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Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting

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Abstract

Human Dopamine Receptor D4 (DRD4) orchestrates several neurological functions and represents a target for many psychological disorders. Here, we examined two rare variants in DRD4; V194G and R237L, which elicit functional alterations leading to disruption of ligand binding and G protein coupling, respectively. Using atomistic molecular dynamics (MD) simulations, we provide in-depth analysis to reveal structural signatures of wild and mutant complexes with their bound agonist and antagonist ligands. We constructed intra-protein network graphs to discriminate the global conformational changes induced by mutations. The simulations also allowed us to elucidate the local side-chain dynamical variations in ligand-bound mutant receptors. The data suggest that the mutation in transmembrane V (V194G) drastically disrupts the organization of ligand binding site and causes disorder in the native helical arrangement. Interestingly, the R237L mutation leads to significant rewiring of side-chain contacts in the intracellular loop 3 (site of mutation) and also affects the distant transmembrane topology. Additionally, these mutations lead to compact ICL3 region compared to the wild type, indicating that the receptor would be inaccessible for G protein coupling. Our findings thus reveal unreported structural determinants of the mutated DRD4 receptor and provide a robust framework for design of effective novel drugs.

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References

  1. Li Y, Hou T, Goddard I (2010) Computational modeling of structure-function of G protein-coupled receptors with applications for drug design. Current Medicinal Chemistry 17:1167–1180

    Article  CAS  Google Scholar 

  2. Juyal RC, Das M, Punia S, Behari M, Nainwal G, et al. (2006) Genetic susceptibility to Parkinson’s disease among south and north Indians: I. Role of polymorphisms in dopamine receptor and transporter genes and association of DRD4 120-bp duplication marker. Neurogenetics 7:223–229

    Article  CAS  Google Scholar 

  3. Seeman P, Guan HC, Van Tol HH (1993) Dopamine D4 receptors elevated in schizophrenia. Nature 365:441–445

    Article  CAS  Google Scholar 

  4. Pritchard AL, Ratcliffe L, Sorour E, Haque S, Holder R, et al. (2009) Investigation of dopamine receptors in susceptibility to behavioural and psychological symptoms in Alzheimer’s disease. International Journal of Geriatric Psychiatry 24:1020–1025

    Article  Google Scholar 

  5. Pavese N, Andrews TC, Brooks DJ, Ho AK, Rosser AE, et al. (2003) Progressive striatal and cortical dopamine receptor dysfunction in Huntington’s disease: a PET study. Brain 126:1127–1135

    Article  Google Scholar 

  6. Probst WC, Snyder LA, Schuster DI, Brosius J, Sealfon SC (1992) Sequence alignment of the G protein-coupled receptor superfamily. DNA and Cell Biology 11:1–20

    Article  CAS  Google Scholar 

  7. Tuteja N (2009) Signaling through G protein coupled receptors. Plant Signaling & Behavior 4:942–947

    Article  CAS  Google Scholar 

  8. Chien EY, Liu W, Zhao Q, Katritch V, Han GW, et al. (2010) Structure of the human dopamine D3 receptor in complex with a D2/D3 selective antagonist. Science 330:1091–1095

    Article  CAS  Google Scholar 

  9. Missale C, Nash SR, Robinson SW, Jaber M, Caron MG (1998) Dopamine receptors: from structure to function. Physiological Reviews 78:189–225

    CAS  Google Scholar 

  10. Beaulieu JM, Gainetdinov RR (2011) The physiology, signaling, and pharmacology of dopamine receptors. Pharmacological Reviews 63:182–217

    Article  CAS  Google Scholar 

  11. Jatana N, Thukral L, Latha N (2015) Structure and dynamics of DRD4 bound to an agonist and an antagonist using in silico approaches. Proteins: Structure, Function, and Bioinformatics 83:867–880

    Article  CAS  Google Scholar 

  12. Shaikh S, Collier D, Sham P, Pilowsky L, Sharma T, et al. (1995) Analysis of clozapine response and polymorphisms of the dopamine D4 receptor gene (DRD4) in schizophrenic patients. American Journal of Medical Genetics 60:541–545

    Article  CAS  Google Scholar 

  13. Wong AH, Buckle CE, Van Tol HH (2000) Polymorphisms in dopamine receptors: what do they tell us? European Journal of Pharmaceutics and Biopharmaceutics 410:183–203

    CAS  Google Scholar 

  14. Van Tol HH, Wu CM, Guan HC, Ohara K, Bunzow JR, et al. (1992) Multiple dopamine D4 receptor variants in the human population. Nature 358:149–152

    Article  CAS  Google Scholar 

  15. Ding YC, Chi HC, Grady DL, Morishima A, Kidd JR, et al. (2002) Evidence of positive selection acting at the human dopamine receptor D4 gene locus. Proceedings of the National Academy of Sciences 99:309–314

    Article  CAS  Google Scholar 

  16. Chang FM, Kidd JR, Livak KJ, Pakstis AJ, Kidd KK (1996) The world-wide distribution of allele frequencies at the human dopamine D4 receptor locus. Human Genetics 98:91–101

    Article  CAS  Google Scholar 

  17. Wang E, Ding YC, Flodman P, Kidd J, Kidd K, et al. (2004) The genetic architecture of selection at the human dopamine receptor D4 (DRD4) gene locus. American Journal of Human Genetics 74:931–944

    Article  CAS  Google Scholar 

  18. Asghari V, Sanyal S, Buchwaldt S, Paterson A, Jovanovic V, et al. (1995) Modulation of intracellular cyclic AMP levels by different human dopamine D4 receptor variants. Journal of Neurochemistry 65:1157–1165

    Article  CAS  Google Scholar 

  19. Liu I, Seeman P, Sanyal S, Ulpian C, Rodgers-Johnson PE (1996) Dopamine D4 receptor variant in Africans D4valinel94glycine, is insensitive to dopamine and clozapine: report of a homozygous individual. American Journal of Medical Genetics 61:277–282

    Article  CAS  Google Scholar 

  20. Seeman P, Ulpian C, Chouinard G, Van Tol H, Dwosh H, et al. (1994) Dopamine D4 receptor variant, D4 glycine194, in Africans, but not in Caucasians: no association with schizophrenia. American Journal of Medical Genetics 54:384–390

    Article  CAS  Google Scholar 

  21. Michealraj K, Jatana N, Jafurulla M, Narayanan L, Chattopadhyay A, et al. (2014) Functional characterization of rare variants in human dopamine receptor D4 gene by genotype–phenotype correlations. Neuroscience 262:176–189

    Article  CAS  Google Scholar 

  22. Eswar N, Webb B, Marti-Renom MA, Madhusudhan M, Eramian D, et al. (2006) Comparative protein structure modeling using modeller. Current Protocols in Bioinformatics Chapter 5: Unit 5:6

    Google Scholar 

  23. Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) Novel procedure for modeling ligand/receptor induced fit effects. Journal of Medicinal Chemistry 49:534–553

    Article  CAS  Google Scholar 

  24. Schrödinger S (2012) Induced fit docking protocol; glide version 5.8, prime version 3.1. Schrödinger, LLC, New York

    Google Scholar 

  25. Sastry GM, Adzhigirey M, Day T, Annabhimoju R, Sherman W (2013) Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. Journal of Computer-Aided Molecular Design 27:221–234

    Article  Google Scholar 

  26. LigPrep (2012) Version 2.5,. Schrödinger. LLC, New York

    Google Scholar 

  27. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, et al. (2006) Scalable algorithms for molecular dynamics simulations on commodity clusters. In: SC 2006 Conference, Proceedings of the ACM/IEEE, IEEE, pp 43–43

  28. Jorgensen WL, Maxwell DS, Tirado-Rives J (1996) Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. Journal of the American Chemical Society 118:11225–11236

    Article  CAS  Google Scholar 

  29. Jorgensen WL, Madura JD (1985) Temperature and size dependence for Monte Carlo simulations of TIP4P water. Molecular Physics 56:1381–1392

    Article  CAS  Google Scholar 

  30. Liu DC, Nocedal J (1989) On the limited memory BFGS method for large-scale optimization. Math Program 45:503–528

    Article  Google Scholar 

  31. Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics 81:3684–3690

    Article  CAS  Google Scholar 

  32. Darden T, York D, Pedersen L (1993) Particle mesh Ewald: An n log (n) method for Ewald sums in large systems. The Journal of Chemical Physics 98:10089–10092

    Article  CAS  Google Scholar 

  33. Doncheva NT, Klein K, Domingues FS, Albrecht M (2011) Analyzing and visualizing residue networks of protein structures. Trends in Biochemical Sciences 36:179–182

    Article  CAS  Google Scholar 

  34. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13:2498–2504

    Article  CAS  Google Scholar 

  35. DeLano WL (2002) The PyMOL molecular graphics system. DeLano Scientific, San Carlos

    Google Scholar 

  36. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. Journal of Molecular Graphics 14:33–38

    Article  CAS  Google Scholar 

  37. Maestro (2012) Version 9.3, schrödinger, llc. New York

  38. Allain A, de Beauchêne IC, Langenfeld F, Guarracino Y, Laine E, et al. (2014) Allosteric pathway identification through network analysis: from molecular dynamics simulations to interactive 2D and 3D graphs. Faraday Discussions 169:303– 321

    Article  CAS  Google Scholar 

  39. Case D, Darden T, Cheatham III T, Simmerling C, Wang J, et al. (2012) Amber 13. University of California, San Francisco

    Google Scholar 

  40. Chennubhotla C, Bahar I (2007) Signal propagation in proteins and relation to equilibrium fluctuations. PLoS Computational Biology 3:1716–1726

    CAS  Google Scholar 

  41. Wallace AC, Laskowski RA, Thornton JM (1995) Ligplot: a program to generate schematic diagrams of protein–ligand interactions. Protein Engineering 8:127–134

    Article  CAS  Google Scholar 

  42. Bastian M, Heymann S, Jacomy M, et al. (2009) Gephi: an open source software for exploring and manipulating networks. ICWSM 8:361–362

    Google Scholar 

  43. Hayes JM, Skamnaki VT, Archontis G, Lamprakis C, Sarrou J, et al. (2011) Kinetics, in silico docking, molecular dynamics, and mm-gbsa binding studies on prototype indirubins, KT5720, and staurosporine as phosphorylase kinase ATP-binding site inhibitors: the role of water molecules examined. Proteins: Structure, Function, and Bioinformatics 79:703–719

    Article  CAS  Google Scholar 

  44. Adasme-Carreño F, Muñoz-Gutierrez C, Caballero J, Alzate-Morales JH (2014) Performance of the MM/GBSA scoring using a binding site hydrogen bond network-based frame selection: the protein kinase case. Physical Chemistry Chemical Physics 16:14047–14058

    Article  Google Scholar 

  45. Prime (2012) Version 3.1, schrödinger, llc. version 31, Schrödinger. LLC, New York

    Google Scholar 

  46. Li J, Abel R, Zhu K, Cao Y, Zhao S, et al. (2011) The vsgb 2.0 model: a next-generation energy model for high-resolution protein structure modeling. Proteins: Structure, Function, and Bioinformatics 79:2794–2812

    Article  CAS  Google Scholar 

  47. Rastelli G, Rio AD, Degliesposti G, Sgobba M (2010) Fast and accurate predictions of binding free energies using MM-PBSA and MM-GBSA. Journal of Computational Chemistry 31:797– 810

    CAS  Google Scholar 

  48. Berezin C, Glaser F, Rosenberg J, Paz I, Pupko T, et al. (2004) Conseq: the identification of functionally and structurally important residues in protein sequences. Bioinformatics 20:1322–1324

    Article  CAS  Google Scholar 

  49. Celniker G, Nimrod G, Ashkenazy H, Glaser F, Martz E, et al. (2013) Consurf: using evolutionary data to raise testable hypotheses about protein function. Israel Journal of Chemistry 53:199–206

    Article  CAS  Google Scholar 

  50. Venkatakrishnan A, Deupi X, Lebon G, Tate CG, Schertler GF, et al. (2013) Molecular signatures of G-protein-coupled receptors. Nature 494:185–194

    Article  CAS  Google Scholar 

  51. Feng Z, Hou T, Li Y (2012) Selectivity and activation of dopamine D3R from molecular dynamics. Journal of Molecular Modeling 18:5051–5063

    Article  CAS  Google Scholar 

  52. Oak JN, Oldenhof J, Van Tol HH (2000) The dopamine d(4) receptor: one decade of research. European Journal of Pharmacology: Molecular Pharmacology 405:303– 327

    Article  CAS  Google Scholar 

  53. Kalani MYS, Vaidehi N, Hall SE, Trabanino RJ, Freddolino PL, et al. (2004) The predicted 3D structure of the human D2 dopamine receptor and the binding site and binding affinities for agonists and antagonists. In: Proceedings of the National Academy of Sciences of the United States of America, vol 101, pp 3815– 3820

  54. Kling RC, Lanig H, Clark T, Gmeiner P (2013) Active-state models of ternary GPCR complexes: determinants of selective receptor-G-protein coupling. PloS one 8:e67244

    Article  CAS  Google Scholar 

  55. Goddard WA, Abrol R (2007) 3-dimensional structures of G protein-coupled receptors and binding sites of agonists and antagonists. The Journal of Nutrition 137:1528S–1538S

    CAS  Google Scholar 

  56. Chemel BR, Bonner LA, Watts VJ, Nichols DE (2012) Ligand-specific roles for transmembrane 5 serine residues in the binding and efficacy of dopamine D1 receptor catechol agonists. Molecular Pharmacology 81:729–738

    Article  CAS  Google Scholar 

  57. Schmidt WJ, Reith ME (2005) Dopamine and glutamate in psychiatric disorders. Springer

  58. Jacobson KA, Costanzi S, Paoletta S (2014) Computational studies to predict or explain G protein-coupled receptor polypharmacology. Trends in Pharmacological Sciences 35:658– 663

    Article  CAS  Google Scholar 

  59. Ballesteros JA, Weinstein H (1995) Integrated methods for the construction of three-dimensional models and computational probing of structure–function relations in G protein-coupled receptors. Methods in Neurosciences 25:366–428

    Article  CAS  Google Scholar 

  60. Laine E, Auclair C, Tchertanov L (2012) Allosteric communication across the native and mutated kit receptor tyrosine kinase. PLoS Computational Biology 8:e1002661–e1002661

    Article  CAS  Google Scholar 

  61. de Beauchêne IC, Allain A, Panel N, Laine E, Trouvé A, et al. (2014) Hotspot mutations in kit receptor differentially modulate its allosterically coupled conformational dynamics: impact on activation and drug sensitivity. PLoS Computational Biology 10:e1003749

    Article  Google Scholar 

  62. Trzaskowski B, Latek D, Yuan S, Ghoshdastider U, Debinski A, et al. (2012) Action of molecular switches in GPCRs-theoretical and experimental studies. Current Medicinal Chemistry 19:1090– 1109

    Article  CAS  Google Scholar 

  63. Unal H, Karnik SS (2012) Domain coupling in GPCRs: the engine for induced conformational changes. Trends in Pharmacological Sciences 33:79–88

    Article  CAS  Google Scholar 

  64. Katritch V, Cherezov V, Stevens RC (2012) Diversity and modularity of G protein-coupled receptor structures. Trends in Pharmacological Sciences 33:17–27

    Article  CAS  Google Scholar 

  65. Rasmussen SG, DeVree BT, Zou Y, Kruse AC, Chung KY, et al. (2011) Crystal structure of the β2 adrenergic receptor-Gs protein complex. Nature 477:549–555

    Article  CAS  Google Scholar 

  66. Jaakola VP, Prilusky J, Sussman JL, Goldman A (2005) G protein-coupled receptors show unusual patterns of intrinsic unfolding. Protein Engineering, Design & Selection 18:103–110

    Article  CAS  Google Scholar 

  67. Gsponer J, Madan Babu M (2009) The rules of disorder or why disorder rules. Progress in Biophysics and Molecular Biology 99:94–103

    Article  CAS  Google Scholar 

  68. Babu MM, Kriwacki RW, Pappu RV (2012) Versatility from protein disorder. Science 337:1460–1461

    Article  CAS  Google Scholar 

  69. Goetz A, Lanig H, Gmeiner P, Clark T (2011) Molecular dynamics simulations of the effect of the G-protein and diffusible ligands on the β2-adrenergic receptor. Journal of Molecular Biology 414:611–623

    Article  CAS  Google Scholar 

  70. Baker JG, Hill SJ (2007) Multiple GPCR conformations and signalling pathways: implications for antagonist affinity estimates. Trends in Pharmacological Sciences 28:374–381

    Article  CAS  Google Scholar 

  71. Hermans E (2003) Biochemical and pharmacological control of the multiplicity of coupling at G-protein-coupled receptors. Pharmacology & Therapeutics 99:25–44

    Article  CAS  Google Scholar 

  72. Maudsley S, Martin B, Luttrell LM (2005) The origins of diversity and specificity in G protein-coupled receptor signaling. The Journal of Pharmacology and Experimental Therapeutics 314:485–494

    Article  CAS  Google Scholar 

  73. Ptáček R, Kuželová H, Stefano GB (2011) Dopamine D4 receptor gene DRD4 and its association with psychiatric disorders. Medical Science Monitor 17:RA215–220

    Google Scholar 

  74. López León S, Croes EA, Sayed-Tabatabaei FA, Claes S, Broeckhoven CV, et al. (2005) The dopamine D4 receptor gene 48-base-pair-repeat polymorphism and mood disorders: a meta-analysis. Biological Psychiatry 57:999–1003

    Article  Google Scholar 

  75. Smalley S, Bailey J, Palmer C, Cantwell D, McGough J, et al. (1998) Evidence that the dopamine D4 receptor is a susceptibility gene in attention deficit hyperactivity disorder. Molecular Psychiatry 3:427–430

    Article  CAS  Google Scholar 

  76. Grice D, Leckman J, Pauls D, Kurlan R, Kidd K, et al. (1996) Linkage disequilibrium between an allele at the dopamine D4 receptor locus and Tourette syndrome, by the transmission-disequilibrium test. American Journal of Human Genetics 59:644–652

    CAS  Google Scholar 

  77. Kenakin TP (2012) Biased signalling and allosteric machines: new vistas and challenges for drug discovery. British Journal of Pharmacology 165:1659–1669

    Article  CAS  Google Scholar 

  78. Wieland K, Zuurmond HM, Krasel C, Ijzerman AP, Lohse MJ (1996) Involvement of Asn-293 in stereospecific agonist recognition and in activation of the beta 2-adrenergic receptor. In: Proceedings of the National Academy of Sciences, vol 93, pp 9276–9281

  79. Kobilka BK (2007) G protein coupled receptor structure and activation. Biochimica et Biophysica Acta (BBA) - Biomembranes 1768:794–807

    Article  CAS  Google Scholar 

  80. O’Dowd BF, Hnatowich M, Regan J, Leader WM, Caron M, et al. (1988) Site-directed mutagenesis of the cytoplasmic domains of the human beta 2-adrenergic receptor. localization of regions involved in G protein-receptor coupling. The Journal of Biological Chemistry 263:15985–15992

    Google Scholar 

  81. Liggett S, Caron M, Lefkowitz R, Hnatowich M (1991) Coupling of a mutated form of the human beta 2-adrenergic receptor to Gi and Gs. requirement for multiple cytoplasmic domains in the coupling process. The Journal of Biological Chemistry 266:4816–4821

    CAS  Google Scholar 

  82. Guan HC, Sunahara RK (1991) Cloning of the gene for a human dopamine D4 receptor with high affinity for the antipsychotic clozapine. Nature 350:610–614

    Article  Google Scholar 

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Acknowledgments

This work was supported by funding from the Department of Biotechnology, Ministry of Science and Technology, Government of India. LT was funded by INSPIRE Faculty Fellowship from Department of Science and Technology. NJ is thankful to University Grants Commission for providing a fellowship.

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Correspondence to Lipi Thukral or N. Latha.

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Jatana, N., Thukral, L. & Latha, N. Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting. J Mol Model 22, 14 (2016). https://doi.org/10.1007/s00894-015-2868-x

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