were derived on a training set of RNA/ligand complexes with known structure and affinity. To validate the free energy function, we screened the entire ACD for ligands for an RNA aptamer which binds L-arginine tightly. The native ligand ranked 17 out of ca. 153,000 compounds screened, i.e., the procedure is able to filter out >99.98% of the database and still retain the native ligand. Screening of the ACD for TAR ligands yielded a high rank for all known TAR ligands contained in the ACD and suggested several other potential TAR ligands. Eight of the highest ranking compounds not previously known to be ligands were assayed for inhibition of the Tat-TAR interaction, and two exhibited a CD50 of ca. 1 microM.

Antibodies against thrombospondin-related anonymous protein do not inhibit Plasmodium sporozoite infectivity in vivo.

Thrombospondin-related anonymous protein (TRAP), a candidate malaria vaccine antigen, is required for Plasmodium sporozoite gliding motility and cell invasion. For the first time, the ability of antibodies against TRAP to inhibit sporozoite infectivity in vivo is evaluated in detail. TRAP contains an A-domain, a well-characterized adhesive motif found in integrins. We modeled here a three-dimensional structure of the TRAP A-domain of Plasmodium yoelii and located regions surrounding the MIDAS (metal ion-dependent adhesion site), the presumed business end of the domain. Mice were immunized with constructs containing these A-domain regions but were not protected from sporozoite challenge. Furthermore, monoclonal and rabbit polyclonal antibodies against the A-domain, the conserved N terminus, and the repeat region of TRAP had no effect on the gliding motility or sporozoite infectivity to mice. TRAP is located in micronemes, secretory organelles of apicomplexan parasites. Accordingly, the antibodies tested here stained cytoplasmic TRAP brightly by immunofluorescence. However, very little TRAP could be detected on the surface of sporozoites. In contrast, a dramatic relocalization of TRAP onto the parasite surface occurred when sporozoites were treated with calcium ionophore. This likely mimics the release of TRAP from micronemes when a sporozoite contacts its target cell in vivo. Contact with hepatoma cells in culture also appeared to induce the release of TRAP onto the surface of sporozoites. If large amounts of TRAP are released in close proximity to its cellular receptor(s), effective competitive inhibition by antibodies may be difficult to achieve.

Aminoglycoside binding in the major groove of duplex RNA: the thermodynamic and electrostatic forces that govern recognition.

We use a combination of spectroscopic, calorimetric, viscometric and computer modeling techniques to characterize the binding of the aminoglycoside antibiotic, tobramycin, to the polymeric RNA duplex, poly(rI).poly(rC), which exhibits the characteristic A-type conformation that is conserved among natural and synthetic double-helical RNA sequences. Our results reveal the following significant features: (i) CD-detected binding of tobramycin to poly(rI).poly(rC) reveals an apparent site size of four base-pairs per bound drug molecule; (ii) tobramycin binding enhances the thermal stability of the host poly(rI).poly(rC) duplex, the extent of which decreases upon increasing in Na(+) concentration and/or pH conditions; (iii) the enthalpy of tobramycin- poly(rI).poly(rC) complexation increases with increasing pH conditions, an observation consistent with binding-induced protonation of one or more drug amino groups; (iv) the affinity of tobramycin for poly(rI).poly(rC) is sensitive to both pH and Na(+) concentration, with increases in pH and/or Na(+) concentration resulting in a concomitant reduction in binding affinity. The salt dependence of the tobramycin binding affinity reveals that the drug binds to the host RNA duplex as trication. (v) The thermodynamic driving force for tobramycin- poly(rI).poly(rC) complexation depends on pH conditions. Specifically, at pH< or =6.0, tobramycin binding is entropy driven, but is enthalpy driven at pH > 6.0. (vi) Viscometric data reveal non-intercalative binding properties when tobramycin complexes with poly(rI).poly(rC), consistent with a major groove-directed mode of binding. These data also are consistent with a binding-induced reduction in the apparent molecular length of the host RNA duplex. (vii) Computer modeling studies reveal a tobramycin-poly(rI). poly(rC) complex in which the drug fits snugly at the base of the RNA major groove and is stabilized, at least in part, by an array of hydrogen bonding interactions with both base and backbone atoms of the host RNA. These studies also demonstrate an inability of tobramycin to form a stable low-energy complex with the minor groove of the poly(rI).poly(rC) duplex. In the aggregate, our results suggest that tobramycin-RNA recognition is dictated and controlled by a broad range of factors that include electrostatic interactions, hydrogen bonding interactions, drug protonation reactions, and binding-induced alterations in the structure of the host RNA. These modulatory effects on tobramycin-RNA complexation are discussed in terms of their potential importance for the selective recognition of specific RNA structural motifs, such as asymmetric internal loops or hairpin loop-stem junctions, by aminoglycoside antibiotics and their derivatives.

Genetic linkage mapping of zebrafish genes and ESTs.

Genetic screens in zebrafish (Danio rerio) have isolated mutations in hundreds of genes essential for vertebrate development, physiology, and behavior. We have constructed a genetic linkage map that will facilitate the identification of candidate genes for these mutations and allow comparisons among the genomes of zebrafish and other vertebrates. On this map, we have localized 771 zebrafish genes and expressed sequence tags (ESTs) by scoring single-stranded conformational polymorphisms (SSCPs) in a meiotic mapping panel. Of these sequences, 642 represent previously unmapped genes and ESTs. The mapping panel was comprised of 42 homozygous diploid individuals produced by heat shock treatment of haploid embryos at the one-cell stage (HS diploids). This "doubled haploid" strategy combines the advantages of mapping in haploid and standard diploid systems, because heat shock diploid individuals have only one allele at each locus and can survive to adulthood, enabling a relatively large quantity of genomic DNA to be prepared from each individual in the mapping panel. To integrate this map with others, we also scored 593 previously mapped simple-sequence length polymorphisms (SSLPs) in the mapping panel. This map will accelerate the molecular analysis of zebrafish mutations and facilitate comparative analysis of vertebrate genomes.

Rational discovery of novel nuclear hormone receptor antagonists.

Nuclear hormone receptors (NRs) are potential targets for therapeutic approaches to many clinical conditions, including cancer, diabetes, and neurological diseases. The crystal structure of the ligand binding domain of agonist-bound NRs enables the design of compounds with agonist activity. However, with the exception of the human estrogen receptor-alpha, the lack of antagonist-bound "inactive" receptor structures hinders the rational design of receptor antagonists. In this study, we present a strategy for designing such antagonists. We constructed a model of the inactive conformation of human retinoic acid receptor-alpha by using information derived from antagonist-bound estrogen receptor-alpha and applied a computer-based virtual screening algorithm to identify retinoic acid receptor antagonists. Thus, the currently available crystal structures of NRs may be used for the rational design of antagonists, which could lead to the development of novel drugs for a variety of diseases.

Expression of the adenovirus receptor and its interaction with the fiber knob.

The coxsackievirus group B (CVB) and adenovirus (Ad) receptor (HCVADR, formerly HCAR) is a cell surface protein with two immunoglobulin-like regions (IG1 and IG2) that serves as a receptor for two structurally unrelated viruses. We have established the tissue distribution of the receptor in the rodent by immunohistochemistry and show that the receptor is broadly expressed during embryonic development in the central and peripheral nervous systems and in several types of epithelial cells. The tissue distribution is more restricted in the adult but remains high mainly in epithelial cells. Using site-directed mutagenesis, based on computer modeling of the IG1 region, Ad5 binding could be inhibited but CVB attachment was unaffected. A double amino acid substitution in a three-stranded anti-parallel beta sheet that may form a face of the receptor completely inhibited Ad5 binding. Therefore, we conclude that the molecular interactions critical for Ad5 binding to HCVADR do not overlap with those of CVB3. In fact a specific antibody interfering with only CVB binding recognizes the IG2 domain in the receptor, suggesting that the CVB interacts with this region or an overlap between the IG1 and the IG2 regions.

Estimating local backbone structural deviation in homology models.

After the atomic coordinates themselves, the most important data in a homology model are the spatial reliability estimates associated with each of the atoms (atom annotation). Recent blind homology modeling predictions have demonstrated that principally correct sequence-structure alignments are achievable to sequence identities as low as 25% [Martin, A.C., MacArthur, M.W., Thornton, J.M., 1997. Assessment of comparative modeling in CASP2. Proteins Suppl(1), 14-28]. The locations and extent of spatial deviations in the backbone between correctly aligned homologous protein structures remained very poorly estimated however, and these errors were the cause of errant loop predictions [Abagyan, R., Batalov, S., Cardozo, T., Totrov, M., Webber, J., Zhou, Y., 1997. Homology modeling with internal coordinate mechanics: deformation zone mapping and improvements of models via conformational search. Proteins Suppl(1), 29-37]. In order to derive accurate measures for local backbone deviations, we made a systematic study of static local backbone deviations between homologous pairs of protein structures. We found that 'through space' proximity to gaps and chain termini, local three-dimensional 'density', three-dimensional environment conservation, and B-factor of the template contribute to local deviations in the backbone in addition to local sequence identity. Based on these finding, we have identified the meaningful ranges of values within which each of these parameters correlates with static local backbone deviation and produced a combined scoring function to greatly improve the estimation of local backbone deviations. The optimized function has more than twice the accuracy of local sequence identity or B-factor alone and was validated in a recent blind structure prediction experiment. This method may be used to evaluate the utility of a preliminary homology model for a particular biological investigation (e.g. drug design) or to provide an improved starting point for molecular mechanics loop prediction methods.

NRIF3 is a novel coactivator mediating functional specificity of nuclear hormone receptors.

Many nuclear receptors are capable of recognizing similar DNA elements. The molecular event(s) underlying the functional specificities of these receptors (in regulating the expression of their native target genes) is a very important issue that remains poorly understood. Here we report the cloning and analysis of a novel nuclear receptor coactivator (designated NRIF3) that exhibits a distinct receptor specificity. Fluorescence microscopy shows that NRIF3 localizes to the cell nucleus. The yeast two-hybrid and/or in vitro binding assays indicated that NRIF3 specifically interacts with the thyroid hormone receptor (TR) and retinoid X receptor (RXR) in a ligand-dependent fashion but does not bind to the retinoic acid receptor, vitamin D receptor, progesterone receptor, glucocorticoid receptor, or estrogen receptor. Functional experiments showed that NRIF3 significantly potentiates TR- and RXR-mediated transactivation in vivo but has little effect on other examined nuclear receptors. Domain and mutagenesis analyses indicated that a novel C-terminal domain in NRIF3 plays an essential role in its specific interaction with liganded TR and RXR while the N-terminal LXXLL motif plays a minor role in allowing optimum interaction. Computer modeling and subsequent experimental analysis suggested that the C-terminal domain of NRIF3 directly mediates interaction with liganded receptors through an LXXIL (a variant of the canonical LXXLL) module while the other part of the NRIF3 protein may still play a role in conferring its receptor specificity. Identification of a coactivator with such a unique receptor specificity may provide new insight into the molecular mechanism(s) of receptor-mediated transcriptional activation as well as the functional specificities of nuclear receptors.

Prediction of the binding energy for small molecules, peptides and proteins.

A fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. Knowledge-based scoring schemes may not be sufficiently general and transferable, while molecular dynamics or Monte Carlo calculations with explicit solvent are too computationally expensive for many applications. Recently, several empirical schemes using finite difference Poisson-Boltzmann electrostatics to predict energies for particular types of complexes were proposed. Here, an improved empirical binding energy function has been derived and validated on three different types of complexes: protein-small ligand, protein-peptide and protein-protein. The function uses the boundary element algorithm to evaluate the electrostatic solvation energy. We show that a single set of parameters can predict the relative binding energies of the heterogeneous validation set of complexes with 2.5 kcal/mol accuracy. We also demonstrate that global optimization of the ligand and of the flexible side-chains of the receptor improves the accuracy of the evaluation.