Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

  • Alexander HeifetzEmail author
  • Michelle Southey
  • Inaki Morao
  • Andrea Townsend-Nicholson
  • Mike J. Bodkin
Part of the Methods in Molecular Biology book series (MIMB, volume 1705)


GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

Key words

Structure-based drug design Molecular dynamics Simulation Hit-to-lead Lead optimization G protein-coupled receptor Docking 



A.H. and A.T.-N. would like to acknowledge the support of EU H2020 CompBioMed project ( and the BBSRC Flexible Interchanger Programme project (BB/P004245/1).


  1. 1.
    Heifetz A, Schertler GF, Seifert R, Tate CG, Sexton PM, Gurevich VV, Fourmy D, Cherezov V, Marshall FH, Storer RI, Moraes I, Tikhonova IG, Tautermann CS, Hunt P, Ceska T, Hodgson S, Bodkin MJ, Singh S, Law RJ, Biggin PC (2015) GPCR structure, function, drug discovery and crystallography: report from academia-industry international conference (UK Royal Society) Chicheley hall, 1-2 September 2014. Naunyn Schmiedeberg's Arch Pharmacol 388:883–903CrossRefGoogle Scholar
  2. 2.
    Shonberg J, Kling RC, Gmeiner P, Lober S (2015) GPCR crystal structures: medicinal chemistry in the pocket. Bioorg Med Chem 23:3880–3906CrossRefPubMedGoogle Scholar
  3. 3.
    Wise A, Gearing K, Rees S (2002) Target validation of G-protein coupled receptors. Drug Discov Today 7:235–246CrossRefPubMedGoogle Scholar
  4. 4.
    Rask-Andersen M, Masuram S, Schioth HB (2014) The druggable genome: evaluation of drug targets in clinical trials suggests major shifts in molecular class and indication. Annu Rev Pharmacol Toxicol 54:9–26CrossRefPubMedGoogle Scholar
  5. 5.
    Dohlman HG (2015) Thematic minireview series: new directions in G protein-coupled receptor pharmacology. J Biol Chem 290:19469–19470CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Jazayeri A, Andrews SP, Marshall FH (2017) Structurally enabled discovery of adenosine A2A receptor antagonists. Chem Rev 117:21–37CrossRefPubMedGoogle Scholar
  7. 7.
    Jazayeri A, Dias JM, Marshall FH (2015) From G protein-coupled receptor structure resolution to rational drug design. J Biol Chem 290:19489–19495CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Cooke RM, Brown AJ, Marshall FH, Mason JS (2015) Structures of G protein-coupled receptors reveal new opportunities for drug discovery. Drug Discov Today 20:1355–1364CrossRefPubMedGoogle Scholar
  9. 9.
    Congreve M, Dias JM, Marshall FH (2014) Structure-based drug design for G protein-coupled receptors. Prog Med Chem 53:1–63CrossRefPubMedGoogle Scholar
  10. 10.
    Topiol S, Sabio M (2009) X-ray structure breakthroughs in the GPCR transmembrane region. Biochem Pharmacol 78:11–20CrossRefPubMedGoogle Scholar
  11. 11.
    Topiol S (2013) X-ray structural information of GPCRs in drug design: what are the limitations and where do we go? Expert Opin Drug Discov 8:607–620CrossRefPubMedGoogle Scholar
  12. 12.
    Topiol S, Sabio M (2015) The role of experimental and computational structural approaches in 7TM drug discovery. Expert Opin Drug Discov 10:1071–1084CrossRefPubMedGoogle Scholar
  13. 13.
    Tautermann CS, Gloriam DE (2016) Editorial overview: new technologies: GPCR drug design and function-exploiting the current (of) structures. Curr Opin Pharmacol 30:8–10CrossRefGoogle Scholar
  14. 14.
    Biggin PC, Aldeghi M, Bodkin MJ, Heifetz A (2016) Beyond membrane protein structure: drug discovery, dynamics and difficulties. Adv Exp Med Biol 922:161–181CrossRefPubMedGoogle Scholar
  15. 15.
    Tautermann CS, Seeliger D, Kriegl JM (2015) What can we learn from molecular dynamics simulations for GPCR drug design? Comput Struct Biotechnol J 13:111–121CrossRefPubMedGoogle Scholar
  16. 16.
    Latorraca NR, Venkatakrishnan AJ, Dror RO (2017) GPCR dynamics: structures in motion. Chem Rev 117:139–155CrossRefPubMedGoogle Scholar
  17. 17.
    Guo D, Pan AC, Dror RO, Mocking T, Liu R, Heitman LH, Shaw DE, IJ AP (2016) Molecular basis of ligand dissociation from the adenosine A2A receptor. Mol Pharmacol 89:485–491CrossRefPubMedGoogle Scholar
  18. 18.
    Pan AC, Borhani DW, Dror RO, Shaw DE (2013) Molecular determinants of drug-receptor binding kinetics. Drug Discov Today 18:667–673CrossRefPubMedGoogle Scholar
  19. 19.
    Dror RO, Arlow DH, Maragakis P, Mildorf TJ, Pan AC, Xu H, Borhani DW, Shaw DE (2011) Activation mechanism of the beta2-adrenergic receptor. Proc Natl Acad Sci U S A 108:18684–18689CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Mason JS, Bortolato A, Weiss DR, Deflorian F, Tehan B, Marshall FH (2013) High end GPCR design: crafted ligand design and druggability analysis using protein structure, lipophilic hotspots and explicit water networks. In Silico Pharmacol 1:23CrossRefPubMedCentralGoogle Scholar
  21. 21.
    Heifetz A, James T, Morao I, Bodkin MJ, Biggin PC (2016) Guiding lead optimization with GPCR structure modeling and molecular dynamics. Curr Opin Pharmacol 30:14–21CrossRefPubMedGoogle Scholar
  22. 22.
    Deprez-Poulain R, Deprez B (2004) Facts, figures and trends in lead generation. Curr Top Med Chem 4:569–580CrossRefPubMedGoogle Scholar
  23. 23.
    Heifetz A, Aldeghi M, Chudyk E, Fedorov DG, Bodkin M, Biggin PC (2016) Using the fragment molecular orbital method to investigate agonist-orexin 2 receptor interactions. Biochem Soc Trans 44(2):574–581CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Heifetz A, Chudyk EI, Gleave L, Aldeghi M, Cherezov V, Fedorov DG, Biggin PC, Bodkin MJ (2016) The fragment molecular orbital method reveals new insight into the chemical nature of GPCR-ligand interactions. J Chem Inf Model 56:159–172CrossRefPubMedGoogle Scholar
  25. 25.
    Heifetz A, Storer RI, McMurray G, James T, Morao I, Aldeghi M, Bodkin MJ, Biggin PC (2016) Application of an integrated GPCR SAR-modeling platform to explain the activation selectivity of human 5-HT over 5-HT. ACS Chem Biol 11(5):1372–1382CrossRefPubMedGoogle Scholar
  26. 26.
    Storer RI, Brennan PE, Brown AD, Bungay PJ, Conlon KM, Corbett MS, DePianta RP, Fish PV, Heifetz A, Ho DK, Jessiman AS, McMurray G, de Oliveira CA, Roberts LR, Root JA, Shanmugasundaram V, Shapiro MJ, Skerten M, Westbrook D, Wheeler S, Whitlock GA, Wright J (2014) Multiparameter optimization in CNS drug discovery: design of pyrimido[4,5-d]azepines as potent 5-hydroxytryptamine 2C (5-HT(2)C) receptor agonists with exquisite functional selectivity over 5-HT(2)A and 5-HT(2)B receptors. J Med Chem 57:5258–5269CrossRefPubMedGoogle Scholar
  27. 27.
    Tautermann CS (2014) GPCR structures in drug design, emerging opportunities with new structures. Bioorg Med Chem Lett 24:4073–4079CrossRefPubMedGoogle Scholar
  28. 28.
    Bartuzi D, Kaczor AA, Targowska-Duda KM, Matosiuk D (2017) Recent advances and applications of molecular docking to G protein-coupled receptors. Molecules 22(2):E340CrossRefPubMedGoogle Scholar
  29. 29.
    Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3:935–949CrossRefPubMedGoogle Scholar
  30. 30.
    Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 19:1639–1662CrossRefGoogle Scholar
  31. 31.
    Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461PubMedPubMedCentralGoogle Scholar
  32. 32.
    Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an incremental construction algorithm. J Mol Biol 261:470–489CrossRefPubMedGoogle Scholar
  33. 33.
    Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD (2003) Improved protein-ligand docking using GOLD. Proteins 52:609–623CrossRefPubMedGoogle Scholar
  34. 34.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749CrossRefPubMedGoogle Scholar
  35. 35.
    Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE 3rd (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33:889–897CrossRefPubMedGoogle Scholar
  36. 36.
    Liu S, Wu Y, Lin T, Abel R, Redmann JP, Summa CM, Jaber VR, Lim NM, Mobley DL (2013) Lead optimization mapper: automating free energy calculations for lead optimization. J Comput Aided Mol Des 27(9).
  37. 37.
    Sotriffer CA, Flader W, Winger RH, Rode BM, Liedl KR, Varga JM (2000) Automated docking of ligands to antibodies: methods and applications. Methods 20:280–291CrossRefPubMedGoogle Scholar
  38. 38.
    Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Blundell CD, Packer MJ, Almond A (2013) Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformation. Bioorg Med Chem 21:4976–4987CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Hawkins PC, Skillman AG, Nicholls A (2007) Comparison of shape-matching and docking as virtual screening tools. J Med Chem 50:74–82CrossRefPubMedGoogle Scholar
  41. 41.
    Marino KA, Shang Y, Filizola M (2017) Insights into the function of opioid receptors from molecular dynamics simulations of available crystal structures. Br J Pharmacol.
  42. 42.
    Schneider S, Provasi D, Filizola M (2015) The dynamic process of drug-GPCR binding at either orthosteric or allosteric sites evaluated by metadynamics. Methods Mol Biol 1335:277–294CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Kaczor AA, Rutkowska E, Bartuzi D, Targowska-Duda KM, Matosiuk D, Selent J (2016) Computational methods for studying G protein-coupled receptors (GPCRs). Methods Cell Biol 132:359–399CrossRefPubMedGoogle Scholar
  44. 44.
    Bartuzi D, Kaczor AA, Matosiuk D (2015) Activation and allosteric modulation of human mu opioid receptor in molecular dynamics. J Chem Inf Model 55:2421–2434CrossRefPubMedGoogle Scholar
  45. 45.
    Labute P (2010) LowModeMD--implicit low-mode velocity filtering applied to conformational search of macrocycles and protein loops. J Chem Inf Model 50:792–800CrossRefPubMedGoogle Scholar
  46. 46.
    De Vivo M, Masetti M, Bottegoni G, Cavalli A (2016) Role of molecular dynamics and related methods in drug discovery. J Med Chem 59:4035–4061CrossRefPubMedGoogle Scholar
  47. 47.
    Mollica L, Theret I, Antoine M, Perron-Sierra F, Charton Y, Fourquez J-M, Wierzbicki M, Boutin JA, Ferry G, Decherchi S, Bottegoni G, Ducrot P, Cavalli A (2016) Molecular dynamics simulations and kinetic measurements to estimate and predict protein–ligand residence times. J Med Chem 59:7167–7176CrossRefPubMedGoogle Scholar
  48. 48.
    Copeland RA (2016) The drug-target residence time model: a 10-year retrospective. Nat Rev Drug Discov 15:87–95CrossRefPubMedGoogle Scholar
  49. 49.
    Heifetz A, Trani G, Aldeghi M, MacKinnon CH, McEwan PA, Brookfield FA, Chudyk E, Bodkin M, Pei Z, Burch JD, Ortwine DF (2016) Fragment molecular orbital method applied to lead optimization of novel interleukin-2 inducible T-Cell Kinase (ITK) inhibitors. J Med Chem 59(9):4352–4363CrossRefPubMedGoogle Scholar
  50. 50.
    Morao I, Fedorov DG, Robinson R, Southey M, Townsend-Nicholson A, Bodkin MJ, Heifetz A (2017) Rapid and accurate assessment of GPCR-ligand interactions using the fragment molecular orbital-based density-functional tight-binding method. J Comput Chem 38(23):1987–1990CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Abel R, Young T, Farid R, Berne BJ, Friesner RA (2008) Role of the active-site solvent in the thermodynamics of factor Xa ligand binding. J Am Chem Soc 130:2817–2831CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Ross GA, Morris GM, Biggin PC (2012) Rapid and accurate prediction and scoring of water molecules in protein binding sites. PLoS One 7:e32036CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Truchon JF, Pettitt BM, Labute P (2014) A cavity corrected 3D-RISM functional for accurate solvation free energies. J Chem Theory Comput 10:934–941CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Gerogiokas G, Southey MW, Mazanetz MP, Heifetz A, Bodkin M, Law RJ, Henchman RH, Michel J (2016) Assessment of hydration thermodynamics at protein interfaces with grid cell theory. J Phys Chem B 120:10442–10452CrossRefPubMedGoogle Scholar
  55. 55.
    Gerogiokas G, Southey MW, Mazanetz MP, Heifetz A, Bodkin M, Law RJ, Michel J (2015) Evaluation of water displacement energetics in protein binding sites with grid cell theory. Phys Chem Chem Phys 17:8416–8426CrossRefPubMedGoogle Scholar
  56. 56.
    Vajda S, Guarnieri F (2006) Characterization of protein-ligand interaction sites using experimental and computational methods. Curr Opin Drug Discov Devel 9:354–362PubMedGoogle Scholar
  57. 57.
    Goldmann D, Zdrazil B, Digles D, Ecker GF (2016) Empowering pharmacoinformatics by linked life science data. J Comput Aided Mol Des 31(3):319328 CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Mazanetz MP, Marmon RJ, Reisser CB, Morao I (2012) Drug discovery applications for KNIME: an open source data mining platform. Curr Top Med Chem 12:1965–1979CrossRefPubMedGoogle Scholar
  59. 59.
    Heifetz A, Barker O, Verquin G, Wimmer N, Meutermans W, Pal S, Law RJ, Whittaker M (2013) Fighting obesity with a sugar-based library: discovery of novel MCH-1R antagonists by a new computational-VAST approach for exploration of GPCR binding sites. J Chem Inf Model 53:1084–1099CrossRefPubMedGoogle Scholar
  60. 60.
    Tye H, Mueller SG, Prestle J, Scheuerer S, Schindler M, Nosse B, Prevost N, Brown CJ, Heifetz A, Moeller C, Pedret-Dunn A, Whittaker M (2011) Novel 6,7,8,9-tetrahydro-5H-1,4,7,10a-tetraaza-cyclohepta[f]indene analogues as potent and selective 5-HT(2C) agonists for the treatment of metabolic disorders. Bioorg Med Chem Lett 21:34–37CrossRefPubMedGoogle Scholar
  61. 61.
    Davenport AJ, Moller C, Heifetz A, Mazanetz MP, Law RJ, Ebneth A, Gemkow MJ (2010) Using electrophysiology and in silico three-dimensional modeling to reduce human Ether-a-go-go related gene K(+) channel inhibition in a histamine H3 receptor antagonist program. Assay Drug Dev Technol 8:781–789CrossRefPubMedGoogle Scholar
  62. 62.
    Heifetz A, Morris GB, Biggin PC, Barker O, Fryatt T, Bentley J, Hallett D, Manikowski D, Pal S, Reifegerste R, Slack M, Law R (2012) Study of human Orexin-1 and -2 G-protein-coupled receptors with novel and published antagonists by modeling, molecular dynamics simulations, and site-directed mutagenesis. Biochemistry 51:3178–3197CrossRefPubMedGoogle Scholar
  63. 63.
    Barnoud J, Monticelli L (2015) Coarse-grained force fields for molecular simulations. Methods Mol Biol 1215:125–149CrossRefPubMedGoogle Scholar
  64. 64.
    Gutierrez-de-Teran H, Keranen H, Azuaje J, Rodriguez D, Aqvist J, Sotelo E (2015) Computer-aided design of GPCR ligands. Methods Mol Biol 1272:271–291CrossRefPubMedGoogle Scholar
  65. 65.
    Tummino PJ, Copeland RA (2008) Residence time of receptor-ligand complexes and its effect on biological function. Biochemistry 47:5481–5492CrossRefPubMedGoogle Scholar
  66. 66.
    Guo D, Hillger JM, IJzerman AP, Heitman LH (2014) Drug-target residence time—a case for G protein-coupled receptors. Med Res Rev 34:856–892CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  • Alexander Heifetz
    • 1
    • 2
    Email author
  • Michelle Southey
    • 1
  • Inaki Morao
    • 1
  • Andrea Townsend-Nicholson
    • 3
  • Mike J. Bodkin
    • 1
  1. 1.Evotec (UK) Ltd.AbingdonUK
  2. 2.Division of Biosciences, Research Department of Structural and Molecular BiologyInstitute of Structural and Molecular Biology, University College LondonLondonUK
  3. 3.Division of Biosciences, Research Department of Structural and Molecular BiologyUniversity College LondonLondonUK

Personalised recommendations