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Chemical genomics: a challenge for de novo drug design

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Abstract

De novo design provides an in silico toolkit for the design of novel small molecular structures to a set of specified structural constraints. With the avalanche of bioinformatics data, de novo design is ideally suited for exploring molecules that could be useful for chemical genomics. The design process involves manipulation of the input, modification of structural constraints, and further processing of the de novo generated molecules using various modular toolkits. The development of a theoretical framework for each of these stages will provide novel practical solutions to the problem of creating compounds with maximal chemical diversity. This short review describes the fundamental problems encountered in the application of novel chemical design technologies to chemical genomics by means of a formal representation. This notation helps to outline and clarify ideas and hypotheses that can then be explored using mathematical algorithms. It is only by developing this rigorous foundation that in silico design can progress in a rational way.

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References

  1. Read, J., Pearce, J., Li, X., Muirhead, H., Chirgwin, J., & Davies, C. (2001). The crystal structure of human phosphoglucose isomerase at 1.6A resolution: Implications for catalytic mechanism, cytokine activity and haemolytic anaemia. Journal of Molecular Biology, 309, 447–463.

    Article  PubMed  CAS  Google Scholar 

  2. Tsutsumi, S., Yanagawa, T., Shimura, T., Fukumori, T., Hogan, V., Kuwano, H., & Raz, A. (2003). Regulation of cell proliferation by autocrine motility factor/phospoglucose isomerase signaling. Journal of Biological Chemistry, 278, 32165–32172.

    Article  PubMed  CAS  Google Scholar 

  3. Ohi, M. D., Vander Kooi, C. W., Rosenberg, J. A., Chazin, W. J., & Gould, K. L. (2003). Structural insights into the U-box, a domain associated with multi-ubiquitination. Nature Structural Biology, 10, 250–255.

    Article  PubMed  CAS  Google Scholar 

  4. Bohacek, R. S., Martin, C., & Guida, W. C. (1996). The art and practice of structure-based drug design: A molecular modeling perspective. Medical Research Review, 16, 3–50.

    Article  CAS  Google Scholar 

  5. Magwene, P. M., & Kim, J. (2004). Estimating genomic coexpression networks using first-order conditional independence. Genome Biology 5, R100.1–R100.16.

    Article  Google Scholar 

  6. di Bernardo, D., Thompson, M. J., Gardener, T. S., Chobot, S. E., Eastwood, E. L., Wojtovich, A. P., Elliot, S. J., Schaus, S. E., & Collins, J. J. (2005). Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks. Nature Biotechnology, 23, 377–383.

    Article  PubMed  Google Scholar 

  7. Zhou, X., Wang, X., & Dougherty, E. R. (2003). Construction of genomic networks using mutual-information clustering and reversible-jump Markov chain Monte-Carlo predictor design. Signal Processing, 83, 745–761.

    Article  Google Scholar 

  8. Hartemink, A. J., Gifford, D. K., Jaakola, T. S., & Young, R. A. (2001). Using graphical models and genomic expression data to statistically validate models of genetic regulatory networks. Pacific Symposium in Biocomputing, 6, 422–433.

    Google Scholar 

  9. Shah, N. P., et al. (2002). Multiple BRC-ABL kinase domain mutations confer polyclonal resistance to the tyrosine kinase inhibitor imatinib (ST1571) in chronic phase and blast crisis chronic myeloid leukemia. Cancer Cell, 2, 117–125.

    Article  PubMed  CAS  Google Scholar 

  10. Shah, N. P., et al. (2004). Overriding imatinib resistance with a novel ABL kinase inhibitor. Science, 305, 399–400.

    Article  PubMed  CAS  Google Scholar 

  11. Azam, M., Nardi, V., Shakespeare, W. C., Metcalf, C. A., Bohacek, R. S., Wang, Y., Sundaramoorthi, R., Sliz, P., Veach, D. R., Bornmann, W. G., Clarkson, B., Dalgarno, D. C., Sawyer, T. K., & Daley, G. Q. (2006). Activity of dual SRC/ABL inhibitors highlights the role of BCR/ABL kinase dynamics in drug resistance. PNAS, 103, 9244–9249.

    Article  PubMed  CAS  Google Scholar 

  12. Duarte, N. C., Becker, S. A., Jamshidi, N., Thiele, I., Mo, M. L., Vo, T. D., Srivas, R., & Palsson, B. O. (2007). Global reconstruction of the human metabolic network based on genomic and bibliomic data. PNAS, 104, 1777–1782.

    Article  PubMed  CAS  Google Scholar 

  13. Koonin, E. V. (1999). http://kr.expasy.org/cgi-bin/prosite-search-ac?PDOC00017

  14. Deng, Z., Chuaqui, C., & Singh, J. (2004). Structural interaction fingerprint (SIFt): A novel method for analyzing three-dimensional protein-ligand binding interactions. Journal of Medical Chemistry 47, 337–344.

    Article  CAS  Google Scholar 

  15. Levitt, M. (2007). Growth of novel protein structural data. PNAS, 104, 3183–3188.

    Article  PubMed  CAS  Google Scholar 

  16. O’Toole, N., Raymond, S., & Cygler, M. (2003). Coverage of protein sequence space by current structural genomics. Journal of Structural and Functional Genomics, 4, 47–55.

    Article  PubMed  CAS  Google Scholar 

  17. Todorov, N. P., Alberts, I. L., Dean, P. M. (2007). De novo design. In J. Mason (Ed.), Comprehensive medicinal chemistry II, Vol. 4, Chapter 13, (pp. 283–305). Elzevier Ltd.

  18. Todorov, N. P., & Dean, P. M. (1997). An evaluation of a method for controlling molecular scaffold diversity in de novo ligand design. Journal of Computer-Aided Molecular Design, 11, 175–192.

    Article  PubMed  CAS  Google Scholar 

  19. Mancera, R. L. (2002). De novo ligand design with explicit water molecules: an application to bacterial neuraminidase. Journal of Computer-Aided Molecular Design, 16, 479–499.

    Article  PubMed  CAS  Google Scholar 

  20. Lloyd, G. G., Garcia-Sosa, A., Alberts, I. L., Todorov, N. P., & Mancera, R. L. (2004a). The effect of tightly bound water molecules on the structural interpretation of ligand-derived pharmacophore models. Journal of Computer-Aided Molecular Design, 18, 89–100.

    Article  PubMed  CAS  Google Scholar 

  21. Stahl, M., Todorov, N. P., Tames, T., Mauser, H., Boehm, H.-J., & Dean, P. M. (2002). A validation study on the practical use of de novo design. Journal of Computer-Aided Molecular Design, 16, 459–478.

    Article  PubMed  CAS  Google Scholar 

  22. Firth-Clark, S., Todorov, N. P., Alberts, I. L., Williams, A., James, T., & Dean, P. M. (2006). Exhaustive de novo design of low-molecular weight fragments against the ATP-binding site of DNA-gyrase. Journal of Chemical Information Modelling, 46, 1168–1173.

    Article  CAS  Google Scholar 

  23. Lloyd, D. G., Buenemann, C. L., Todorov, N. P., Manallack, D. T., & Dean, P. M. (2004b). Scaffold hopping in de novo drug design – ligand generation in the absence of receptor information. Journal of Medical Chemistry, 47, 493–496.

    Article  CAS  Google Scholar 

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  1. De Novo Pharmaceuticals Ltd, Vision Park, Compass House, Histon, Cambridge, CB4 9ZR, UK

    P. M. Dean

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  1. P. M. Dean
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Dean, P.M. Chemical genomics: a challenge for de novo drug design. Mol Biotechnol 37, 237–245 (2007). https://doi.org/10.1007/s12033-007-0037-x

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  • DOI: https://doi.org/10.1007/s12033-007-0037-x

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