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Network Pharmacology and Epilepsy

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Antiepileptic Drug Discovery

Part of the book series: Methods in Pharmacology and Toxicology ((MIPT))

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Abstract

In contrast with the reductionist “one gene, one target, one drug” approach, network pharmacology proposes the use of multi-target therapies, a strategy that seems particularly suitable to treat disorders of complex etiology, among them epilepsy. As a matter of fact, most of the existing antiepileptic drugs are indeed multi-target unintended agents. Whereas a number of authors have recently advocated the use of network-based approximations in the antiepileptic drug discovery field, such strategy has so far not produced deliverables. Here, we review some practical considerations which could be used to assist in silico and wet screening for novel antiepileptic agents.

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References

  1. Sams-Dodd F (2005) Target-based drug discovery: is something wrong? Drug Discov Today 10:139–147

    Article  CAS  PubMed  Google Scholar 

  2. Hopkins AL (2008) Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 4:682–690

    Article  CAS  PubMed  Google Scholar 

  3. Kotz J (2012) Phenotypic screening, take two. SciBX 5:1–3

    Google Scholar 

  4. Talevi A, Bellera CL, Di Ianni E et al (2012) CNS drug development – lost in translation? Mini Rev Med Chem 12:959–970

    Article  CAS  PubMed  Google Scholar 

  5. Arrowsmith J (2011) Trial watch: Phase III and submission failures: 2007-2010. Nat Rev Drug Discov 10:87

    Article  CAS  PubMed  Google Scholar 

  6. Swinney DC, Anthony J (2011) How were new medicines discovered? Nat Rev Drug Discov 10:507–519

    Article  CAS  PubMed  Google Scholar 

  7. Margineanu DG (2012) Systems biology impact on antiepileptic drug discovery. Epilepsy Res 98:104–115

    Article  CAS  PubMed  Google Scholar 

  8. Margineanu DG (2014) Systems biology, complexity, and the impact on antiepileptic drug discovery. Epilepsy Behav 38:131–142

    Article  PubMed  Google Scholar 

  9. Loscher W, Klitgaard H, Twyman RE et al (2013) New avenues for ant-epileptic drug discovery and development. Nat Rev Drug Discov 12:757–776

    Article  PubMed  Google Scholar 

  10. Di Ianni ME, Talevi A (2014) How can network-pharmacology contribute to antiepileptic drug development? Mol Cell Epilepsy 1:e30

    Google Scholar 

  11. Bianchi MT, Pathmanathan J, Cash SS (2009) From ion channels to complex networks: magic bullet versus magic shotgun approaches to anticonvulsant pharmacotherapy. Med Hypotheses 72:297–305

    Article  CAS  PubMed  Google Scholar 

  12. Margineanu DG (2015) Neuropharmacology beyond reductionism – a likely prospect. Biosystems 141:1–9

    Article  PubMed  Google Scholar 

  13. Kamisnki RM, Matagne A, Patsalos PN et al (2009) Benefit of combination therapy in epilepsy: a review of the preclinical evidence with levetiracetam. Epilepsia 50:387–397

    Article  Google Scholar 

  14. Brodie MJ, Sills GJ (2011) Combining antiepileptic drugs – rational polytherapy? Seizure 20:369–375

    Article  PubMed  Google Scholar 

  15. Löscher W, Rundfelt C, Hönack D (1993) Low doses of NMDA receptor antagonists synergistically increase the anticonvulsant effect of the AMPA receptor antagonist NBQX in the kindling model of epilepsy. Eur J Neurosci 5:1545–1550

    Article  PubMed  Google Scholar 

  16. Brandt C, Nozadze M, Heuchert N et al (2010) Disease-modifying effects of phenobarbital and the NKCC1 inhibitor bumetanide in the pilocarpine model of temporal lobe epilepsy. J Neurosci 30:8602–8612

    Article  CAS  PubMed  Google Scholar 

  17. Hughes JP, Ress S, Kalindjian SB et al (2011) Principles of early drug discovery. Br J Pharmacol 162:1239–1249

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Jahromi SS, Pelletier MR, McDonald PJ et al (2000) Antiepileptic efficacy of topiramate: assessment in two in vitro seizure models. Brain Res 872:20–28

    Article  CAS  PubMed  Google Scholar 

  19. Ohno K, Higashima M (2002) Effects of antiepileptic drugs on afterdischarge generation in rat hippocampal slices. Brain Res 924:39–45

    Article  CAS  PubMed  Google Scholar 

  20. Shin DS, Yu W, Sutton A (2011) Isovaline, a rare amino acid, has anticonvulsant properties in two in vitro hippocampal seizure models by increasing interneuronal. Epilepsia 52:2084–2093

    Article  CAS  PubMed  Google Scholar 

  21. Kombian SB, Phillips OA (2013) Novel actions of oxazolidinones: in vitro screening of a triazolyloxazolidinone for anticonvulsant activity. Med Princ Pract 22:340–345

    Article  PubMed  Google Scholar 

  22. Jones RS, da Silva AB, Whittaker RG et al (2016) Human brain slices for epilepsy research: pitfalls, solutions and future challenges. J Neurosci Methods 260:221–232

    Article  PubMed  Google Scholar 

  23. Löscher W, Schmidt D (2011) Modern antiepileptic drug development has failed to deliver: ways out of the current dilemma. Epilepsia 52:657–678

    Article  PubMed  Google Scholar 

  24. Milan JL (2014) On ‘polypharmacy’ and multi-target agents, complementary strategies for improving the treatment of depression: a comparative appraisal. Int J Neuropsychopharmacol 17:1009–1037

    Article  Google Scholar 

  25. Talevi A, Bruno-Blanch LE (2012) In: Rocha L, Cavalheiro EA (eds) Pharmacoresistance in epilepsy. From genes and molecules to promising therapies, 1st edn. Springer, New York, NY

    Google Scholar 

  26. Vezzani A, French J, Bartfai T et al (2011) The role of inflammation in epilepsy. Nat Rev Neurol 7:31–40

    Article  CAS  PubMed  Google Scholar 

  27. Vezzani A, Friedman A, Dingledine RJ (2013) The role of inflammation in epileptogenesis. Neuropharmacology 69:16–34

    Article  CAS  PubMed  Google Scholar 

  28. Ximenes JC, de Oliveira Gonçalves D, Siqueira RM et al (2013) Valproic acid: an anticonvulsant drug with potent antinociceptive and anti-inflammatory properties. Naunym Schmiedebergs Arch Pharmacol 386:575–587

    Article  CAS  Google Scholar 

  29. Vuilleumier P, Jallon P (1998) Epilepsy and psychiatric disorders: epidemiological data. Rev Neurol 154:305–317

    CAS  PubMed  Google Scholar 

  30. Dalmagro CL, Velasco TR, Bianchin MM et al (2012) Psychiatric comorbidity in refractory focal epilepsy: a study of 490 patients. Epilepsy Behav 25:593–597

    Article  PubMed  Google Scholar 

  31. Morphy R, Kay C, Rankovic Z (2004) From magic bullets to designed multiple ligands. Drug Discov Today 9:641–665

    Article  CAS  PubMed  Google Scholar 

  32. Ma X, Shi Z, Tan C et al (2010) In silico approaches to multi-target drug design: computer-aided multi-target drug design, multi-target virtual screening. Curr Pharm Res 27:739–744

    Article  CAS  Google Scholar 

  33. Talevi A (2015) Multi-target pharmacology: possibilities and limitations of the “skeleton key approach” from a medicinal chemist perspective. Front Pharmacol 6:205

    Article  PubMed  PubMed Central  Google Scholar 

  34. Lipisnki CA, Lombardo F, Dominy BW et al (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26

    Article  Google Scholar 

  35. Veber DF, Johnson SR, Cheng HY et al (2002) Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 45:2615–2623

    Article  CAS  PubMed  Google Scholar 

  36. Wager TT, Hou X, Verhoest PR et al (2010) Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci 1:435–449

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kuntz ID, Chen K, Sharp KA et al (1999) The maximal affinity of ligands. Proc Natl Acad Sci 96:9997–10002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hopkins AL, Keserú GM, Leeson PD et al (2014) The role of ligand efficiency metrics in drug discovery. Nat Rev Drug Discov 13:105–121

    Article  CAS  PubMed  Google Scholar 

  39. Sturm N, Desaphy J, Quinn RJ et al (2012) Structural insights into the molecular basis of the ligand promiscuity. J Chem Inf Model 52:2410–2421

    Article  CAS  PubMed  Google Scholar 

  40. Cases M, Mestres J (2009) A chemogenomic approach to drug discovery: focus on cardiovascular diseases. Drug Discov Today 14:479–485

    Article  CAS  PubMed  Google Scholar 

  41. Hu Y, Gupta-Ostermann D, Bajorath J (2014) Exploring compound promiscuity patterns and multi-target activity spaces. Comput Struct Biotechnol 9:e201401003

    Google Scholar 

  42. Azzaoui K, Hamon H, Faller B et al (2007) Modeling promiscuity based on in vitro safety pharmacology profiling data. ChemMedChem 2:874–880

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  44. Yang Y, Chen H, Nilsson I et al (2010) Investigation of the relationship between topology and selectivity for druglike molecules. J Med Chem 53:7709–7714

    Article  CAS  PubMed  Google Scholar 

  45. Bernis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular framework. J Med Chem 39:2887–2893

    Article  Google Scholar 

  46. Talevi A, Bellera CL, Castro EA et al (2007) A successful virtual screening application: prediction of anticonvulsant activity in MES test of widely used pharmaceutical and food preservatives methylparaben and propylparaben. J Comput Aided Mol Des 21:527–538

    Article  CAS  PubMed  Google Scholar 

  47. Leeson PD, St-Gallay SA (2011) The influence of the ‘organizational factor’ on compound quality in drug discovery. Nat Rev Drug Discov 10:749–765

    Article  CAS  PubMed  Google Scholar 

  48. Talevi A (2016) Tailored multi-target agents. Applications and design considerations. Curr Pharm Des 22: 3164–3170

    Google Scholar 

  49. Juan D, Pazos F, Valencia A (2013) Emerging methods in protein co-evolution. Nat Rev Gen 14:249–261

    Article  Google Scholar 

  50. Csernely P, Korcsmárosa T, Kissa HJM et al (2013) Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol Ther 138:333–408

    Article  Google Scholar 

  51. Zheng H, Fridkin M, Youdim M (2014) From single target to multitarget/network therapeutics in Alzheimer’s therapy. Pharmaceuticals 7:113–135

    Article  PubMed  PubMed Central  Google Scholar 

  52. Lipton SA (2006) Paradigm shift in neuroprotection by NMDA receptor blockade: memantine and beyond. Nat Rev Drug Discov 5:160–170

    Article  CAS  PubMed  Google Scholar 

  53. Rammes G, Rupprecht R, Ferrari U et al (2001) The N-methyl-D-aspartate receptor channel blockers memantine, MRZ 2/579 and other amino-alkyl-cyclohexanes antagonize 5-HT(3) receptor currents in cultured HEK-293 and N1E-115 cell systems in a non-competitive manner. Neurosci Lett 306:81–84

    Article  CAS  PubMed  Google Scholar 

  54. Seeman P, Caruso C, Lasaga M (2008) Memantine agonist action at dopamine D2High receptors. Synapse 62:149–153

    Article  CAS  PubMed  Google Scholar 

  55. Stables JP, Kupferberg HJ. The NIH Anticonvulsant Drug Development (ADD) Program: preclinical anticonvulsant screening project. http://www.ninds.nih.gov/research/asp/addadd_review.pdf. Assessed on Mar 2016

  56. Löscher W (2011) Critical review of current animal models of seizures and epilepsy used in the discovery and development of new antiepileptic drugs. Seizure 20:359–368

    Article  PubMed  Google Scholar 

  57. Langer T, Bryant SD (2008) 3D quantitative structure-property relationships. In: The practice of medicinal chemistry, 3rd edn. Academic, London

    Google Scholar 

  58. Sippl W (2010) 3D QSAR: applications, recent advances, and limitations. In: Recent advances in QSAR studies. Method and applications, 1st edn. Springer, Dordrecht

    Google Scholar 

  59. Roy K, Kar S, Das RN (2015) Background of QSAR and historical developments. In: Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment, 1st edn. Academic, London

    Google Scholar 

  60. Shen M, LeTiran A, Xiao Y et al (2002) Quantitative structure–activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods. J Med Chem 45:2811–2823

    Article  CAS  PubMed  Google Scholar 

  61. Tasso SM, Moon SC, Bruno-Blanch LE et al (2004) Characterization of anticonvulsant profile of valpromide derivatives. Bioorg Med Chem 12:3857–3869

    Article  CAS  PubMed  Google Scholar 

  62. Talevi A, Enrique AV, Bruno-Blanch LE (2012) Anticonvulsant activity of artificial sweeteners: a structural link between sweet-taste receptor T1R3 and brain glutamate receptors. Bioorg Med Chem Lett 22:4072–4074

    Article  CAS  PubMed  Google Scholar 

  63. Sutherland JJ, Weaver DF (2003) Development of quantitative structure–activity relationships and classification models for anticonvulsant activity of hydantoin analogues. J Chem Inf Model 43:1028–1036

    CAS  Google Scholar 

  64. Gavernet L, Domínguez-Cabrera MJ, Bruno-Blanch LE et al (2007) 3D QSAR design of novel antiepileptic sulfamides. Bioorg Med Chem 2007:1556–1567

    Article  Google Scholar 

  65. Gavernet L, Talevi A, Castro EA et al (2008) A combined virtual screening 2D and 3D QSAR methodology for the selection of new anticonvulsant candidates from a natural product library. QSAR Comb Sci 27:1120–1129

    Article  CAS  Google Scholar 

  66. Di Ianni ME, Enrique AV, Palestro PH et al (2012) Several new diverse anticonvulsant agents discovered in a virtual screening campaign aimed at novel antiepileptic drugs to treat refractory epilepsy. J Chem Inf Model 52:3325–3330

    Article  PubMed  Google Scholar 

  67. Bruno-Blanch L, Gálvez J, García-Domenech R (2003) Topological virtual screening: a way to find new anticonvulsant drugs from chemical diversity. Bioorg Med Chem Lett 13:2749–2754

    Article  CAS  PubMed  Google Scholar 

  68. Talevi A, Cravero MS, Castro EA et al (2007) Discovery of anticonvulsant activity of abietic acid through application of linear discriminant analysis. Bioorg Med Chem Lett 17:1684–1690

    Article  CAS  PubMed  Google Scholar 

  69. Di Ianni ME, Del Valle ME, Enrique AV et al (2015) Computer-aided identification of anticonvulsant effect of natural nonnutritive sweeteners stevioside and rebaudioside A. Assay Drug Dev Technol 13:313–318

    Article  PubMed  PubMed Central  Google Scholar 

  70. Talevi A, Prieto JJ, Bruno-Blanch LE et al (2007) New similarity-based algorithm and its application to classification of anticonvulsant compounds. J Enzyme Inhib Med Chem 22:253–265

    Article  CAS  PubMed  Google Scholar 

  71. Qu XA, Rajpal DK (2012) Applications of connectivity map in drug discovery and development. Drug Discov Today 17:1289–1298

    Article  CAS  PubMed  Google Scholar 

  72. Lamb J, Crawford ED, Peck D et al (2006) The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313:1929–1935

    Article  CAS  PubMed  Google Scholar 

  73. Elliot RC, Miles MF, Lowestein DH (2003) Overlapping microarray profiles of dentate gyrus gene expression during development- and epilepsy-associated neurogenesis and axon outgrowth. J Neurosci 23:2218–2227

    Google Scholar 

  74. Newton SS, Collier EF, Hunsberger J et al (2003) Gene profile of electroconvulsive seizures: induction of neurotrophic and angiogenic factors. J Neurosci 23:10841–10851

    CAS  PubMed  Google Scholar 

  75. Hunsberger JG, Bennett AH, Selvanayagam E et al (2005) Gene profiling the response to kainic acid induced seizures. Mol Brain Res 141:95–112

    Article  CAS  PubMed  Google Scholar 

  76. Borges K, Shaw R, Dingledine R (2007) Gene expression changes after seizure preconditioning in the three major hippocampal cell layers. Neurobiol Dis 26:66–77

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Theilhaber J, Rakhade SN, Sudhalter J et al (2013) Gene expression profiling of a hypoxic seizure model of epilepsy suggests a role for mTOR and Wnt signaling in epileptogenesis. PLoS One 8:e74428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The author work is supported by Agencia Nacional de Promoción Científica y Tecnológica (PICT 2013-3175), CONICET, and Universidad Nacional de La Plata (Incentivos UNLP).

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Authors and Affiliations

  1. Laboratorio de Investigación y Desarrollo de Bioactivos (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), 47 & 115, La Plata, Buenos Aires, Argentina

    Alan Talevi

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Correspondence to Alan Talevi .

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  1. Laboratorio de Investigación y Desarrollo de Bioactivos (LIDeB) Faculty of Exact Sciences, National University of La Plata, La Plata, Buenos Aires, Argentina

    Alan Talevi

  2. Department of Pharmacobiology, Center for Research and Advanced Studies, Mexico City, Mexico

    Luisa Rocha

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Talevi, A. (2016). Network Pharmacology and Epilepsy. In: Talevi, A., Rocha, L. (eds) Antiepileptic Drug Discovery. Methods in Pharmacology and Toxicology. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6355-3_18

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  • DOI: https://doi.org/10.1007/978-1-4939-6355-3_18

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6353-9

  • Online ISBN: 978-1-4939-6355-3

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