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  • Review Article
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Mechanistic enzymology in drug discovery: a fresh perspective

An Erratum to this article was published on 15 December 2017

This article has been updated

Key Points

  • The application of detailed mechanistic enzyme kinetics is vital for the characterization of enzyme targets; furthermore, it is crucial to aid in the design and prosecution of assays to effectively profile compound properties and to gain insight into the mechanism of action required for drug efficacy.

  • Enzyme assays are used extensively in hit identification and hit validation and for detailed characterization of the compound mechanism to guide lead optimization.

  • It is important to understand the limitation of IC50 values and to more deeply probe the relationship between the molecular structures of hits and leads and their kinetics of binding, inhibition and mechanism of action.

  • Combining information from enzyme kinetic studies with that derived from biophysical methods can be advantageous in assessing protein quality, generating suitable assays to identify a range of desired mechanisms and to complement detailed mechanistic characterization.

  • The efficient use of these methods enables the identification, prioritization and progression of truly differentiated compound series that have an enhanced probability of success in translation through to the clinic as a consequence of detailed understanding of their mechanism.

Abstract

Given the therapeutic and commercial success of small-molecule enzyme inhibitors, as exemplified by kinase inhibitors in oncology, a major focus of current drug-discovery and development efforts is on enzyme targets. Understanding the course of an enzyme-catalysed reaction can help to conceptualize different types of inhibitor and to inform the design of screens to identify desired mechanisms. Exploiting this information allows the thorough evaluation of diverse compounds, providing the knowledge required to efficiently optimize leads towards differentiated candidate drugs. This review highlights the rationale for conducting high-quality mechanistic enzymology studies and considers the added value in combining such studies with orthogonal biophysical methods.

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Figure 1: The kinetics of drug–target interactions.
Figure 2: Translating IC50 into reality.
Figure 3: Mechanisms of slow-binding inhibition.

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Change history

  • 15 December 2017

    In the affiliations of this article, the address provided for Discovery Sciences, IMED Biotech Unit, AstraZeneca was incorrect and should be Building 310, Cambridge Science Park, Milton Road, Cambridge CB4 0WG, UK. The article has been corrected in the print and online version.

References

  1. Imming, P., Sinning, C. & Meyer, A. Drugs, their targets and the nature and number of drug targets. Nat. Rev. Drug Discov. 5, 821–834 (2006).

    Article  CAS  PubMed  Google Scholar 

  2. Hopkins, A. L. & Groom, C. R. The druggable genome. Nat. Rev. Drug Discov. 1, 727–730 (2002).

    Article  CAS  PubMed  Google Scholar 

  3. Skeggs, L. T., Kahn, J. R. & Shumway, N. P. The preparation and function of the hypertensin-converting enzyme. J. Exp. Med. 103, 295–299 (1956).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ondetti, M. A., Rubin, B. & Cushman, D. W. Design of specific inhibitors of angiotensin-converting enzyme: new class of orally active antihypertensive agents. Science 196, 441–444 (1977).

    Article  CAS  PubMed  Google Scholar 

  5. Cushman, D. W., Cheung, H., Sabo, E. & Ondetti, M. Design of potent competitive inhibitors of angiotensin-converting enzyme. Carboxyalkanoyl and mercapto-alkanoyl amino acids. Biochemistry 16, 5484–5491 (1977).

    Article  CAS  PubMed  Google Scholar 

  6. Patchett, A. A. et al. A new class of angiotensin-converting enzyme inhibitors. Nature 288, 280–283 (1980).

    Article  CAS  PubMed  Google Scholar 

  7. Roth, B. D. The discovery and development of atorvastatin, a potent novel hypolipidemic agent. Progress Med. Chem. 40, 1–22 (2002).

    Article  CAS  Google Scholar 

  8. Alberts, A. et al. Mevinolin: a highly potent competitive inhibitor of hydroxymethylglutaryl-coenzyme A reductase and a cholesterol-lowering agent. Proc. Natl Acad. Sci. USA 77, 3957–3961 (1980).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Nakamura, C. E. & Abeles, R. H. Mode of interaction of β-hydroxy-β-methylglutaryl coenzyme A reductase with strong binding inhibitors: compactin and related compounds. Biochemistry 24, 1364–1376 (1985).

    Article  CAS  PubMed  Google Scholar 

  10. Roberts, N. A. et al. Rational design of peptide-based HIV proteinase inhibitors. Science 248, 358–362 (1990).

    Article  CAS  PubMed  Google Scholar 

  11. Vacca, J. et al. L-735,524: an orally bioavailable human immunodeficiency virus type 1 protease inhibitor. Proc. Natl Acad. Sci. USA 91, 4096–4100 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Meek, T. D. Inhibitors of HIV-1 protease. J. Enzyme Inhib. 6, 65–98 (1992).

    Article  CAS  PubMed  Google Scholar 

  13. Robertson, J. G. Mechanistic basis of enzyme-targeted drugs. Biochemistry 44, 5561–5571 (2005).

    Article  CAS  PubMed  Google Scholar 

  14. Patel, M. P. et al. Kinetic and chemical mechanisms of the fabG-encoded Streptococcus pneumoniae β-ketoacyl-ACP reductase. Biochemistry 44, 16753–16765 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Dryer, G. et al. Hydroxyethylene isostere inhibitors of HIV-1 protease structure-activity analysis using enzyme kinetics, X-ray crystallography, and infected T-cell assays. Biochemistry 31, 6646–6659 (1992).

    Article  Google Scholar 

  16. Schramm, V. L. Transition states, analogues, and drug development. ACS Chem. Biol. 8, 71–81 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Schramm, V. L. Transition states and transition state analogue interactions with enzymes. Accounts Chem. Res. 48, 1032–1039 (2015).

    Article  CAS  Google Scholar 

  18. Pham, T. V. et al. Mechanism-based inactivator of isocitrate lyases 1 and 2 from Mycobacterium tuberculosis. Proc. Natl Acad. Sci. USA 114, 7617–7622 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. De Cesco, S., Kurian, J., Dufresne, C., Mittermaier, A. & Moitessier, N. Covalent inhibitors design and discovery. Eur. J. Med. Chem. 138, 96–114 (2017).

    Article  CAS  PubMed  Google Scholar 

  20. Radzicka, A. & Wolfenden, R. Transition state and multisubstrate analog inhibitors. Methods Enzymol. 249, 284–312 (1995).

    Article  CAS  PubMed  Google Scholar 

  21. Byers, L. D. & Wolfenden, R. Binding of the by-product analog benzylsuccinic acid by carboxypeptidase A. Biochemistry 12, 2070–2078 (1973).

    Article  CAS  PubMed  Google Scholar 

  22. Copeland, R. A., Pompliano, D. L. & Meek, T. D. Drug-target residence time and its implications for lead optimization. Nat. Rev. Drug Discov. 5, 730–739 (2006). This seminal paper introduces an alternative approach to drug optimization, focusing on drug–target residence time rather than the optimization of thermodynamic affinity alone.

    Article  CAS  PubMed  Google Scholar 

  23. Overington, J. P., Al-Lazikani, B. & Hopkins, A. L. How many drug targets are there? Nat. Rev. Drug Discov. 5, 993–996 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Smith, G. F. 1-Medicinal chemistry by the numbers: the physicochemistry, thermodynamics and kinetics of modern drug design. Progress Med. Chem. 48, 1–29 (2009).

    Article  CAS  Google Scholar 

  25. Sachsenmaier, C. & Schachtele, C. Integrated technology platform protein kinases for drug development in oncology. Biotechniques 33, S101–S106 (2002).

    Article  Google Scholar 

  26. Lindsley, C. W. et al. Allosteric Akt (PKB) inhibitors: discovery and SAR of isozyme selective inhibitors. Bioorg. Med. Chem. Lett. 15, 761–764 (2005).

    Article  CAS  PubMed  Google Scholar 

  27. Barnett, S. F. et al. Identification and characterization of pleckstrin-homology-domain-dependent and isoenzyme-specific Akt inhibitors. Biochem. J. 385, 399–408 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Joseph, R. E., Min, L. & Andreotti, A. H. The linker between SH2 and kinase domains positively regulates catalysis of the Tec family kinases. Biochemistry 46, 5455–5462 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Hays, J. L. & Watowich, S. J. Oligomerization-induced modulation of TPR-MET tyrosine kinase activity. J. Biol. Chem. 278, 27456–27463 (2003).

    Article  CAS  PubMed  Google Scholar 

  30. Timofeevski, S. L. et al. Enzymatic characterization of c-Met receptor tyrosine kinase oncogenic mutants and kinetic studies with aminopyridine and triazolopyrazine inhibitors. Biochemistry 48, 5339–5349 (2009).

    Article  CAS  PubMed  Google Scholar 

  31. Favata, M. F. et al. Identification of a novel inhibitor of mitogen-activated protein kinase kinase. J. Biol. Chem. 273, 18623–18632 (1998).

    Article  CAS  PubMed  Google Scholar 

  32. Solowiej, J. et al. Characterizing the effects of the juxtamembrane domain on vascular endothelial growth factor receptor-2 enzymatic activity, autophosphorylation, and inhibition by axitinib. Biochemistry 48, 7019–7031 (2009).

    Article  CAS  PubMed  Google Scholar 

  33. Kopcho, L. M. et al. Comparative studies of active site-ligand interactions among various recombinant constructs of human β-amyloid precursor protein cleaving enzyme. Arch. Biochem. Biophys. 410, 307–316 (2003).

    Article  CAS  PubMed  Google Scholar 

  34. Stevenson, L. M., Deal, M. S., Hagopian, J. C. & Lew, J. Activation mechanism of CDK2: role of cyclin binding versus phosphorylation. Biochemistry 41, 8528–8534 (2002).

    Article  CAS  PubMed  Google Scholar 

  35. Anderson, K. et al. Binding of TPX2 to Aurora A alters substrate and inhibitor interactions. Biochemistry 46, 10287–10295 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Kuzmichev, A., Nishioka, K., Erdjument-Bromage, H., Tempst, P. & Reinberg, D. Histone methyltransferase activity associated with a human multiprotein complex containing the Enhancer of Zeste protein. Genes Dev. 16, 2893–2905 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dang, L. et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 462, 739–744 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Smits, A. H., Jansen, P. W., Poser, I., Hyman, A. A. & Vermeulen, M. Stoichiometry of chromatin-associated protein complexes revealed by label-free quantitative mass spectrometry-based proteomics. Nucleic Acids Res. 41, e28 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Krishnaswamy, S. & Betz, A. Exosites determine macromolecular substrate recognition by prothrombinase. Biochemistry 36, 12080–12086 (1997).

    Article  CAS  PubMed  Google Scholar 

  40. Harpel, M. R. et al. Mutagenesis and mechanism-based inhibition of Streptococcus pyogenes Glu-tRNAGln amidotransferase implicate a serine-based glutaminase site. Biochemistry 41, 6398–6407 (2002).

    Article  CAS  PubMed  Google Scholar 

  41. Szafranska, A. E. & Dalby, K. N. Kinetic mechanism for p38 MAP kinase α. A partial rapid-equilibrium random-order ternary-complex mechanism for the phosphorylation of a protein substrate. FEBS J. 272, 4631–4645 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. LoGrasso, P. V. et al. Kinetic mechanism for p38 MAP kinase. Biochemistry 36, 10422–10427 (1997).

    Article  CAS  PubMed  Google Scholar 

  43. Chen, G., Porter, M. D., Bristol, J. R., Fitzgibbon, M. J. & Pazhanisamy, S. Kinetic mechanism of the p38-α MAP kinase: phosphoryl transfer to synthetic peptides. Biochemistry 39, 2079–2087 (2000).

    Article  CAS  PubMed  Google Scholar 

  44. Gao, X. & Harris, T. K. Steady-state kinetic mechanism of PDK1. J. Biol. Chem. 281, 21670–21681 (2006).

    Article  CAS  PubMed  Google Scholar 

  45. Keshwani, M. M., Gao, X. & Harris, T. K. Mechanism of PDK1-catalyzed Thr-229 phosphorylation of the S6K1 protein kinase. J. Biol. Chem. 284, 22611–22624 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Davidson, W. et al. Discovery and characterization of a substrate selective p38α inhibitor. Biochemistry 43, 11658–11671 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Pargellis, C. et al. Inhibition of p38 MAP kinase by utilizing a novel allosteric binding site. Nat. Struct. Mol. Biol. 9, 268 (2002).

    Article  CAS  Google Scholar 

  48. Li, Y. et al. The target of the NSD family of histone lysine methyltransferases depends on the nature of the substrate. J. Biol. Chem. 284, 34283–34295 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Poulin, M. B. et al. Transition state for the NSD2-catalyzed methylation of histone H3 lysine 36. Proc. Natl Acad. Sci. 113, 1197–1201 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Bar-Even, A. et al. The moderately efficient enzyme: evolutionary and physicochemical trends shaping enzyme parameters. Biochemistry 50, 4402–4410 (2011).

    Article  CAS  PubMed  Google Scholar 

  51. Garuti, L., Roberti, M. & Bottegoni, G. Non-ATP competitive protein kinase inhibitors. Curr. Med. Chem. 17, 2804–2821 (2010).

    Article  CAS  PubMed  Google Scholar 

  52. Cornish-Bowden, A. Why is uncompetitive inhibition so rare?: A possible explanation, with implications for the design of drugs and pesticides. FEBS Lett. 203, 3–6 (1986). This paper provides insight into why uncompetitive inhibition is rarely encountered and suggests that it is a useful approach, as these inhibitors may have greater pharmacological effects.

    Article  CAS  PubMed  Google Scholar 

  53. Hedstrom, L. IMP dehydrogenase: structure, mechanism, and inhibition. Chem. Rev. 109, 2903–2928 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Ward, W. H. et al. Kinetic and structural characteristics of the inhibition of enoyl (acyl carrier protein) reductase by triclosan. Biochemistry 38, 12514–12525 (1999).

    Article  CAS  PubMed  Google Scholar 

  55. Swinney, D. C. Biochemical mechanisms of drug action: what does it take for success? Nat. Rev. Drug Discov. 3, 801–808 (2004).

    Article  CAS  PubMed  Google Scholar 

  56. Dahl, G. & Akerud, T. Pharmacokinetics and the drug-target residence time concept. Drug Discov. Today 18, 697–707 (2013). This paper demonstrates that the extension of binding due to a long drug–target residence time occurs only when the binding dissociation rate is slower than the PK elimination rate. Exemplary data for many drugs and/or drug candidates indicate that the opposite scenario is commonly observed.

    Article  CAS  PubMed  Google Scholar 

  57. Walkup, G. K. et al. Translating slow-binding inhibition kinetics into cellular and in vivo effects. Nat. Chem. Biol. 11, 416–423 (2015). This paper describes a mechanistic pharmacodynamic model that includes drug–target kinetic parameters. It has been applied to predict dose–response curves for inhibitors in an animal model of infection.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Johnson, D. S., Weerapana, E. & Cravatt, B. F. Strategies for discovering and derisking covalent, irreversible enzyme inhibitors. Future Med. Chem. 2, 949–964 (2010).

    Article  CAS  PubMed  Google Scholar 

  59. Copeland, R. A. Mechanistic considerations in high-throughput screening. Anal. Biochem. 320, 1–12 (2003). This paper describes the steps required to design the best hit-finding assay possible, taking into account the requirements for a successful screening campaign and also post-screening lead evaluation.

    Article  CAS  PubMed  Google Scholar 

  60. Segal, I. H. Enzyme Kinetics: Behavior and Analysis of Rapid Equilibrium and Steady-State Enzyme Systems (Wiley, 1975). This book is an essential text for any academic or industrial enzymologist, as it provides a comprehensive introduction to enzyme kinetics.

    Google Scholar 

  61. Schneck, J. L. et al. Chemical mechanism of a cysteine protease, cathepsin C, as revealed by integration of both steady-state and pre-steady-state solvent kinetic isotope effects. Biochemistry 47, 8697–8710 (2008).

    Article  CAS  PubMed  Google Scholar 

  62. Noble, M. et al. The kinetic model of the shikimate pathway as a tool to optimize enzyme assays for high-throughput screening. Biotechnol. Bioeng. 95, 560–573 (2006).

    Article  CAS  PubMed  Google Scholar 

  63. Schneck, J. L. et al. Kinetic mechanism and rate-limiting steps of focal adhesion kinase-1. Biochemistry 49, 7151–7163 (2010).

    Article  CAS  PubMed  Google Scholar 

  64. Teague, S. J. Implications of protein flexibility for drug discovery. Nat. Rev. Drug Discov. 2, 527–541 (2003).

    Article  CAS  PubMed  Google Scholar 

  65. Thorne, N., Auld, D. S. & Inglese, J. Apparent activity in high-throughput screening: origins of compound-dependent assay interference. Curr. Opin. Chem. Biol. 14, 315–324 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hermann, J. C. et al. Metal impurities cause false positives in high-throughput screening campaigns. ACS Med. Chem. Lett. 4, 197–200 (2013).

    Article  CAS  PubMed  Google Scholar 

  67. Di, L. & Kerns, E. H. Biological assay challenges from compound solubility: strategies for bioassay optimization. Drug Discov. Today 11, 446–451 (2006).

    Article  CAS  PubMed  Google Scholar 

  68. McGovern, S. L., Helfand, B. T., Feng, B. & Shoichet, B. K. A specific mechanism of nonspecific inhibition. J. Med. Chem. 46, 4265–4272 (2003). This paper shows that aggregates formed by promiscuous compounds can reversibly sequester enzymes, resulting in apparent inhibition. It presents post-screening approaches for detecting and avoiding such compounds.

    Article  CAS  PubMed  Google Scholar 

  69. Johnston, P. A. Redox cycling compounds generate H2O2 in HTS buffers containing strong reducing reagents — real hits or promiscuous artifacts? Curr. Opin. Chem. Biol. 15, 174–182 (2011).

    Article  CAS  PubMed  Google Scholar 

  70. Dahlin, J. L., Baell, J. & Walters, M. A. in Assay Guidance Manual (eds Sittampalam, G. S. et al.) (2004).

    Google Scholar 

  71. McGovern, S. L. & Shoichet, B. K. Kinase inhibitors: not just for kinases anymore. J. Med. Chem. 46, 1478–1483 (2003).

    Article  CAS  PubMed  Google Scholar 

  72. Baell, J. B. & Holloway, G. A. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J. Med. Chem. 53, 2719–2740 (2010).

    Article  CAS  PubMed  Google Scholar 

  73. Baell, J. & Walters, M. A. Chemical con artists foil drug discovery. Nature 513, 481 (2014).

    Article  CAS  PubMed  Google Scholar 

  74. Nissink, J. W. M. & Blackburn, S. Quantification of frequent-hitter behavior based on historical high-throughput screening data. Future Med. Chem. 6, 1113–1126 (2014).

    Article  CAS  Google Scholar 

  75. Saubern, S., Guha, R. & Baell, J. B. KNIME workflow to assess PAINS filters in SMARTS format. Comparison of RDKit and Indigo cheminformatics libraries. Mol. Informat. 30, 847–850 (2011).

    Article  CAS  Google Scholar 

  76. Shoichet, B. K. Interpreting steep dose-response curves in early inhibitor discovery. J. Med. Chem. 49, 7274–7277 (2006).

    Article  CAS  PubMed  Google Scholar 

  77. Shoichet, B. K. Screening in a spirit haunted world. Drug Discov. Today 11, 607–615 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Selwyn, M. J. A simple test for inactivation of an enzyme during assay. Biochim. Biophys. Acta 105, 193–195 (1965).

    Article  CAS  PubMed  Google Scholar 

  79. Copeland, R. A. in Enzymes: A Practical Introduction to Structure, Mechanism, and Data Analysis 2nd edn (ed. Copeland, R. A. ) 266–304 (Wiley, 2002).

    Google Scholar 

  80. Singh, J., Petter, R. C., Baillie, T. A. & Whitty, A. The resurgence of covalent drugs. Nat. Rev. Drug Discov. 10, 307–317 (2011).

    Article  CAS  PubMed  Google Scholar 

  81. Rawat, R., Whitty, A. & Tonge, P. J. The isoniazid-NAD adduct is a slow, tight-binding inhibitor of InhA, the Mycobacterium tuberculosis enoyl reductase: adduct affinity and drug resistance. Proc. Natl Acad. Sci. USA 100, 13881–13886 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Garvey, E. P. et al. Potent inhibitors of HIV-1 integrase display a two-step, slow-binding inhibition mechanism which is absent in a drug-resistant T66I/M154I mutant. Biochemistry 48, 1644–1653 (2009).

    Article  CAS  PubMed  Google Scholar 

  83. Rudolph, J., Xiao, Y., Pardi, A. & Ahn, N. G. Slow inhibition and conformation selective properties of extracellular signal-regulated kinase 1 and 2 inhibitors. Biochemistry 54, 22–31 (2014).

    Article  CAS  PubMed  Google Scholar 

  84. Sculley, M. J., Morrison, J. F. & Cleland, W. W. Slow-binding inhibition: the general case. Biochim. Biophys. Acta 1298, 78–86 (1996).

    Article  PubMed  Google Scholar 

  85. Morrison, J. F. & Walsh, C. T. The behavior and significance of slow-binding enzyme inhibitors. Adv. Enzymol. Relat. Areas Mol. Biol. 61, 201–301 (1988). This article describes the detection and analysis of slow-binding inhibition.

    CAS  PubMed  Google Scholar 

  86. Copeland, R. A., Basavapathruni, A., Moyer, M. & Scott, M. P. Impact of enzyme concentration and residence time on apparent activity recovery in jump dilution analysis. Anal. Biochem. 416, 206–210 (2011).

    Article  CAS  PubMed  Google Scholar 

  87. Copeland, R. A., Lombardo, D., Giannaras, J. & Decicco, C. P. Estimating KI values for tight binding inhibitors from dose-response plots. Bioorg. Med. Chem. Lett. 5, 1947–1952 (1995).

    Article  CAS  Google Scholar 

  88. Goldstein, A. The mechanism of enzyme-inhibitor-substrate reactions: illustrated by the cholinesterase-physostigmine-acetylcholine system. J. Gen. Physiol. 27, 529–580 (1944).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Morrison, J. F. Kinetics of the reversible inhibition of enzyme-catalysed reactions by tight-binding inhibitors. Biochim. Biophys. Acta 185, 269–286 (1969). This paper highlights the challenges associated with the determination of inhibition constants for tight-binding inhibitors and presents the theory behind the analysis.

    Article  CAS  PubMed  Google Scholar 

  90. Murphy, D. J. Determination of accurate KI values for tight-binding enzyme inhibitors: an in silico study of experimental error and assay design. Anal. Biochem. 327, 61–67 (2004).

    Article  CAS  PubMed  Google Scholar 

  91. Copeland, R. A., Harpel, M. R. & Tummino, P. J. Targeting enzyme inhibitors in drug discovery. Expert Opin. Ther. Targets 11, 967–978 (2007).

    Article  CAS  PubMed  Google Scholar 

  92. Bauer, R. A. Covalent inhibitors in drug discovery: from accidental discoveries to avoided liabilities and designed therapies. Drug Discov. Today 20, 1061–1073 (2015).

    Article  CAS  PubMed  Google Scholar 

  93. Strelow, J. M. A. Perspective on the kinetics of covalent and irreversible inhibition. SLAS Discov. 22, 3–20 (2017). This paper provides a detailed explanation of the characterization of irreversible inhibition.

    CAS  PubMed  Google Scholar 

  94. Krippendorff, B. F., Neuhaus, R., Lienau, P., Reichel, A. & Huisinga, W. Mechanism-based inhibition: deriving KI and kinact directly from time-dependent IC50 values. J. Biomol. Screen 14, 913–923 (2009).

    Article  CAS  PubMed  Google Scholar 

  95. Jo¨st, C., Nitsche, C., Scholz, T., Roux, L. & Klein, C. D. Promiscuity and selectivity in covalent enzyme inhibition: a systematic study of electrophilic fragments. J. Med. Chem. 57, 7590–7599 (2014).

    Article  CAS  Google Scholar 

  96. Lanning, B. R. et al. A road map to evaluate the proteome-wide selectivity of covalent kinase inhibitors. Nat. Chem. Biol. 10, 760–767 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Schwartz, P. A. et al. Covalent EGFR inhibitor analysis reveals importance of reversible interactions to potency and mechanisms of drug resistance. Proc. Natl Acad. Sci. USA 111, 173–178 (2014).

    Article  CAS  PubMed  Google Scholar 

  98. Ring, B., Wrighton, S. A. & Mohutsky, M. in Enzyme Kinetics in Drug Metabolism: Fundamentals and Applications (eds Nagar, S., Argikar, U. & Tweedie, D.) 37–56 (Springer, 2014).

    Book  Google Scholar 

  99. Fleming, M. A. et al. Inhibition of IMPDH by mycophenolic acid: dissection of forward and reverse pathways using capillary electrophoresis. Biochemistry 35, 6990–6997 (1996).

    Article  CAS  PubMed  Google Scholar 

  100. Hedstrom, L. & Wang, C. C. Mycophenolic acid and thiazole adenine dinucleotide inhibition of Tritrichomonas foetus inosine 5′-monophosphate dehydrogenase: implications on enzyme mechanism. Biochemistry 29, 849–854 (1990).

    Article  CAS  PubMed  Google Scholar 

  101. Copeland, R. A. Evaluation of Enzyme Inhibitors in Drug Discovery: A Guide for Medicinal Chemists and Pharmacologists (John Wiley & Sons, 2013).

    Book  Google Scholar 

  102. Munson, P. J. & Rodbard, D. An exact correction to the “Cheng-Prusoff” correction. J. Recept. Res. 8, 533–546 (1988). This paper describes the effect of the concentration of labelled drug and the concentration of the binding site on the measured ED 50 and hence K i values, as well as provides an explicit correction to overcome these issues.

    Article  CAS  PubMed  Google Scholar 

  103. Cheng, H. C. The influence of cooperativity on the determination of dissociation constants: examination of the Cheng-Prusoff equation, the Scatchard analysis, the Schild analysis and related power equations. Pharmacol. Res. 50, 21–40 (2004).

    Article  CAS  PubMed  Google Scholar 

  104. Johnson, K. A. A century of enzyme kinetic analysis, 1913 to 2013. FEBS Lett. 587, 2753–2766 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Cornish-Bowden, A. Analysis and interpretation of enzyme kinetic data. Persp. Sci. 1, 121–125 (2014).

    Google Scholar 

  106. Renaud, J. P. et al. Biophysics in drug discovery: impact, challenges and opportunities. Nat. Rev. Drug Discov. 15, 679–698 (2016).

    Article  CAS  PubMed  Google Scholar 

  107. Holdgate, G. et al. in Protein-Ligand Interactions: Methods and Applications (eds Williams, M. & Daviter, T.) 327–355 (Springer, 2013).

    Book  Google Scholar 

  108. Olson, B. J. & Markwell, J. UNIT 3.4: Assays for determination of protein concentration. Curr. Protoc. Protein Sci. http://dx.doi.org/10.1002/0471140864.ps0304s48 (2007).

  109. Dunn, B. UNIT 3.2: Quantitative amino acid analysis. Curr. Protoc. Protein Sci. http://dx.doi.org/10.1002/0471140864.ps0302s00 (2001).

  110. Holdgate, G. A., Anderson, M., Edfeldt, F. & Geschwindner, S. Affinity-based, biophysical methods to detect and analyze ligand binding to recombinant proteins: matching high information content with high throughput. J. Struct. Biol. 172, 142–157 (2010).

    Article  CAS  PubMed  Google Scholar 

  111. Prinz, F., Schlange, T. & Asadullah, K. Believe it or not: how much can we rely on published data on potential drug targets? Nat. Rev. Drug Discov. 10, 712 (2011).

    Article  CAS  PubMed  Google Scholar 

  112. Frye, S. V. et al. Tackling reproducibility in academic preclinical drug discovery. Nat. Rev. Drug Discov. 14, 733–734 (2015).

    Article  CAS  PubMed  Google Scholar 

  113. Mullane, K. & Williams, M. Unknown unknowns in biomedical research: does an inability to deal with ambiguity contribute to issues of irreproducibility? Biochem. Pharmacol. 97, 133–136 (2015).

    Article  CAS  PubMed  Google Scholar 

  114. Edfeldt, F. N., Folmer, R. H. & Breeze, A. L. Fragment screening to predict druggability (ligandability) and lead discovery success. Drug Discov. Today 16, 284–287 (2011).

    Article  CAS  PubMed  Google Scholar 

  115. Folmer, R. H. Integrating biophysics with HTS-driven drug discovery projects. Drug Discov. Today 21, 491–498 (2016).

    Article  CAS  PubMed  Google Scholar 

  116. Kaeberlein, M. et al. Substrate-specific activation of sirtuins by resveratrol. J. Biol. Chem. 280, 17038–17045 (2005).

    Article  CAS  PubMed  Google Scholar 

  117. Borra, M. T., Smith, B. C. & Denu, J. M. Mechanism of human SIRT1 activation by resveratrol. J. Biol. Chem. 280, 17187–17195 (2005).

    Article  CAS  PubMed  Google Scholar 

  118. Kalliokoski, T., Kramer, C., Vulpetti, A. & Gedeck, P. Comparability of mixed IC50 data – a statistical analysis. PloS ONE 8, e61007 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Hall, J. et al. Biophysical and mechanistic insights into novel allosteric inhibitor of spleen tyrosine kinase. J. Biol. Chem. 287, 7717–7727 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Foda, Z. H., Shan, Y., Kim, E. T., Shaw, D. E. & Seeliger, M. A. A dynamically coupled allosteric network underlies binding cooperativity in Src kinase. Nat. Commun. 6, 5939 (2015).

    Article  CAS  PubMed  Google Scholar 

  121. Brown, A. J. XXXVI.—Enzyme action. J. Chem. Soc., Trans. 81, 373–388 (1902).

    Article  CAS  Google Scholar 

  122. Michaelis, L. & Menten, M. L. Die kinetik der invertinwirkung. Biochem. Z. 49, 333–369 (1913).

    CAS  Google Scholar 

  123. Ehrlich, P. Address in pathology on chemiotherapy: delivered before the Seventeenth International Congress of Medicine. Br. Med. J. 2, 353–359 (1913).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Cook, D. et al. Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat. Rev. Drug Discov. 13, 419–431 (2014).

    Article  CAS  PubMed  Google Scholar 

  125. Mezzasalma, T. M. et al. Enhancing recombinant protein quality and yield by protein stability profiling. J. Biomol. Screen 12, 418–428 (2007).

    Article  CAS  PubMed  Google Scholar 

  126. Hajduk, P. J. et al. A strategy for high-throughput assay development using leads derived from nuclear magnetic resonance-based screening. J. Biomol. Screen 7, 429–432 (2002).

    Article  CAS  PubMed  Google Scholar 

  127. Hajduk, P. J. & Burns, D. J. Integration of NMR and high-throughput screening. Comb. Chem. High Throughput Screen 5, 613–621 (2002).

    Article  CAS  PubMed  Google Scholar 

  128. Genick, C. C. et al. Applications of biophysics in high-throughput screening hit validation. J. Biomol. Screen 19, 707–714 (2014).

    Article  CAS  PubMed  Google Scholar 

  129. Evenas, J. et al. HTS followed by NMR based counterscreening. Discovery and optimization of pyrimidones as reversible and competitive inhibitors of xanthine oxidase. Bioorg. Med. Chem. Lett. 24, 1315–1321 (2014).

    Article  CAS  PubMed  Google Scholar 

  130. Ciulli, A. Biophysical screening for the discovery of small-molecule ligands. Methods Mol. Biol. 1008, 357–388 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Geschwindner, S. in Lead Generation: Methods and Strategies Ch. 14 (ed. Holenz, J. ) (Wiley, 2016).

    Google Scholar 

  132. Bergsdorf, C. & Ottl, J. Affinity-based screening techniques: their impact and benefit to increase the number of high quality leads. Expert Opin. Drug Discov. 5, 1095–1107 (2010).

    Article  PubMed  Google Scholar 

  133. Huber, W. A new strategy for improved secondary screening and lead optimization using high-resolution SPR characterization of compound-target interactions. J. Mol. Recognit. 18, 273–281 (2005).

    Article  CAS  PubMed  Google Scholar 

  134. Barsyte-Lovejoy, D. et al. (R)-PFI-2 is a potent and selective inhibitor of SETD7 methyltransferase activity in cells. Proc. Natl Acad. Sci. USA 111, 12853–12858 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Davis, M. I. et al. Biochemical, cellular, and biophysical characterization of a potent inhibitor of mutant isocitrate dehydrogenase IDH1. J. Biol. Chem. 289, 13717–13725 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors would like to thank S. Thrall for critical input into Fig. 1.

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Correspondence to Geoffrey A. Holdgate.

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G.H. and R.G. are current employees of AstraZeneca. T.M. is a former employee of GSK.

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Glossary

Mechanism

A process by which a reaction takes place, fully determined when all the intermediates, complexes and conformational states of an enzyme are characterized and the rate constants associated with the conversion between them are quantified. The term is often used in inhibition studies to distinguish between different modes of inhibition.

Half-maximal inhibitory concentration

(IC50). The inhibitor concentration that gives a 50% decrease in rate under the specific assay conditions employed.

Random-order mechanism

A reaction mechanism in which either of the two substrates may bind to the enzyme first to form a binary complex, followed by the other to form a ternary complex.

Non-competitive inhibitors

Inhibitors that bind with equal affinity both before and after the varied substrate.

Uncompetitive inhibitors

Inhibitors that bind only after the substrate.

Slow-binding inhibition

An inhibition that occurs slowly on the timescale of the assay as the enzyme–inhibitor complex concentration increases to its steady-state level.

Competitive inhibition

A type of inhibition where the inhibitor binds only before the varied substrate (see also non-competitive and uncompetitive inhibition).

Reversible inhibition

An inhibition that can be reversed on the timescale of the assay by competition or dilution. Reversible inhibitors are not precluded from forming covalent bonds with the enzyme.

Irreversible inhibition

An inhibition that cannot be reversed on the timescale of the assay. Truly irreversible inhibitors never dissociate from the enzyme and are characterized by an inactivation rate constant, not a dissociation constant. Irreversible inhibitors do not necessarily have to be covalently bound.

Tight-binding inhibition

A type of inhibition occurring under conditions when the concentration of inhibitor required to cause inhibition is similar to the enzyme concentration, leading to depletion of the free inhibitor concentration. This results in breakdown of the usual assumptions leading to simple inhibition kinetics and requires a more complex rate equation.

Mixed inhibition

A type of inhibition in which the inhibitor binds both before and after the varied substrate.

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Holdgate, G., Meek, T. & Grimley, R. Mechanistic enzymology in drug discovery: a fresh perspective. Nat Rev Drug Discov 17, 115–132 (2018). https://doi.org/10.1038/nrd.2017.219

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