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Statistical Molecular Design: A Tool to Follow Up Hits from Small-Molecule Screening

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Plant Chemical Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1056))

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Abstract

In high-throughput screening (HTS) a robust assay is used to interrogate a large collection of small organic molecules in order to find compounds, hits, with a desired biological activity. The hits are then further explored by an iterative process where new compounds are designed, purchased, or synthesized, followed by an evaluation in one or more assays. Statistical molecular design (SMD) is a useful method to select a balanced, varied, and information-rich compound collection based on hits from HTS in order to create a foundation for development of optimized compounds with improved properties. In this chapter, we describe the use of SMD to explore a hit obtained from small-molecule screening.

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References

  1. Wold S, Josefson M, Gottfries J, Linusson A (2003) The utility of multivariate design in PLS modeling. J Chemom 18:156–165

    Article  Google Scholar 

  2. Eriksson L, Johansson E (1996) Multivariate design and modeling in QSAR. Chemom Intell Lab Syst 34:1–19

    Article  CAS  Google Scholar 

  3. Johnson SR (2006) The trouble with QSAR (or how I learned to stop worrying and embrace fallacy). J Chem Inf Model 48:25–26

    Article  Google Scholar 

  4. Linusson A, Elofsson M, Andersson IE, Dahlgren MK (2010) Statistical molecular design of balanced compound libraries for QSAR modeling. Curr Med Chem 17:2001–2016

    Article  PubMed  CAS  Google Scholar 

  5. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1979) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25

    Article  Google Scholar 

  6. Jackson JE (1991) A user’s guide to principal components. Wiley, New York

    Book  Google Scholar 

  7. http://www.sigmaaldrich.com/catalog/search/substructure/SubstructureSearchPage. Accessed 14 Sep 2011

  8. FILTER 2.0.2., OpenEye Scientific Software, 9 Bisbee Court, Suite D, Santa Fe, NM 87508, USA. http://www.eyesopen.com. Accessed 14 Sep 2011

  9. MOE 2010.10., Chemical Computing Group, 1010 Sherbrooke St. W, Suite 910, Montreal, Quebec, Canada H3A 2R7. http://www.chemcomp.com. Accessed 14 Sep 2011

  10. SIMCA-P+ 12.0.1., Umetrics AB, Box 7960, SE-907 19, Umeå, Sweden. http://www.umetrics.com. Accessed 14 Sep2011

  11. MODDE 9.0., Umetrics AB, Box 7960, SE-907 19, Umeå, Sweden. http://www.umetrics.com. Accessed 14 Sep 2011

  12. Dahlgren MD, Zetterström CE, Gylfe Å, Linusson A, Elofsson M (2010) Design, synthesis and multivariate quantitative structure-activity relationship of salicylidenacylhydrazides—inhibitors of type III Secretion in Yersinia. Bioorg Med Chem 18:2686–2703

    Article  PubMed  CAS  Google Scholar 

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Acknowledgment

This work was supported by the Swedish Research Council, the Swedish Foundation for Strategic Research, and the Knut and Alice Wallenberg Foundation.

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© 2014 Springer Science+Business Media, New York

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Lindgren, A.E.G., Larsson, A., Linusson, A., Elofsson, M. (2014). Statistical Molecular Design: A Tool to Follow Up Hits from Small-Molecule Screening. In: Hicks, G., Robert, S. (eds) Plant Chemical Genomics. Methods in Molecular Biology, vol 1056. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-592-7_17

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  • DOI: https://doi.org/10.1007/978-1-62703-592-7_17

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-591-0

  • Online ISBN: 978-1-62703-592-7

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