A practical application of two in silico systems for identification of potentially mutagenic impurities.

The International Conference on Harmonization (ICH) M7 guidance for the assessment and control of DNA reactive impurities in pharmaceutical products includes the use of in silico prediction systems as part of the hazard identification and risk assessment strategy. This is the first internationally agreed guidance document to include the use of these types of approaches. The guideline requires the use of two complementary approaches, an expert rule-based method and a statistical algorithm. In addition, the guidance states that the output from these computer-based assessments can be reviewed using expert knowledge to provide additional support or resolve conflicting predictions. This approach is designed to maximize the sensitivity for correctly identifying DNA reactive compounds while providing a framework to reduce the number of compounds that need to be synthesized, purified and subsequently tested in an Ames assay. Using a data set of 801 chemicals and pharmaceutical intermediates, we have examined the relative predictive performances of some popular commercial in silico systems that are in common use across the pharmaceutical industry. The overall accuracy of each of these systems was fairly comparable ranging from 68% to 73%; however, the sensitivity of each system (i.e. how many Ames positive compounds are correctly identified) varied much more dramatically from 48% to 68%. We have explored how these systems can be combined under the ICH M7 guidance to enhance the detection of DNA reactive molecules. Finally, using four smaller sets of molecules, we have explored the value of expert knowledge in the review process, especially in cases where the two systems disagreed on their predictions, and the need for care when evaluating the predictions for large data sets.

Development and validation of an in vitro micronucleus assay platform in TK6 cells.

The Organization for Economic Co-operation and Development (OECD) has recently adopted Test Guideline 487 (TG487) for conducting the in vitro micronucleus (MNvit) assay. The purpose of this study is to evaluate and validate treatment conditions for the use of p53 competent TK6 human lymphoblastoid cells in a TG487 compliant MNvit assay. The ten reference compounds suggested in TG487 (mitomycin C, cytosine arabinoside, cyclophosphamide, benzo-a-pyrene, vinblastine sulphate, colchicine, sodium chloride, nalidixic acid and di(2-ethylhexyl)phthalate and pyrene) and noscapine hydrochloride were chosen for this study. In order to optimize the micronucleus response after treatment with some positive substances, we extended the recovery time after pulse treatment from 2 cell cycles recommended in TG487 to 3 cell cycles for untreated cells (40h). Each compound was tested in at least one of four exposure conditions: a 4h exposure followed by a 40h recovery, a 4h exposure followed by a 24h recovery, a 4h exposure in the presence of an exogenous metabolic activation system followed by a 40h recovery period, and a 27h continuous direct treatment. Results show that the direct acting clastogens, clastogens requiring metabolic activation and aneugens caused a robust increase in micronuclei in at least one test condition whereas the negative compounds did not induce micronuclei. The negative control cultures exhibited reproducibly low and consistent micronucleus frequencies ranging from 0.4 to 1.8% (0.8±0.3% average and standard deviation). Furthermore, extending the recovery period from 24h to 40h produced a 2-fold higher micronucleus frequency after a 4h pulse treatment with mitomycin C. In summary, the protocol described in this study in TK6 cells produced the expected result with model compounds and should be suitable for performing the MNvit assay in accordance with guideline TG487.

In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey.

With the increasing emphasis on identification and low level control of potentially genotoxic impurities (GTIs), there has been increased use of structure-based assessments including application of computerized models. To date many publications have focused on the ability of computational models, either individually or in combination, to accurately predict the mutagenic effects of a chemical in the Ames assay. Typically, these investigations take large numbers of compounds and use in silico tools to predict their activity with no human interpretation being made. However, this does not reflect how these assessments are conducted in practice across the pharmaceutical industry. Current guidelines indicate that a structural assessment is sufficient to conclude that an impurity is non-mutagenic. To assess how confident we can be in identifying non-mutagenic structures, eight companies were surveyed for their success rate. The Negative Predictive Value (NPV) of the in silico approaches was 94%. When human interpretation of in silico model predictions was conducted, the NPV increased substantially to 99%. The survey illustrates the importance of expert interpretation of in silico predictions. The survey also suggests the use of multiple computational models is not a significant factor in the success of these approaches with respect to NPV.

Discovery of two clinical histamine H(3) receptor antagonists: trans-N-ethyl-3-fluoro-3-[3-fluoro-4-(pyrrolidinylmethyl)phenyl]cyclobutanecarboxamide (PF-03654746) and trans-3-fluoro-3-[3-fluoro-4-(pyrrolidin-1-ylmethyl)phenyl]-N-(2-methylpropyl)cyclobutanecarboxamide (PF-03654764).

The discovery of two histamine H(3) antagonist clinical candidates is disclosed. The pathway to identification of the two clinical candidates, 6 (PF-03654746) and 7 (PF-03654764) required five hypothesis driven design cycles. The key to success in identifying these clinical candidates was the development of a compound design strategy that leveraged medicinal chemistry knowledge and traditional assays in conjunction with computational and in vitro safety tools. Overall, clinical compounds 6 and 7 exceeded conservative safety margins and possessed optimal pharmacological and pharmacokinetic profiles, thus achieving our initial goal of identifying compounds with fully aligned oral drug attributes, "best-in-class" molecules.

Discovery and characterization of QPT-1, the progenitor of a new class of bacterial topoisomerase inhibitors.

QPT-1 was discovered in a compound library by high-throughput screening and triage for substances with whole-cell antibacterial activity. This totally synthetic compound is an unusual barbituric acid derivative whose activity resides in the (-)-enantiomer. QPT-1 had activity against a broad spectrum of pathogenic, antibiotic-resistant bacteria, was nontoxic to eukaryotic cells, and showed oral efficacy in a murine infection model, all before any medicinal chemistry optimization. Biochemical and genetic characterization showed that the QPT-1 targets the beta subunit of bacterial type II topoisomerases via a mechanism of inhibition distinct from the mechanisms of fluoroquinolones and novobiocin. Given these attributes, this compound represents a promising new class of antibacterial agents. The success of this reverse genomics effort demonstrates the utility of exploring strategies that are alternatives to target-based screens in antibacterial drug discovery.

Ligand-specific activation of Escherichia coli chemoreceptor transmethylation.

Adaptation in the chemosensory pathways of bacteria like Escherichia coli is mediated by the enzyme-catalyzed methylation (and demethylation) of glutamate residues in the signaling domains of methyl-accepting chemotaxis proteins (MCPs). MCPs can be methylated in trans, where the methyltransferase (CheR) molecule catalyzing methyl group transfer is tethered to the C terminus of a neighboring receptor. Here, it was shown that E. coli cells exhibited adaptation to attractant stimuli mediated through either engineered or naturally occurring MCPs that were unable to tether CheR as long as another MCP capable of tethering CheR was also present, e.g., either the full-length aspartate or serine receptor (Tar or Tsr). Methylation of isolated membrane samples in which engineered tethering and substrate receptors were coexpressed demonstrated that the truncated substrate receptors (trTsr) were efficiently methylated in the presence of tethering receptors (Tar with methylation sites blocked) relative to samples in which none of the MCPs had tethering sites. The effects of ligand binding on methylation were investigated, and an increase in rate was produced only with serine (the ligand specific for the substrate receptor trTsr); no significant change in rate was produced by aspartate (the ligand specific for the tethering receptor Tar). Although the overall efficiency of methylation was lower, receptor-specific effects were also observed in trTar- and trTsr-containing samples, where neither Tar nor Tsr possessed the CheR binding site at the C terminus. Altogether, the results are consistent with a ligand-induced conformational change that is limited to the methylated receptor dimer and does not spread to adjacent receptor dimers.