Structural diversity of biologically interesting datasets: a scaffold analysis approach

ABSTRACT:The recent public availability of the human metabolome and natural product datasets has revitalized "metabolite-likeness" and "natural product-likeness" as a drug design concept to design lead libraries targeting specific pathways. Many reports have analyzed the physicochemical property space of biologically important datasets, with only a few comprehensively characterizing the scaffold diversity in public datasets of biological interest. With large collections of high quality public data currently available, we carried out a comparative analysis of current day leads with other biologically relevant datasets.In this study, we note a two-fold enrichment of metabolite scaffolds in drug dataset (42%) as compared to currently used lead libraries (23%). We also note that only a small percentage (5%) of natural product scaffolds space is shared by the lead dataset. We have identified specific scaffolds that are present in metabolites and natural products, with close counterparts in the drugs, but are missing in the lead dataset. To determine the distribution of compounds in physicochemical property space we analyzed the molecular polar surface area, the molecular solubility, the number of rings and the number of rotatable bonds in addition to four well-known Lipinski properties. Here, we note that, with only few exceptions, most of the drugs follow Lipinski's rule. The average values of the molecular polar surface area and the molecular solubility in metabolites is the highest while the number of rings is the lowest. In addition, we note that natural products contain the maximum number of rings and the rotatable bonds than any other dataset under consideration.Currently used lead libraries make little use of the metabolites and natural products scaffold space. We believe that metabolites and natural products are recognized by at least one protein in the biosphere therefore, sampling the fragment and scaffold space of these compounds, along with the knowledge of distribution in physicochemical property space, can result in better lead libraries. Hence, we recommend the greater use of metabolites and natural products while designing lead libraries. Nevertheless, metabolites have a limited distribution in chemical space that limits the usage of metabolites in library design.14 page(s

PET/CT Imaging of c-Myc Transgenic Mice Identifies the Genotoxic N-Nitroso-Diethylamine as Carcinogen in a Short-Term Cancer Bioassay

Background: More than 100,000 chemicals are in use but have not been tested for their safety. To overcome limitations in the cancer bioassay several alternative testing strategies are explored. The inability to monitor non-invasively onset and progression of disease limits, however, the value of current testing strategies. Here, we report the application of in vivo imaging to a c-Myc transgenic mouse model of liver cancer for the development of a short-term cancer bioassay. Methodology/Principal Findings: mCT and 18 F-FDG mPET were used to detect and quantify tumor lesions after treatment with the genotoxic carcinogen NDEA, the tumor promoting agent BHT or the hepatotoxin paracetamol. Tumor growth was investigated between the ages of 4 to 8.5 months and contrast-enhanced mCT imaging detected liver lesions as well as metastatic spread with high sensitivity and accuracy as confirmed by histopathology. Significant differences in the onset of tumor growth, tumor load and glucose metabolism were observed when the NDEA treatment group was compared with any of the other treatment groups. NDEA treatment of c-Myc transgenic mice significantly accelerated tumor growth and caused metastatic spread of HCC in to lung but this treatment also induced primary lung cancer growth. In contrast, BHT and paracetamol did not promote hepatocarcinogenesis. Conclusions/Significance: The present study evidences the accuracy of in vivo imaging in defining tumor growth, tumor load, lesion number and metastatic spread. Consequently, the application of in vivo imaging techniques to transgeni

Power, expertise and the limits of representative democracy: genetics as scientific progress or political legitimation in carcinogenic risk assessment of pharmaceuticals?

In modern ‘representative’ democratic states, the legitimacy of governments’ actions rests on their publicly declared commitment to protect the interests of their citizens. Regarding the pharmaceutical sector in most democracies, new drug products are developed and marketed by a capitalist industry, whose member firms, via shareholders, have commercial interests in expanding product sales. In those democracies, states have established government agencies to regulate the pharmaceutical industry on behalf of citizens. State legislatures, such as the US Congress and European Parliaments, have charged government drug regulatory agencies with the legal responsibility to protect public health. Yet, this paper argues that government drug regulatory agencies in the EU, Japan, and USA have permitted the pharmaceutical industry to reshape the regulatory guidance for carcinogenic risk assessment of pharmaceuticals in ways that are not techno-scientifically defensible as bases for improved, or even equivalent, protection of public health, compared with the previous techno-regulatory standards. By adopting the industry’s agenda of streamlining carcinogenicity testing in order to accelerate drug development and regulatory review, it is contended that these regulatory agencies have allowed the techno-regulatory standards for carcinogenic risk assessment to be loosened in ways that are presented as scientific progress resulting from new genetics, but for which there is little evidence of progress in public health protection