The protein product of the human ether-a-go-go gene (hERG) is a potassium channel that when inhibited by some drugs may lead to cardiac arrhythmia. Previously, a three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore model was constructed using Catalyst with in vitro inhibition data for antipsychotic agents. The rationale of the current study was to use a combination of in vitro and in silico technologies to further test the pharmacophore model and qualitatively predict whether molecules are likely to inhibit this potassium channel. These predictions were assessed with the experimental data using the Spearman's rho rank correlation. The antipsychotic-based hERG inhibitor model produced a statistically significant Spearman's rho of 0.71 for 11 molecules. In addition, 15 molecules from the literature were used as a further test set and were also well ranked by the same model with a statistically significant Spearman's rho value of 0.76. A Catalyst General hERG pharmacophore model was generated with these literature molecules, which contained four hydrophobic features and one positive ionizable feature. Linear regression of log-transformed observed versus predicted IC 50 values for this training set resulted in an r 2 value of 0.90. The model based on literature data was evaluated with the in vitro data generated for the original 22 molecules (including the antipsychotics) and illustrated a significant Spearman's rho of 0.77. Thus, the Catalyst 3D-QSAR approach provides useful qualitative predictions for test set molecules. The model based on literature data therefore provides a potentially valuable tool for discovery chemistry as future molecules may be synthesized that are less likely to inhibit hERG based on information provided by a pharmacophore for the inhibition of this potassium channel.

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Using in vitro data, we previously built Catalyst 3-dimensional quantitative structure activity relationship (3D-QSAR) models that qualitatively rank and predict IC 50 values for P-glycoprotein (P-gp) inhibitors. These models were derived and tested with data for inhibition of digoxin transport, calcein accumulation, vinblastine accumulation, and vinblastine binding. In the present study, 16 inhibitors of verapamil binding to P-gp were predicted using these models. These inhibition results were then used to generate a new pharmacophore that consisted of one hydrogen bond acceptor, one ring aromatic feature, and two hydrophobes. This model predicted the rank order of the four data sets described previously and correctly ranked the inhibitory potency of a further four verapamil metabolites identified in the literature. The degree of similarity in rank ordering prediction by these inhibitor pharmacophore models generated to date confirms a likely overlap in the sites to which the three P-gp substrates used in these studies (verapamil, vinblastine, and digoxin) bind. Alignment of the three substrate probes indicated that they are likely to bind the same or overlapping sites within P-gp. Important features on these substrates include multiple hydrophobic and hydrogen bond acceptor features, which are widely dispersed and in agreement among most of the five inhibitor pharmacophores we have described so far. These 3D-QSAR models will be useful for future prediction of likely substrates and inhibitors of P-gp.

P-glycoprotein (P-gp) is an efflux transporter involved in limiting the oral bioavailability and tissue penetration of a variety of structurally divergent molecules. A better understanding of the structural requirements of modulators of P-gp function will aid in the design of therapeutic agents. Toward this goal, threedimensional quantitative structure-activity relationship (3D-QSAR) models were generated using in vitro data associated with inhibition of P-gp function. Several approaches were undertaken with multiple iterations, yielding Catalyst 3D-QSAR models being able to qualitatively rank-order and predict IC 50 values for P-gp inhibitors excluded from the model in question. The success of these validations suggests that a P-gp pharmacophore for 27 inhibitors of digoxin transport in Caco-2 cells consisted of four hydrophobes and one hydrogen bond acceptor. A second pharmacophore generated with 21 inhibitors of vinblastine binding to plasma membrane vesicles derived from CEM/VLB 100 cells contained three ring aromatic features and one hydrophobic feature. A third pharmacophore generated with 17 inhibitors of vinblastine accumulation in P-gp expressing LLC-PK1 cells contained four hydrophobes and one hydrogen bond acceptor. A final pharmacophore was generated for inhibition of calcein accumulation in P-gp expressing LLC-PK1 cells and found to contain two hydrophobes, a ring aromatic feature, and a hydrogen bond donor. The similarity of features for the pharmacophores of P-gp inhibitors of digoxin transport and vinblastine binding suggest some commonality in their binding sites. Utilization of such models may prove to be of value for prediction of molecules that may modulate one or more P-gp binding sites.

Organic cation transporters play a critical role in the elimination of therapeutic compounds in the liver and the kidney. We used computational quantitative structure activity approaches to predict molecular features that influence interaction with the human ortholog of the organic cation transporter (hOCT1). [ 3 H]tetraethylammonium uptake in HeLa cells stably expressing hOCT1 was inhibited to varying extents by a diverse set of 30 molecules. A subset of 22 of these was used to produce, using Catalyst, a pharmacophore that consisted of three hydrophobic features and a positive ionizable feature. The correlation coefficient of observed versus predicted IC 50 was 0.86 for this training set, which was superior to calculated logP alone (r ϭ 0.73) as a predictor of hOCT1 inhibition. A descriptor-based quantitative structure-activity relationship study using Cerius 2 resulted in an equation relating five molecular descriptors to log IC 50 with a correlation coefficient of 0.95. Furthermore, a group of phenylpyridinium and quinolinium compounds were used to investigate the spatial limitations of the hOCT1 binding site. The affinity for hOCT was higher for 4-phenylpyridiniums Ͼ 3-phenylpyridiniums Ͼ quinolinium, indicating that substrate affinity was influenced by the distribution of hydrophobic mass. In addition, supraplanar hydrophobic mass was found to increase the affinity for binding hOCT1. These results indicate how a combination of computational and in vitro approaches may yield insight into the binding affinity of transporters and may be applicable to predicting these properties for new therapeutics.The transepithelial transport of organic cations (OCs) plays an important role in the excretion of xenobiotic compounds from the body by means of the liver and kidney, and from the cerebrospinal fluid via the choroid plexus (Pritchard and Miller, 1993). The proteins involved in the translocation of OCs transport a broad range of substrates. These substrates include naturally occurring plant alkaloids and synthetic drugs such as cimetidine and procainamide. These chemicals are not only therapeutically diverse but show remarkable structural diversity as well. A characterization of the structural parameters of substrates translocated by organic cation transporters may provide insight into the molecular determinants of substrate specificity (Ullrich, 1999). Because the elimination of many therapeutic drugs is significantly influenced by the interaction of these compounds with OC transporters, information pertinent to predicting the kinetics of such interactions may be useful in estimating the pharmacokinetics of a broad range of pharmaceuticals.The organic cation transporter,

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Recent developments in high-throughput screening and combinatorial chemistry have generated interest in experimental design methods to select subsets of molecules from large chemical databases. In this manuscript three methods for selecting molecules from large databases are described:  edge designs, spread designs, and coverage designs. Two algorithms with linear time complexity that approximate spread and coverage designs are described. These algorithms can be threaded for multiprocessor systems, are compatible with any definition of molecular distance, and may be applied to very large chemical databases. For example, ten thousand molecules were selected using the maximum dissimilarity approximation to a spread design from a sixty-dimensional simulated molecular database of one million molecules in approximately 6 h on a UNIX workstation.

Chemotherapy-induced peripheral neuropathy (CIPN) is a potentially debilitating side effect of a number of chemotherapeutic agents. There are currently no U.S. Food and Drug Administration-approved interventions or prevention strategies for CIPN. Although the cellular mechanisms mediating CIPN remain to be determined, several lines of evidence support the notion that DNA damage caused by anticancer therapies could contribute to the neuropathy. DNA damage in sensory neurons after chemotherapy correlates with symptoms of CIPN. Augmenting apurinic/apyrimidinic endonuclease (APE)-1 function in the base excision repair pathway reverses this damage and the neurotoxicity caused by anticancer therapies. This neuronal protection is accomplished by either overexpressing APE1 or by using a first-generation targeted APE1 small molecule, E3330 [(2E)-2-[(4,5-dimethoxy-2-methyl-3,6-dioxo-1,4-cyclohexadien-1-yl)methylene]-undecanoic acid; also called APX3330]. Although E3330 has been approved for phase 1 clinical trials (Investigational New Drug application number IND125360), we synthesized novel, second-generation APE1-targeted molecules and determined whether they would be protective against neurotoxicity induced by cisplatin or oxaliplatin while not diminishing the platins' antitumor effect. We measured various endpoints of neurotoxicity using our ex vivo model of sensory neurons in culture, and we determined that APX2009is an effective small molecule that is neuroprotective against cisplatin and oxaliplatin-induced toxicity. APX2009 also demonstrated a strong tumor cell killing effect in tumor cells and the enhanced tumor cell killing was further substantiated in a more robust three-dimensional pancreatic tumor model. Together, these data suggest that the secondgeneration compound APX2009 is effective in preventing or reversing platinum-induced CIPN while not affecting the anticancer activity of platins.