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Working with Small Molecules: Rules-of-Thumb of “Drug Likeness”

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Book cover Chemical Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 803))

Abstract

Based on analyses of existing small organic drug molecules, a set of “rules-of-thumb” have been devised to assess the likeness of a small molecule under study to those existing drugs in terms of physicochemical and topological properties. These rules can be used to estimate the likelihood of a small molecule to possess the desired efficacy, pharmacokinetic/pharmacodynamic properties, and toxicity profiles to eventually become a drug, and therefore, whether it justifies further experimental work and development. These rules are particularly useful when selecting a chemical starting point for a given project or choosing a chemical series to focus when multiple series are available. Caution should be paid, however, not to overly rely on these rules for decision-making, since these rules are restricted by knowledge of existing drugs. Novel chemotypes and/or targets may be exceptions.

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References

  1. Takaoka, Y., Endo, Y., Yamanobe, S., Kakinuma, H., Okubo, T., Shimazaki, Y., Ota,T., Sumiya, S., and Yoshikawa, K. (2003) Development of a method for evaluating drug-likeness and ease of synthesis using a data set in which compounds are assigned scores based on chemists’ intuition. J. Chem. Inf. Comput. Sci. 43, 1269–1275.

    Google Scholar 

  2. Leeson, P.D., and Springthorpe, B. (2007) The influence of drug-like concepts on decision-making in medicinal chemistry. Nat. Rev. Drg Disc. 6, 881–890.

    Google Scholar 

  3. Young, D.C. Computational Drug Design: A Guide for Computational and Medicinal Chemists, Wiley-Interscience (February 12, 2009) ISBN-10: 047012685X; Tudor I. Oprea (Editor). Chemoinformatics in Drug Discovery. Wiley-VCH (May 6, 2005) ISBN-10: 3527307532 and other volumes in the book series of Methods and Principles in Medicinal Chemistry, Mannhold R., Kubinyi H., and Folkers G (Eds).

    Google Scholar 

  4. Lipkus, A.H., Yuan, Q., Lucas, K.A., Funk, S.A., Bartelt III, W. F., Schenck, R. J., and Trippe, A.J. (2008) Structural diversity of organic chemistry. A scaffold analysis of the CAS registry. J. Org. Chem. 73, 4443–4451.

    Google Scholar 

  5. Bemis, G.W., and Murcko, M.A. (1996) The properties of known drugs. 1. Molecular frameworks. J. Med. Chem 39, 2887–2893.

    Google Scholar 

  6. Duarte, C.D., Barreiro, E.J., and Fraga, C.A. (2007) Privileged structures: a useful concept for the rational design of new lead drug candidates. Mini Rev. Med. Chem. 7, 1108–1119.

    Google Scholar 

  7. Abad-Zapatero, C., and Metz, J.T. (2005) Ligand efficiency indices as guideposts for drug discovery. Drug Disc Today 10, 464–469.

    Google Scholar 

  8. Bembenek, S.D., Tounge, B.A., and Reynolds, C.H. (2009) Ligand efficiency and fragment-based drug discovery. Drug Disc. Today 14, 278–283.

    Google Scholar 

  9. Nissink, J.W.M. (2009) Simple size-independent measure of ligand efficiency. J. Chem. Inf. Model 49, 1617–1622.

    Google Scholar 

  10. Olsson, T.S.G., Williams, M.A., Pitt, W.R., and Ladbury, J.E. (2008) The thermodynamics of protein-ligand interaction and salvation: insights for ligand design. J. Mol. Biol. 384, 1002–1017.

    Google Scholar 

  11. Freire, E. (2008) Do enthalpy and entropy distinguish first-in-class from best-in-class? Drug Disc. Today 13, 869–874.

    Google Scholar 

  12. Copeland, R.A., Pompliano, D.L, and Meek, T.D. (2006) Drug-target residence time and its implications for lead optimization. Nat. Rev Drug Disc. 5, 730–739.

    Google Scholar 

  13. LoRusso, P.M., and Eder, J.P. (2008) Therapeutic potential of novel selective-spectrum kinase inhibitors in oncology. Expert Opin. Invest. Drugs 17, 1013–1028.

    Google Scholar 

  14. Lipinski, C.A., Lombardo, F., Dominy, B.W., and Feeney, P.J. (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25.

    Google Scholar 

  15. van de Waterbeemd, H., Smith D.A., Beaumont K., and Walker D.K. (2001) Property-based design: Optimization of drug absorption and pharmacokinetics. J. Med. Chem. 44, 1313–1333.

    Google Scholar 

  16. Pajouhesh, H., and Lenz, G.R. (2005) Medicinal chemical properties of successful central nervous system drugs. NeuroRx 2, 541–553.

    Google Scholar 

  17. Waring, M.J. (2009) Defining optimum lipophilicity and molecular weight ranges for drug candidates – Molecular weight dependent lower logD limits based on permeability. Bioorg. Med. Chem. Lett. 19, 2844–2851.

    Google Scholar 

  18. Ritchie, T.J., and Macdonald, S.J.F. (2009) The impact of aromatic ring count on compound developability – Are too many aromatic rings a liability in drug design? Drug Discovery Today 14, 1011–1020.

    Google Scholar 

  19. Kerns, E.H., and Di, L. (2008) Drug-like properties: Concepts, structure, design and methods, from ADME to toxicity optimization. ISBN 978-0-1236-9520-8, Academic Press, Burlington, MA 01803, USA, pp64.

    Google Scholar 

  20. Lipinski, C.A. (2000) Drug-like properties and the cause of poor solubility and poor permeability. J. Pharmacol. Toxicol. Methods 44, 235–249.

    Google Scholar 

  21. Smith, D.A., van de Waterbeemd, H., and Walker, D.K. (2001) Pharmacokinetics and metabolism in drug design. ISBN 3-527-30197-6, Wiley-VCH Verlag GmbH, Weinheim, Germany, pp 99–122.

    Google Scholar 

  22. Williams, D.P., and Park B.K. (2003) Idiosyncratic toxicity: The role of toxicophores and bioactivation. Drug Discovery Today 8, 1044–1050.

    Google Scholar 

  23. Waring, M.J. (2010) Lipophilicity in drug discovery. Expert Opin. Drug Discov. 5, 235–248.

    Google Scholar 

  24. Ploemen, J.P., Kelder, J., Hafmans, T., van de Sandt, H., van Burgsteden J.A., Saleminki P.J., and van Esch E. (2004) Use of physicochemical calculation of pKa and CLogP to predict phospholipidosis-inducing potential: a case study with structurally related piperazines. Exp Toxicol Pathol. 55, 347–55.

    Google Scholar 

  25. Wiseman, T., Williston, S., Brandts, J.F., and Lin, L.N. (1989) Rapid measurement of binding constants and heats of binding using a new titration calorimeter. Anal Biochem. 179, 131–137.

    Google Scholar 

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Correspondence to Ming-Qiang Zhang .

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Zhang, MQ. (2012). Working with Small Molecules: Rules-of-Thumb of “Drug Likeness”. In: Drewes, G., Bantscheff, M. (eds) Chemical Proteomics. Methods in Molecular Biology, vol 803. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-364-6_20

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  • DOI: https://doi.org/10.1007/978-1-61779-364-6_20

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-363-9

  • Online ISBN: 978-1-61779-364-6

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