Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Biophysics in drug discovery: impact, challenges and opportunities

Nature Reviews Drug Discovery volume 15, pages 679–698 (2016)Cite this article

Subjects

Key Points

  • The rapid development of sensitive biophysical methods is transforming drug discovery by providing early profiling of compound properties and insights into mechanisms of action.

  • Biophysical methods are used extensively in hit finding (fragment-based screening and high-throughput screening), hit validation, in depth characterization of compound binding and lead optimization.

  • A growing application of biophysical methods is to understand the relationship between the kinetics of binding, mode of action, and molecular structures and interactions. This has had substantial impact on recognizing the importance of binding kinetics and residence time for therapeutic action.

  • Additional information derived from biophysical methods ranges from protein quality control, quantitative binding data, and determination of ligand–target complex structures to complex mode-of-action studies.

  • The efficient use of these methods requires experience in experimental design and data analysis, and a strategic combination of orthogonal methods.

  • Newly emerging technologies such as cryo-electron microscropy (cryo-EM) for high-resolution determination of massive biological structures and more rapid methods for the characterization of binding kinetics and thermodynamics will further reinforce the importance of biophysics in drug discovery.

Abstract

Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound–target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Typical data obtained from biophysical methods in drug discovery.
Figure 2: Biophysical techniques in drug discovery: throughput versus content.

Similar content being viewed by others

References

  1. Arkin, M. R., Tang, Y. & Wells, J. A. Small-molecule inhibitors of protein–protein interactions: progressing toward the reality. Chem. Biol. 21, 1102–1114 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Higueruelo, A. P., Jubb, H. & Blundell, T. L. Protein–protein interactions as druggable targets: recent technological advances. Curr. Opin. Pharmacol. 13, 791–796 (2013).

    CAS  PubMed  Google Scholar 

  3. Holdgate, G. A. & Gill, A. L. Kinetic efficiency: the missing metric for enhancing compound quality? Drug Discov. Today 16, 910–913 (2011).

    PubMed  Google Scholar 

  4. Copeland, R. A. The drug-target residence time model: a 10-year retrospective. Nat. Rev. Drug Discov. 15, 87–95 (2016). This paper explains the context and importance of the drug–target residence time concept in drug discovery. Progress in exploiting this concept in the past decade is summarized alongside opportunities for further advances.

    CAS  PubMed  Google Scholar 

  5. 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).

    CAS  PubMed  Google Scholar 

  6. Jhoti, H., Williams, G., Rees, D. C. & Murray, C. W. The 'rule of three' for fragment-based drug discovery: where are we now? Nat. Rev. Drug Discov. 12, 644–645 (2013).

    CAS  PubMed  Google Scholar 

  7. Silvestre, H. L., Blundell, T. L., Abell, C. & Ciulli, A. Integrated biophysical approach to fragment screening and validation for fragment-based lead discovery. Proc. Natl Acad. Sci. USA 110, 12984–12989 (2013). This paper describes the application of fragment screening using different biophysical techniques.

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Erlanson, D. A. & Zartler, E. Fragments in the clinic: 2015 edition. Practical Fragments, http://practicalfragments.blogspot.fr/2015/01/fragments-in-clinic-2015-edition.html (2015).

    Google Scholar 

  9. Klebe, G. Applying thermodynamic profiling in lead finding and optimization. Nat. Rev. Drug Discov. 14, 95–110 (2015). In this paper, multiple factors influencing the thermodynamics of binding are described. Key issues in understanding the effects of these factors and the application of this this knowledge in drug discovery are presented.

    CAS  PubMed  Google Scholar 

  10. Leeson, P. D. & Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat. Rev. Drug Discov. 6, 881–890 (2007).

    CAS  PubMed  Google Scholar 

  11. Blundell, T. L. & Patel, S. High-throughput X-ray crystallography for drug discovery. Curr. Opin. Pharmacol. 4, 490–496 (2004).

    CAS  PubMed  Google Scholar 

  12. Cala, O., Guilliere, F. & Krimm, I. NMR-based analysis of protein-ligand interactions. Anal. Bioanal. Chem. 406, 943–956 (2014).

    CAS  PubMed  Google Scholar 

  13. Pellecchia, M. et al. Perspectives on NMR in drug discovery: a technique comes of age. Nat. Rev. Drug Discov. 7, 738–745 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Śledź, P., Abell, C. & Ciulli, A. NMR of Biomolecules: Towards Mechanistic Systems Biology. 1st edn (eds Bertini, I., McGreevy, K. S. & Parigi, G.) 265–280 (Wiley-VCH Verlag GmbH & Co. KGaA, 2012).

    Google Scholar 

  15. Cooper, M. A. Optical biosensors in drug discovery. Nat. Rev. Drug Discov. 1, 515–528 (2002).

    CAS  PubMed  Google Scholar 

  16. Geschwindner, S., Carlsson, J. F. & Knecht, W. Application of optical biosensors in small-molecule screening activities. Sensors (Basel) 12, 4311–4323 (2012).

    CAS  Google Scholar 

  17. Huber, W. & Mueller, F. Biomolecular interaction analysis in drug discovery using surface plasmon resonance technology. Curr. Pharm. Des. 12, 3999–4021 (2006).

    CAS  PubMed  Google Scholar 

  18. Neumann, T., Junker, H. D., Schmidt, K. & Sekul, R. SPR-based fragment screening: advantages and applications. Curr. Top. Med. Chem. 7, 1630–1642 (2007).

    CAS  PubMed  Google Scholar 

  19. Renaud, J. P., Neumann, T. & Van Hijfte, L. Small Molecule Medicinal Chemistry: Strategies and Technologies. (eds Czechtizky, W. & Hamley, P.) 221–249 (John Wiley & Sons Inc., 2015).

    Google Scholar 

  20. Lo, M. C. et al. Evaluation of fluorescence-based thermal shift assays for hit identification in drug discovery. Anal. Biochem. 332, 153–159 (2004).

    CAS  PubMed  Google Scholar 

  21. Niesen, F. H., Berglund, H. & Vedadi, M. The use of differential scanning fluorimetry to detect ligand interactions that promote protein stability. Nat. Protoc. 2, 2212–2221 (2007).

    CAS  PubMed  Google Scholar 

  22. Ladbury, J. E., Klebe, G. & Freire, E. Adding calorimetric data to decision making in lead discovery: a hot tip. Nat. Rev. Drug Discov. 9, 23–27 (2010).

    CAS  PubMed  Google Scholar 

  23. Chaires, J. B. Calorimetry and thermodynamics in drug design. Annu. Rev. Biophys. 37, 135–151 (2008).

    CAS  PubMed  Google Scholar 

  24. Hofstadler, S. A. & Sannes-Lowery, K. A. Applications of ESI-MS in drug discovery: interrogation of noncovalent complexes. Nat. Rev. Drug Discov. 5, 585–595 (2006).

    CAS  PubMed  Google Scholar 

  25. Vivat Hannah, V., Atmanene, C., Zeyer, D., Van Dorsselaer, A. & Sanglier-Cianferani, S. Native MS: an 'ESI' way to support structure- and fragment-based drug discovery. Future Med. Chem. 2, 35–50 (2010).

    PubMed  Google Scholar 

  26. Annis, D. A., Nickbarg, E., Yang, X., Ziebell, M. R. & Whitehurst, C. E. Affinity selection-mass spectrometry screening techniques for small molecule drug discovery. Curr. Opin. Chem. Biol. 11, 518–526 (2007).

    CAS  PubMed  Google Scholar 

  27. Chalmers, M. J., Busby, S. A., Pascal, B. D., West, G. M. & Griffin, P. R. Differential hydrogen/deuterium exchange mass spectrometry analysis of protein–ligand interactions. Expert Rev. Proteom. 8, 43–59 (2011).

    CAS  Google Scholar 

  28. Konermann, L., Pan, J. & Liu, Y. H. Hydrogen exchange mass spectrometry for studying protein structure and dynamics. Chem. Soc. Rev. 40, 1224–1234 (2011).

    CAS  PubMed  Google Scholar 

  29. Seidel, S. A. et al. Microscale thermophoresis quantifies biomolecular interactions under previously challenging conditions. Methods 59, 301–315 (2013).

    CAS  PubMed  Google Scholar 

  30. Seidel, S. A. et al. Label-free microscale thermophoresis discriminates sites and affinity of protein–ligand binding. Angew. Chem. Int. 51, 10656–10659 (2012).

    CAS  Google Scholar 

  31. Tuukkanen, A. T. & Svergun, D. I. Weak protein-ligand interactions studied by small-angle X-ray scattering. FEBS J. 281, 1974–1987 (2014).

    CAS  PubMed  Google Scholar 

  32. Vestergaard, B. & Sayers, Z. Investigating increasingly complex macromolecular systems with small-angle X-ray scattering. IUCrJ 1, 523–529 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Hirst, E. R., Yuan, Y. J., Xu, W. L. & Bronlund, J. E. Bond-rupture immunosensors — a review. Biosens. Bioelectron. 23, 1759–1768 (2008).

    CAS  PubMed  Google Scholar 

  34. Cooper, M. A. & Singleton, V. T. A survey of the 2001 to 2005 quartz crystal microbalance biosensor literature: applications of acoustic physics to the analysis of biomolecular interactions. J. Mol. Recognit 20, 154–184 (2007).

    CAS  PubMed  Google Scholar 

  35. Björke, H. & Andersson, K. Measuring the affinity of a radioligand with its receptor using a rotating cell dish with in situ reference area. Appl. Radiat. Isot. 64, 32–37 (2006).

    PubMed  Google Scholar 

  36. Danielson, U. H. Fragment library screening and lead characterization using SPR biosensors. Curr. Top. Med. Chem. 9, 1725–1735 (2009).

    CAS  PubMed  Google Scholar 

  37. Giannetti, A. M. From experimental design to validated hits a comprehensive walk-through of fragment lead identification using surface plasmon resonance. Methods Enzymol. 493, 169–218 (2011).

    CAS  PubMed  Google Scholar 

  38. Davis, B. J. & Erlanson, D. A. Learning from our mistakes: the 'unknown knowns' in fragment screening. Bioorg. Med. Chem. Lett. 23, 2844–2852 (2013).

    CAS  PubMed  Google Scholar 

  39. Kitova, E. N., El-Hawiet, A., Schnier, P. D. & Klassen, J. S. Reliable determinations of protein-ligand interactions by direct ESI-MS measurements. Are we there yet? J. Am. Soc. Mass Spectrom. 23, 431–441 (2012).

    CAS  PubMed  Google Scholar 

  40. Hubbard, R. E. & Murray, J. B. Experiences in fragment-based lead discovery. Methods Enzymol. 493, 509–531 (2011). This paper provides an overview of the application of biophysical techniques in fragment screening across a range of different targets.

    CAS  PubMed  Google Scholar 

  41. Shuker, S. B., Hajduk, P. J., Meadows, R. P. & Fesik, S. W. Discovering high-affinity ligands for proteins: SAR by NMR. Science 274, 1531–1534 (1996).

    CAS  PubMed  Google Scholar 

  42. Hajduk, P. J. & Greer, J. A decade of fragment-based drug design: strategic advances and lessons learned. Nat. Rev. Drug Discov. 6, 211–219 (2007).

    CAS  PubMed  Google Scholar 

  43. Nienaber, V. L. et al. Discovering novel ligands for macromolecules using X-ray crystallographic screening. Nat. Biotechnol. 18, 1105–1108 (2000).

    CAS  PubMed  Google Scholar 

  44. Sharff, A. & Jhoti, H. High-throughput crystallography to enhance drug discovery. Curr. Opin. Chem. Biol. 7, 340–345 (2003).

    CAS  PubMed  Google Scholar 

  45. Murray, C. W., Verdonk, M. L. & Rees, D. C. Experiences in fragment-based drug discovery. Trends Pharmacol. Sci. 33, 224–232 (2012).

    CAS  PubMed  Google Scholar 

  46. Hubbard, R. E., Davis, B., Chen, I. & Drysdale, M. J. The SeeDs approach: integrating fragments into drug discovery. Curr. Top. Med. Chem. 7, 1568–1581 (2007).

    CAS  PubMed  Google Scholar 

  47. Nordström, H. et al. Identification of MMP-12 inhibitors by using biosensor-based screening of a fragment library. J. Med. Chem. 51, 3449–3459 (2008).

    PubMed  Google Scholar 

  48. Kuo, L. C. Fragment-based drug design — tools, practical approaches, and examples. Preface. Methods Enzymol. 493, xxi–xxii (2011).

    PubMed  Google Scholar 

  49. Schiebel, J. et al. One question, multiple answers: biochemical and biophysical screening methods retrieve deviating fragment hit lists. ChemMedChem. 10, 1511–1521 (2015). This is a study of how different biophysical filtering techniques result in poorly overlapping compound collections in fragment screening.

    CAS  PubMed  Google Scholar 

  50. Hennig, M., Ruf, A. & Huber, W. Combining biophysical screening and X-ray crystallography for fragment-based drug discovery. Top. Curr. Chem. 317, 115–143 (2012).

    CAS  PubMed  Google Scholar 

  51. Zhang, J. et al. Targeting Bcr–Abl by combining allosteric with ATP-binding-site inhibitors. Nature 463, 501–506 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Jahnke, W. et al. Allosteric non-bisphosphonate FPPS inhibitors identified by fragment-based discovery. Nat. Chem. Biol. 6, 660–666 (2010).

    CAS  PubMed  Google Scholar 

  53. Darby, J. F. et al. Discovery of selective small-molecule activators of a bacterial glycoside hydrolase. Angew. Chem. Int. 53, 13419–13423 (2014).

    CAS  Google Scholar 

  54. Winter, A. et al. Biophysical and computational fragment-based approaches to targeting protein-protein interactions: applications in structure-guided drug discovery. Q. Rev. Biophys. 45, 383–426 (2012).

    CAS  PubMed  Google Scholar 

  55. Iversen, P. W. et al. in Assay Guidance Manual (eds Sittampalam, G. S. et al.) (Bethesda (MD), 2004).

    Google Scholar 

  56. Folmer, R. H. Integrating biophysics with HTS-driven drug discovery projects. Drug Discov. Today 21, 491–498 (2016). This is a discussion of the impact of biophysical techniques for screening as well as their application as filters for HTS outcomes.

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  58. Pantoliano, M. W. et al. High-density miniaturized thermal shift assays as a general strategy for drug discovery. J. Biomol. Screen 6, 429–440 (2001).

    CAS  PubMed  Google Scholar 

  59. Roddy, T. P. et al. Mass spectrometric techniques for label-free high-throughput screening in drug discovery. Anal. Chem. 79, 8207–8213 (2007).

    CAS  PubMed  Google Scholar 

  60. Baell, J. & Walters, M. A. Chemistry: chemical con artists foil drug discovery. Nature 513, 481–483 (2014).

    CAS  PubMed  Google Scholar 

  61. Seidler, J., McGovern, S. L., Doman, T. N. & Shoichet, B. K. Identification and prediction of promiscuous aggregating inhibitors among known drugs. J. Med. Chem. 46, 4477–4486 (2003).

    CAS  PubMed  Google Scholar 

  62. 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).

    CAS  PubMed  Google Scholar 

  63. Elinder, M. et al. Inhibition of HIV-1 by non-nucleoside reverse transcriptase inhibitors via an induced fit mechanism-Importance of slow dissociation and relaxation rates for antiviral efficacy. Biochem. Pharmacol. 80, 1133–1140 (2010).

    CAS  PubMed  Google Scholar 

  64. Geitmann, M. et al. Interaction kinetic and structural dynamic analysis of ligand binding to acetylcholine-binding protein. Biochemistry 49, 8143–8154 (2010).

    CAS  PubMed  Google Scholar 

  65. Seeger, C., Gorny, X., Reddy, P. P., Seidenbecher, C. & Danielson, U. H. Kinetic and mechanistic differences in the interactions between caldendrin and calmodulin with AKAP79 suggest different roles in synaptic function. J. Mol. Recognit 25, 495–503 (2012).

    CAS  PubMed  Google Scholar 

  66. Souers, A. J. et al. ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets. Nat. Med. 19, 202–208 (2013).

    CAS  PubMed  Google Scholar 

  67. Saalau-Bethell, S. M. et al. Discovery of an allosteric mechanism for the regulation of HCV NS3 protein function. Nat. Chem. Biol. 8, 920–925 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Friberg, A. et al. Discovery of potent myeloid cell leukemia 1 (Mcl-1) inhibitors using fragment-based methods and structure-based design. J. Med. Chem. 56, 15–30 (2013).

    CAS  PubMed  Google Scholar 

  69. Maurer, T. et al. Small-molecule ligands bind to a distinct pocket in Ras and inhibit SOS-mediated nucleotide exchange activity. Proc. Natl Acad. Sci. USA 109, 5299–5304 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Sun, Q. et al. Discovery of small molecules that bind to K-Ras and inhibit Sos-mediated activation. Angew. Chem. Int. 51, 6140–6143 (2012).

    CAS  Google Scholar 

  71. Ostrem, J. M., Peters, U., Sos, M. L., Wells, J. A. & Shokat, K. M. K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions. Nature 503, 548–551 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Pickhardt, M. et al. Identification of small molecule inhibitors of tau aggregation by targeting monomeric tau as a potential therapeutic approach for tauopathies. Curr. Alzheimer Res. 12, 814–828 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Bunnage, M. E. Getting pharmaceutical R&D back on target. Nat. Chem. Biol. 7, 335–339 (2011).

    CAS  PubMed  Google Scholar 

  74. Martinez Molina, D. et al. Monitoring drug target engagement in cells and tissues using the cellular thermal shift assay. Science 341, 84–87 (2013).

    PubMed  Google Scholar 

  75. Reinhard, F. B. et al. Thermal proteome profiling monitors ligand interactions with cellular membrane proteins. Nat. Methods 12, 1129–1131 (2015).

    CAS  PubMed  Google Scholar 

  76. Savitski, M. M. et al. Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346, 1255784 (2014).

    PubMed  Google Scholar 

  77. Martinez Molina, D. & Nordlund, P. The cellular thermal shift assay: a novel biophysical assay for in situ drug target engagement and mechanistic biomarker studies. Annu. Rev. Pharmacol. Toxicol. 56, 141–161 (2016).

    CAS  PubMed  Google Scholar 

  78. Navratilova, I., Dioszegi, M. & Myszka, D. G. Analyzing ligand and small molecule binding activity of solubilized GPCRs using biosensor technology. Anal. Biochem. 355, 132–139 (2006).

    CAS  PubMed  Google Scholar 

  79. Navratilova, I., Sodroski, J. & Myszka, D. G. Solubilization, stabilization, and purification of chemokine receptors using biosensor technology. Anal. Biochem. 339, 271–281 (2005).

    CAS  PubMed  Google Scholar 

  80. Aristotelous, T. et al. Discovery of β2 adrenergic receptor ligands using biosensor fragment screening of tagged wild-type receptor. ACS Med. Chem. Lett. 4, 1005–1010 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Chu, R., Reczek, D. & Brondyk, W. Capture-stabilize approach for membrane protein SPR assays. Sci. Rep. 4, 7360 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Christopher, J. A. et al. Biophysical fragment screening of the β1-adrenergic receptor: identification of high affinity arylpiperazine leads using structure-based drug design. J. Med. Chem. 56, 3446–3455 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Errey, J. C., Dore, A. S., Zhukov, A., Marshall, F. H. & Cooke, R. M. Purification of stabilized GPCRs for structural and biophysical analyses. Methods Mol. Biol. 1335, 1–15 (2015).

    PubMed  Google Scholar 

  84. Congreve, M. et al. Fragment screening of stabilized G-protein-coupled receptors using biophysical methods. Methods Enzymol. 493, 115–136 (2011).

    CAS  PubMed  Google Scholar 

  85. Christopher, J. A. et al. Discovery of HTL6641, a dual orexin receptor antagonist with differentiated pharmacodynamic properties. MedChemComm 6, 947–955 (2015).

    CAS  Google Scholar 

  86. Egloff, P. et al. Structure of signaling-competent neurotensin receptor 1 obtained by directed evolution in Escherichia coli. Proc. Natl Acad. Sci. USA 111, E655–E662 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Chen, D. et al. Fragment screening of GPCRs using biophysical methods: identification of ligands of the adenosine A2A receptor with novel biological activity. ACS Chem. Biol. 7, 2064–2073 (2012).

    CAS  PubMed  Google Scholar 

  88. Fruh, V. et al. Application of fragment-based drug discovery to membrane proteins: identification of ligands of the integral membrane enzyme DsbB. Chem. Biol. 17, 881–891 (2010).

    PubMed  PubMed Central  Google Scholar 

  89. Bocquet, N. et al. Real-time monitoring of binding events on a thermostabilized human A2A receptor embedded in a lipid bilayer by surface plasmon resonance. Biochim. Biophys. Acta 1848, 1224–1233 (2015).

    CAS  PubMed  Google Scholar 

  90. Dawson, R. J. et al. Structure of the acid-sensing ion channel 1 in complex with the gating modifier Psalmotoxin 1. Nat. Commun. 3, 936 (2012).

    PubMed  Google Scholar 

  91. Seeger, C. et al. Histaminergic pharmacology of homo-oligomeric β3 γ-aminobutyric acid type A receptors characterized by surface plasmon resonance biosensor technology. Biochem. Pharmacol. 84, 341–351 (2012).

    CAS  PubMed  Google Scholar 

  92. Kesters, D. et al. Structural basis of ligand recognition in 5-HT3 receptors. EMBO Rep. 14, 49–56 (2013).

    CAS  PubMed  Google Scholar 

  93. Spurny, R. et al. Molecular blueprint of allosteric binding sites in a homologue of the agonist-binding domain of the alpha7 nicotinic acetylcholine receptor. Proc. Natl Acad. Sci. USA 112, E2543–2552 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Perspicace, S. et al. Isothermal titration calorimetry with micelles: thermodynamics of inhibitor binding to carnitine palmitoyltransferase 2 membrane protein. FEBS Open Bio. 3, 204–211 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Claridge, S. A., Schwartz, J. J. & Weiss, P. S. Electrons, photons, and force: quantitative single-molecule measurements from physics to biology. ACS Nano. 5, 693–729 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Kapanidis, A. N. & Strick, T. Biology, one molecule at a time. Trends Biochem. Sci. 34, 234–243 (2009).

    CAS  PubMed  Google Scholar 

  97. Walter, N. G., Huang, C. Y., Manzo, A. J. & Sobhy, M. A. Do-it-yourself guide: how to use the modern single-molecule toolkit. Nat. Methods 5, 475–489 (2008). This is a summary of the current state of the art in single-molecule tools, including fluorescence spectroscopy, tethered particle microscopy, optical and magnetic tweezers, and atomic force microscopy, including guidelines on when to apply each method and what outcome to expect from them.

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Grohmann, D., Werner, F. & Tinnefeld, P. Making connections — strategies for single molecule fluorescence biophysics. Curr. Opin. Chem. Biol. 17, 691–698 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Smiley, R. D. & Hammes, G. G. Single molecule studies of enzyme mechanisms. Chem. Rev. 106, 3080–3094 (2006).

    CAS  PubMed  Google Scholar 

  100. Roy, R., Hohng, S. & Ha, T. A practical guide to single-molecule FRET. Nat. Methods 5, 507–516 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Gunnarsson, A. et al. Drug discovery at the single molecule level: inhibition-in-solution assay of membrane-reconstituted beta-secretase using single-molecule imaging. Anal. Chem. 87, 4100–4103 (2015).

    CAS  PubMed  Google Scholar 

  102. Zhao, Y. et al. Lab-on-a-chip technologies for single-molecule studies. Lab. Chip 13, 2183–2198 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Marx, V. Structural biology: 'seeing' crystals the XFEL way. Nat. Methods 11, 903–908 (2014).

    CAS  PubMed  Google Scholar 

  104. Schlichting, I. Serial femtosecond crystallography: the first five years. IUCrJ 2, 246–255 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Bai, X. C., McMullan, G. & Scheres, S. H. How cryo-EM is revolutionizing structural biology. Trends Biochem. Sci. 40, 49–57 (2015). This is a good overview of recent advances in cryo-EM techniques and what can be achieved with these techniques regarding opportunities in structural biology (such as size of molecules and resolution).

    CAS  PubMed  Google Scholar 

  106. Cheng, Y., Grigorieff, N., Penczek, P. A. & Walz, T. A primer to single-particle cryo-electron microscopy. Cell 161, 438–449 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. Kern, J., Yachandra, V. K. & Yano, J. Metalloprotein structures at ambient conditions and in real-time: biological crystallography and spectroscopy using X-ray free electron lasers. Curr. Opin. Struct. Biol. 34, 87–98 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Liao, M., Cao, E., Julius, D. & Cheng, Y. Structure of the TRPV1 ion channel determined by electron cryo-microscopy. Nature 504, 107–112 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Bai, X. C. et al. An atomic structure of human gamma-secretase. Nature 525, 212–217 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  110. Bartesaghi, A. et al. 2.2 Å resolution cryo-EM structure of beta-galactosidase in complex with a cell-permeant inhibitor. Science 348, 1147–1151 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Henderson, R. The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules. Q. Rev. Biophys. 28, 171–193 (1995).

    CAS  PubMed  Google Scholar 

  112. Markgren, P. O., Hämäläinen, M. & Danielson, U. H. Kinetic analysis of the interaction between HIV-1 protease and inhibitors using optical biosensor technology. Anal. Biochem. 279, 71–78 (2000).

    CAS  PubMed  Google Scholar 

  113. Gossas, T. et al. The advantage of biosensor analysis over enzyme inhibition studies for slow dissociating inhibitors — characterization of hydroxamate-based matrix metalloproteinase-12 inhibitors. MedChemComm 4, 432–442 (2013).

    CAS  Google Scholar 

  114. Talibov, V. O., Linkiviene, V., Matulis, D. & Danielson, U. H. Kinetically selective inhibitors of human carbonic anhydrase isoenzymes I, II, VII, IX, XII and XIII. J. Med. Chem. 59, 2083–2093 (2016).

    CAS  PubMed  Google Scholar 

  115. Christopeit, T. et al. A surface plasmon resonance-based biosensor with full-length BACE1 in a reconstituted membrane. Anal. Biochem. 414, 14–22 (2011).

    CAS  PubMed  Google Scholar 

  116. Dominguez, J. L. et al. Effect of the protonation state of the titratable residues on the inhibitor affinity to BACE-1. Biochemistry 49, 7255–7263 (2010).

    CAS  PubMed  Google Scholar 

  117. Sussman, F., Villaverde, M. C., Dominguez, J. L. & Danielson, U. H. On the active site protonation state in aspartic proteases: implications for drug design. Curr. Pharm. Des. 19, 4257–4275 (2013).

    CAS  PubMed  Google Scholar 

  118. Cusack, K. P. et al. Design strategies to address kinetics of drug binding and residence time. Bioorg. Med. Chem. Lett. 25, 2019–2027 (2015). In this paper, factors contributing to long residence time are introduced by the authors as well as how these factors could be useful to medicinal chemists in the design of compounds with long residence times. Case studies on structure–kinetic relationships are given.

    CAS  PubMed  Google Scholar 

  119. Swinney, D. C. The role of binding kinetics in therapeutically useful drug action. Curr. Opin. Drug Discov. Devel 12, 31–39 (2009).

    CAS  PubMed  Google Scholar 

  120. Dahl, G. & Åkerud, T. Pharmacokinetics and the drug-target residence time concept. Drug Discov. Today 18, 697–707 (2013). This article raises concerns about the utility of drug–target residence times for predicting the in vivo outcomes in terms of duration of effect of drugs when pharmacokinetics are not taken into account.

    CAS  PubMed  Google Scholar 

  121. Pan, A. C., Borhani, D. W., Dror, R. O. & Shaw, D. E. Molecular determinants of drug-receptor binding kinetics. Drug Discov. Today 18, 667–673 (2013). This is a discussion of the challenges of using kinetics during lead optimization and a review of key factors that are thought to be important for drug–receptor binding kinetics.

    CAS  PubMed  Google Scholar 

  122. Bradshaw, J. M. et al. Prolonged and tunable residence time using reversible covalent kinase inhibitors. Nat. Chem. Biol. 11, 525–531 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  123. Ferenczy, G. G. & Keseru, G. M. Thermodynamics guided lead discovery and optimization. Drug Discov. Today 15, 919–932 (2010).

    CAS  PubMed  Google Scholar 

  124. Holdgate, G. A. Thermodynamics of binding interactions in the rational drug design process. Expert Opin. Drug Discov. 2, 1103–1114 (2007).

    CAS  PubMed  Google Scholar 

  125. Chodera, J. D. & Mobley, D. L. Entropy-enthalpy compensation: role and ramifications in biomolecular ligand recognition and design. Annu. Rev. Biophys. 42, 121–142 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  126. Klebe, G. The use of thermodynamic and kinetic data in drug discovery: decisive insight or increasing the puzzlement? ChemMedChem. 10, 229–231 (2015).

    CAS  PubMed  Google Scholar 

  127. Geschwindner, S., Ulander, J. & Johansson, P. Ligand binding thermodynamics in drug discovery: still a hot tip? J. Med. Chem. 58, 6321–6335 (2015). This article shows that the mere use of enthalpy and entropy data is of little help in lead optimization in the absence of structural information, owing to multiple factors affecting thermodynamic signatures. Several case studies are presented.

    CAS  PubMed  Google Scholar 

  128. Schiele, F., Ayaz, P. & Fernandez-Montalvan, A. A universal homogeneous assay for high-throughput determination of binding kinetics. Anal. Biochem. 468, 42–49 (2014). This article introduces a method for high-throughput determination of kinetic parameters, exemplifying it using three different target classes: enzymes, protein–protein interactions and GPCRs.

    PubMed  Google Scholar 

  129. Motulsky, H. J. & Mahan, L. C. The kinetics of competitive radioligand binding predicted by the law of mass action. Mol. Pharmacol. 25, 1–9 (1984).

    CAS  PubMed  Google Scholar 

  130. Braissant, O. et al. Isothermal microcalorimetry accurately detects bacteria, tumorous microtissues, and parasitic worms in a label-free well-plate assay. Biotechnol. J. 10, 460–468 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Luchinat, E. & Banci, L. A. Unique tool for cellular structural biology: in-cell NMR. J. Biol. Chem. 291, 3776–3784 (2016).

    CAS  PubMed  Google Scholar 

  132. Leake, M. C. The physics of life: one molecule at a time. Phil. Trans. R. Soc. B 368, 20120248 (2013).

    PubMed  PubMed Central  Google Scholar 

  133. Aristotelous, T., Hopkins, A. L. & Navratilova, I. Surface plasmon resonance analysis of seven-transmembrane receptors. Methods Enzymol. 556, 499–525 (2015). This is an overview of SPR technologies and their application to GPCRs.

    CAS  PubMed  Google Scholar 

  134. Olaru, A., Bala, C., Jaffrezic-Renault, N. & Aboul-Enein, H. Y. Surface plasmon resonance (SPR) biosensors in pharmaceutical analysis. Crit. Rev. Anal. Chem. 45, 97–105 (2015).

    CAS  PubMed  Google Scholar 

  135. Patching, S. G. Surface plasmon resonance spectroscopy for characterisation of membrane protein-ligand interactions and its potential for drug discovery. Biochim. Biophys. Acta 1838, 43–55 (2014).

    CAS  PubMed  Google Scholar 

  136. Recht, M. I. et al. Identification and optimization of PDE10A inhibitors using fragment-based screening by nanocalorimetry and X-ray crystallography. J. Biomol. Screen 19, 497–507 (2014).

    CAS  PubMed  Google Scholar 

  137. Oltersdorf, T. et al. An inhibitor of Bcl-2 family proteins induces regression of solid tumours. Nature 435, 677–681 (2005).

    CAS  PubMed  Google Scholar 

  138. Brough, P. A. et al. 4,5-diarylisoxazole Hsp90 chaperone inhibitors: potential therapeutic agents for the treatment of cancer. J. Med. Chem. 51, 196–218 (2008).

    CAS  PubMed  Google Scholar 

  139. Murray, J. B., Roughley, S. D., Matassova, N. & Brough, P. A. Off-rate screening (ORS) by surface plasmon resonance. An efficient method to kinetically sample hit to lead chemical space from unpurified reaction products. J. Med. Chem. 57, 2845–2850 (2014).

    CAS  PubMed  Google Scholar 

  140. Brough, P. A. et al. Combining hit identification strategies: fragment-based and in silico approaches to orally active 2-aminothieno[2,3-d]pyrimidine inhibitors of the Hsp90 molecular chaperone. J. Med. Chem. 52, 4794–4809 (2009).

    CAS  PubMed  Google Scholar 

  141. Marzinzik, A. L. et al. Discovery of novel allosteric non-bisphosphonate inhibitors of farnesyl pyrophosphate synthase by integrated lead finding. ChemMedChem. 10, 1884–1891 (2015).

    CAS  PubMed  Google Scholar 

  142. Harner, M. J., Frank, A. O. & Fesik, S. W. Fragment-based drug discovery using NMR spectroscopy. J. Biomol. NMR 56, 65–75 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  143. Wu, B. et al. HTS by NMR of combinatorial libraries: a fragment-based approach to ligand discovery. Chem. Biol. 20, 19–33 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  144. Wu, B. et al. High-throughput screening by nuclear magnetic resonance (HTS by NMR) for the identification of PPIs antagonists. Curr. Top. Med. Chem. 15, 2032–2042 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  145. Bruylants, G., Wouters, J. & Michaux, C. Differential scanning calorimetry in life science: thermodynamics, stability, molecular recognition and application in drug design. Curr. Med. Chem. 12, 2011–2020 (2005).

    CAS  PubMed  Google Scholar 

  146. Concepcion, J. et al. Label-free detection of biomolecular interactions using BioLayer interferometry for kinetic characterization. Comb. Chem. High Throughput Screen. 12, 791–800 (2009).

    CAS  PubMed  Google Scholar 

  147. Shah, N. B. & Duncan, T. M. Bio-layer interferometry for measuring kinetics of protein–protein interactions and allosteric ligand effects. J. Vis. Exp. 18, e51383 (2014).

    Google Scholar 

  148. Wartchow, C. A. et al. Biosensor-based small molecule fragment screening with biolayer interferometry. J. Comput. Aided Mol. Des. 25, 669–676 (2011).

    CAS  PubMed  Google Scholar 

  149. Baksh, M. M., Kussrow, A. K., Mileni, M., Finn, M. G. & Bornhop, D. J. Label-free quantification of membrane-ligand interactions using backscattering interferometry. Nat. Biotechnol. 29, 357–360 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. Bornhop, D. J. et al. Free-solution, label-free molecular interactions studied by back-scattering interferometry. Science 317, 1732–1736 (2007).

    CAS  PubMed  Google Scholar 

  151. Heym, R. G., Hornberger, W. B., Lakics, V. & Terstappen, G. C. Label-free detection of small-molecule binding to a GPCR in the membrane environment. Biochim. Biophys. Acta 1854, 979–986 (2015).

    CAS  PubMed  Google Scholar 

  152. Perpeet, M. et al. SAW sensor system for marker-free molecular interaction analysis. Anal. Lett. 39, 1747–1757 (2006).

    CAS  Google Scholar 

  153. Moree, B. et al. Protein conformational changes are detected and resolved site specifically by second-harmonic generation. Biophys. J. 109, 806–815 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  154. Moree, B. et al. Small molecules detected by second-harmonic generation modulate the conformation of monomeric α-synuclein and reduce its aggregation in cells. J. Biol. Chem. 290, 27582–27593 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  155. Salafsky, J. S. Detection of protein conformational change by optical second-harmonic generation. J. Chem. Phys. 125, 074701 (2006).

    PubMed  Google Scholar 

  156. Kozma, P., Hamori, A., Kurunczi, S., Cottier, K. & Horvath, R. Grating coupled optical waveguide interferometer for label-free biosensing. Sens. Actuators B: Chem. 155, 446–450 (2011).

    CAS  Google Scholar 

  157. Kozma, P., Kehl, F., Ehrentreich-Forster, E., Stamm, C. & Bier, F. F. Integrated planar optical waveguide interferometer biosensors: a comparative review. Biosens. Bioelectron. 58, 287–307 (2014).

    CAS  PubMed  Google Scholar 

  158. Langer, A. et al. Protein analysis by time-resolved measurements with an electro-switchable DNA chip. Nat. Commun. 4, 2099 (2013).

    PubMed  Google Scholar 

Download references

Author information

Author notes

  1. Michael Hennig

    Present address: Present address: leadXpro AG, PARK INNOVAARE, CH-5234 Villigen, Switzerland.,

Authors and Affiliations

  1. NovAliX, Boulevard Sébastien Brant, Illkirch Cedex, 67405, France

    Jean-Paul Renaud

  2. Institut de Génétique et Biologie Moléculaire et Cellulaire, CNRS UMR7104/INSERM U964/Université de Strasbourg, 1 rue Laurent Fries - BP10142, Illkirch Cedex, 67404, France

    Jean-Paul Renaud

  3. RiboStruct, 15 rue Neuve, Ostwald, 67540, France

    Jean-Paul Renaud

  4. GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, SG1 2NY, UK

    Chun-wa Chung

  5. Department of Chemistry — BMC and Science for Life Laboratory, Drug Discovery & Development Platform, Uppsala University, Uppsala, SE-751 05, Sweden

    U. Helena Danielson

  6. Beactica AB, Uppsala Business Park, Uppsala, 754 50, Sweden

    U. Helena Danielson

  7. Bayer Pharma AG, Müllerstrasse 178, Berlin, 13353, Germany

    Ursula Egner

  8. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, Basel, 4070, Switzerland

    Michael Hennig

  9. University of York, Heslington, York, YO10 5DD, UK

    Roderick E. Hubbard

  10. Vernalis (R&D), Granta Park, Cambridge, CB21 6GB, UK

    Roderick E. Hubbard

  11. Boehringer Ingelheim GmbH & Co. KG, Birkendorfer Strasse 65, Biberach, 88400, Germany

    Herbert Nar

Authors
  1. Jean-Paul Renaud
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chun-wa Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. U. Helena Danielson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ursula Egner
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michael Hennig
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Roderick E. Hubbard
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Herbert Nar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jean-Paul Renaud, Chun-wa Chung, U. Helena Danielson, Ursula Egner, Michael Hennig, Roderick E. Hubbard or Herbert Nar.

Ethics declarations

Competing interests

J.P.R. is a co-founder and a shareholder of NovAliX.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Renaud, JP., Chung, Cw., Danielson, U. et al. Biophysics in drug discovery: impact, challenges and opportunities. Nat Rev Drug Discov 15, 679–698 (2016). https://doi.org/10.1038/nrd.2016.123

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrd.2016.123

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research