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      Evaluation of molecular descriptors for antitumor drugs with respect to noncovalent binding to DNA and antiproliferative activity

      research-article
      1 ,
      BMC Pharmacology
      BioMed Central

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          Abstract

          Background

          Small molecules that bind reversibly to DNA are among the antitumor drugs currently used in chemotherapy. In the pursuit of a more rational approach to cancer chemotherapy based upon these molecules, it is necessary to exploit the interdependency between DNA-binding affinity, sequence selectivity and cytotoxicity. For drugs binding noncovalently to DNA, it is worth exploring whether molecular descriptors, such as their molecular weight or the number of potential hydrogen acceptors/donors, can account for their DNA-binding affinity and cytotoxicity.

          Results

          Fifteen antitumor agents, which are in clinical use or being evaluated as part of the National Cancer Institute's drug screening effort, were analyzed in silico to assess the contribution of various molecular descriptors to their DNA-binding affinity, and the capacity of the descriptors and DNA-binding constants for predicting cell cytotoxicity. Equations to predict drug-DNA binding constants and growth-inhibitory concentrations were obtained by multiple regression following rigorous statistical procedures.

          Conclusion

          For drugs binding reversibly to DNA, both their strength of binding and their cytoxicity are fairly predicted from molecular descriptors by using multiple regression methods. The equations derived may be useful for rational drug design. The results obtained agree with that compounds more active across the National Cancer Institute's 60-cell line data set tend to have common structural features.

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          Most cited references40

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          A gene expression database for the molecular pharmacology of cancer.

          We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity patterns in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology.
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            DNA and its associated processes as targets for cancer therapy.

            DNA is the molecular target for many of the drugs that are used in cancer therapeutics, and is viewed as a non-specific target of cytotoxic agents. Although this is true for traditional chemotherapeutics, other agents that were discovered more recently have shown enhanced efficacy. Furthermore, a new generation of agents that target DNA-associated processes are anticipated to be far more specific and effective. How have these agents evolved, and what are their molecular targets?
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              An information-intensive approach to the molecular pharmacology of cancer.

              Since 1990, the National Cancer Institute (NCI) has screened more than 60,000 compounds against a panel of 60 human cancer cell lines. The 50-percent growth-inhibitory concentration (GI50) for any single cell line is simply an index of cytotoxicity or cytostasis, but the patterns of 60 such GI50 values encode unexpectedly rich, detailed information on mechanisms of drug action and drug resistance. Each compound's pattern is like a fingerprint, essentially unique among the many billions of distinguishable possibilities. These activity patterns are being used in conjunction with molecular structural features of the tested agents to explore the NCI's database of more than 460,000 compounds, and they are providing insight into potential target molecules and modulators of activity in the 60 cell lines. For example, the information is being used to search for candidate anticancer drugs that are not dependent on intact p53 suppressor gene function for their activity. It remains to be seen how effective this information-intensive strategy will be at generating new clinically active agents.
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                Author and article information

                Journal
                BMC Pharmacol
                BMC Pharmacology
                BioMed Central
                1471-2210
                2009
                16 September 2009
                : 9
                : 11
                Affiliations
                [1 ]Instituto de Biología Molecular de Barcelona, CSIC, Parc Cientific de Barcelona, Baldiri Reixac, 10, E-08028 Barcelona, Spain
                Article
                1471-2210-9-11
                10.1186/1471-2210-9-11
                2758867
                19758437
                b6bdb597-179e-493a-a515-39c95ae9b1ca
                Copyright © 2009 Portugal; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 February 2009
                : 16 September 2009
                Categories
                Research Article

                Pharmacology & Pharmaceutical medicine
                Pharmacology & Pharmaceutical medicine

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