The reactive metabolite target protein database (TPDB) – a web-accessible resource

BACKGROUND: The toxic effects of many simple organic compounds stem from their biotransformation to chemically reactive metabolites which bind covalently to cellular proteins. To understand the mechanisms of cytotoxic responses it may be important to know which proteins become adducted and whether some may be common targets of multiple toxins. The literature of this field is widely scattered but expanding rapidly, suggesting the need for a comprehensive, searchable database of reactive metabolite target proteins. DESCRIPTION: The Reactive Metabolite Target Protein Database (TPDB) is a comprehensive, curated, searchable, documented compilation of publicly available information on the protein targets of reactive metabolites of 18 well-studied chemicals and drugs of known toxicity. TPDB software enables i) string searches for author names and proteins names/synonyms, ii) more complex searches by selecting chemical compound, animal species, target tissue and protein names/synonyms from pull-down menus, and iii) commonality searches over multiple chemicals. Tabulated search results provide information, references and links to other databases. CONCLUSION: The TPDB is a unique on-line compilation of information on the covalent modification of cellular proteins by reactive metabolites of chemicals and drugs. Its comprehensiveness and searchability should facilitate the elucidation of mechanisms of reactive metabolite toxicity. The database is freely available a

Expression pattern of class I histone deacetylases in vulvar intraepithelial neoplasia and vulvar cancer: a tissue microarray study

BACKGROUND: Epigenetic regulation is an important mechanism leading to cancer initiation and promotion. Histone acetylation by histone deacetylases (HDACs) represents an important part of it. The development of HDAC inhibitors has identified the utility of HDACs as a therapeutic target. Little is known about the epigenetic regulation of vulvar intraepithelial neoplasia (VIN) and vulvar squamous cell cancer (VSCC). In this study, the expression of class I HDACs (HDAC 1, 2 and 3) was compared in a series of VIN and VSCC tissues. METHODS: A tissue micro array (TMA) with specimens from 106 patients with high-grade VIN and 59 patients with vulvar cancer was constructed. The expression of HDACs 1, 2 and 3 were analyzed with immunohistochemistry (IHC). The nuclear expression pattern was evaluated in terms of intensity and percentage of stained nuclei and was compared between vulvar preinvasive lesions and vulvar cancer. RESULTS: HDAC 2 expression was significantly higher in VIN than in VSCC (p < 0.001, Fisher's test). Also, 88.7% (n=94/106) of VIN samples and only 54.5% (n=31/57) of VSCC samples were scored at the maximum level. Conversely, HDAC 3 expression was significantly higher in VSCC (93%, 53/57) compared to VIN (73.6%, 78/106, p=0.003), whereas only a small difference in the expression of HDAC 1 was found between these two entities of vulvar neoplasia. CONCLUSIONS: These results suggest that epigenetic regulation plays a considerable role in the transformation of VIN to invasive vulvar neoplasia

Pharmacophore modeling and in silico toxicity assessment of potential anticancer agents from African medicinal plants

Fidele Ntie-Kang,1,2,* Conrad Veranso Simoben,1,2,* Berin Karaman,1 Valery Fuh Ngwa,3 Philip Neville Judson,4 Wolfgang Sippl,1 Luc Meva&rsquo;a Mbaze5 1Department of Pharmaceutical Chemistry, Martin-Luther University of Halle-Wittenberg, Halle (Saale), Germany; 2Department of Chemistry, University of Buea, Buea, Cameroon; 3Interuniversity Institute For Biostatistics and Statistical Bioinformatics (I-BioStat), University of Hasselt, Hasselt, Belgium; 4Chemical Bioactivity Information Centre, Harrogate, UK; 5Department of Chemistry, Faculty of Science, University of Douala, Douala, Cameroon *These authors contributed equally to this work Abstract: Molecular modeling has been employed in the search for lead compounds of chemotherapy to fight cancer. In this study, pharmacophore models have been generated and validated for use in virtual screening protocols for eight known anticancer drug targets, including tyrosine kinase, protein kinase B &beta;, cyclin-dependent kinase, protein farnesyltransferase, human protein kinase, glycogen synthase kinase, and indoleamine 2,3-dioxygenase 1. Pharmacophore models were validated through receiver operating characteristic and G&uuml;ner&ndash;Henry scoring methods, indicating that several of the models generated could be useful for the identification of potential anticancer agents from natural product databases. The validated pharmacophore models were used as three-dimensional search queries for virtual screening of the newly developed AfroCancer database (~400 compounds from African medicinal plants), along with the Naturally Occurring Plant-based Anticancer Compound-Activity-Target dataset (comprising ~1,500 published naturally occurring plant-based compounds from around the world). Additionally, an in silico assessment of toxicity of the two datasets was carried out by the use of 88 toxicity end points predicted by the Lhasa&rsquo;s expert knowledge-based system (Derek), showing that only an insignificant proportion of the promising anticancer agents would be likely showing high toxicity profiles. A diversity study of the two datasets, carried out using the analysis of principal components from the most important physicochemical properties often used to access drug-likeness of compound datasets, showed that the two datasets do not occupy the same chemical space. Keywords: anticancer, natural products, medicinal plants, pharmacophore, toxicity, virtual screenin

Early prediction of ecotoxicological side effects of pharmaceutical impurities based on open-source non-testing approaches

Despite the increasing efforts to limit waste and avoid environmental contaminants, a large number of compounds using in the pharmaceutical field may have an ecotoxicological impact. Nevertheless, a complete overview of all possible ecotoxicological effects of pharmaceuticals is missing: that is especially true for chemical impurities. The lacking information regarding environmental behavior of impurities could be faced by computational techniques: the ability to predict the unknown toxicity of a compound can reduce uncertainties regarding possible negative effects on the environment of pharmaceutical impurities. In the current scenario, non-testing methods may answer to the requirement of assessing the ecotoxicological impact of chemicals in a more affordable way. For this purpose, in the first part of the review, definition and classification of chemical impurities are proposed, while in the second part, a description of four open-source computational tools (T.E.S.T., VEGA, LAZAR, and QSAR Toolbox) is provided after a brief survey of the computational methods. The paper also shows the advantages of combining individual test methods in order to increase confidence in the predictive results