Computational approaches for innovative antiepileptic drug discovery

References

• World Health Organization. Fact sheet 999: Epilepsy. [Updated 2016 Feb].
   Google Scholar
• Sills G, Butler E, Thompson GG, et al. Vigabatrin and tiagabine are pharmacologically different drugs. A pre-clinical study. Seizure. 1999;8:404–411. doi:10.1053/seiz.1999.0326.
   PubMed Web of Science ®Google Scholar
• Löscher W, Schmidt D. Modern antiepileptic drug development has failed to deliver: ways out of the current dilemma. Epilepsia. 2011;52:657–678. doi:10.1111/j.1528-1167.2011.03024.x.
   PubMed Web of Science ®Google Scholar
• Sholvon SD. Drug treatment of epilepsy in the century of the ILAE: the second 50 years, 1959-2009. Epilepsia. 2009;50(Suppl. 3):93–130. doi:10.1111/j.1528-1167.2009.02042.x.
   PubMed Web of Science ®Google Scholar
• Löscher W, Klitgaard H, Twyman RE, et al. New avenues for anti-epileptic drug discovery and development. Nat Rev Drug Discov. 2013;12:757–776. doi:10.1038/nrd4126.
   PubMed Web of Science ®Google Scholar
• Khan HN, Rashid H, Kulsoom S. Homology modeling of ɣ-aminobutyrateaminotransferase, a pyridoxal phosphate-dependent enzyme of Homo sapiens: molecular modeling approach to rational drug design against epilepsy. Af J Biotechnol. 2013;10:5916–5926.
   Google Scholar
• Baglo Y, Gabrielsen M, Sylte I, et al. Homology modeling of human γ-butyric acid transporters and the binding of pro-drugs 5-aminolevulinic acid and methyl aminolevulinic acid used in photodynamic. PLoS One. 2013;8:e65200. doi:10.1371/journal.pone.0065200.
   Google Scholar
• Lee J, Daniels V, Sands ZA, et al. Exploring the interaction of SV2A with racetams using homology modelling, molecular dynamics and site-directed mutagenesis. PLoS One. 2015;10:e0116589. doi:10.1371/journal.pone.0116589.
   Google Scholar
• Temperini C, Innocenti A, Mastrolorenzo A, et al. Carbonic anhydrase inhibitors. Interaction of the antiepileptic drug sulthiame with twelve mammalian isoforms: kinetic and X-ray crystallographic studies. Bioorg Med Chem Lett. 2008;17:4866–4872. doi:10.1016/j.bmcl.2007.06.044.
   Web of Science ®Google Scholar
• De Luca L, Ferro S, Damiano FM, et al. Structure-based screening for the discovery of new carbonic anhydrase VII inhibitors. Eur J Med Chem. 2014;71:105–111. doi:10.1016/j.ejmech.2013.10.071.
   PubMed Web of Science ®Google Scholar
• Liu T, Zhou L, Wang T, et al. Toward the identification of novel carbonic anhydrase XIV inhibitors using 3D-QSAR pharmacophore model, virtual screening and molecular docking study. Lett Drug Des Discov. 2014;11:403–412. doi:10.2174/15701808113106660083.
   Web of Science ®Google Scholar
• Villalba ML, Palestro P, Ceruso M, et al. Sulfamide derivatives with selective carbonic anhydrase VII inhibitory action. Bioorg Med Chem. 2016;24:894–901. doi:10.1016/j.bmc.2016.01.012.
   PubMed Web of Science ®Google Scholar
• Sams-Dodd F. Target-based drug discovery: is something wrong? Drug Discov Today. 2005;10:139–147. doi:10.1016/S1359-6446(04)03316-1.
   PubMed Web of Science ®Google Scholar
• Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol. 2008;4:682–690. doi:10.1038/nchembio.118.
   PubMed Web of Science ®Google Scholar
• Kotz J. Phenotypic screening, take two. SciBX. 2012;5:1–3.
   Google Scholar
• Talevi A, Bellera CL, Di Ianni ME, et al. CNS drug development – lost in translation? Mini Rev Med Chem. 2012;12:959–970.
   PubMed Web of Science ®Google Scholar
• Arrowsmith J. Trial watch: phase III and submission failures: 2007-2010. Nat Rev Drug Discov. 2011;10:82. doi:10.1038/nrd3375.
   PubMed Web of Science ®Google Scholar
• Swinney DC, Anthony J. How were new medicines discovered? Nat Rev Drug Discov. 2011;10:507–519. doi:10.1038/nrd3480.
   PubMed Web of Science ®Google Scholar
• Potiga (Ezogabine): drug safety communication – linked to retinal abnormalities and blue skin discoloration. [cited 2016 Jul]. Available from: http://www.fda.gov/Safety/MedWatch/SafetyInformation/SafetyAlertsforHumanMedicalProducts/ucm349847.htm.
   Google Scholar
• Retigabine (Trobalt): indication restricted to last-line use and new monitoring requirements. [Cited 2016 Jul]. Available from: https://www.gov.uk/drug-safety-update/retigabine-trobalt-indication-restricted-to-last-line-use-and-new-monitoring-requirements.
   Google Scholar
• Clark S, Antell A, Kaufman K. New antiepileptic medication linked to blue discoloration of the skin and eyes. Ther Adv Drug Saf. 2015;6:15–19. doi:10.1177/2042098614560736.
   PubMedGoogle Scholar
• Chiron C. Stiripentol and vigabatrin current roles in the treatment of epilepsy. Expert Opin Pharmacother. 2016;17:1091–1101. doi:10.1517/14656566.2016.1161026.
   PubMed Web of Science ®Google Scholar
• Thiele EA. Managing epilepsy in tuberous sclerosis complex. J Child Neurol. 2004;19:680–686.
   PubMed Web of Science ®Google Scholar
• Margineanu DG. Systems biology impact on antiepileptic drug discovery. Espilepsy Res. 2012;98:104–115. doi:10.1016/j.eplepsyres.2011.10.006.
   PubMed Web of Science ®Google Scholar
• Margineanu DG. Systems biology, complexity, and the impact on antiepileptic drug discovery. Epilepsy Behav. 2014;38:131–142. doi:10.1016/j.yebeh.2013.08.029.
   PubMed Web of Science ®Google Scholar
• Di Ianni ME, Talevi A. How can network-pharmacology contribute to antiepileptic drug development? Mol Cell Epilepsy. 2014;1:e30.
   Google Scholar
• Bianchi MT, Pathmanathan J, Cash SS. From ion channels to complex networks: magic bullet versus magic shotgun approaches to anticonvulsant pharmacotherapy. Med Hypotheses. 2009;72:297–305. doi:10.1016/j.mehy.2008.09.049.
   PubMed Web of Science ®Google Scholar
• Margineanu DG. Neuropharmacology beyond reductionism – a likely prospect. Biosystems. 2015;141:1–9. doi:10.1016/j.biosystems.2015.11.010.
   PubMed Web of Science ®Google Scholar
• Fang M, Xi ZQ, Wu Y, et al. A new hypothesis of drug refractory epilepsy: neural network hypothesis. Med Hypotheses. 2011;76:871–876. doi:10.1016/j.mehy.2011.02.039.
   PubMed Web of Science ®Google Scholar
• Banerjee J, Chandra SP, Kurwale N, et al. Epileptogenic networks and drug-resistant epilepsy: present and future perspectives of epilepsy research – utility for the epileptologist and the epilepsy surgeon. Ann Indian Acad Neurol. 2014;17(Suppl. 1):S134–S140. doi:10.4103/0972-2327.128688.
   Google Scholar
• Kamisnki RM, Matagne A, Patsalos PN, et al. Benefit of combination therapy in epilepsy: a review of the preclinical evidence with levetiracetam. Epilepsia. 2009;50:387–397. doi:10.1111/j.1528-1167.2008.01713.x.
   PubMed Web of Science ®Google Scholar
• Brodie MJ, Sills GJ. Combining antiepileptic drugs – rational polytherapy? Seizure. 2011;20:369–375. doi:10.1016/j.seizure.2011.01.004.
   PubMed Web of Science ®Google Scholar
• Löscher W, Rundfelt C, Hönack D. 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. 1993;5:1545–1550. doi:10.1111/j.1460-9568.1993.tb00224.x.
   PubMed Web of Science ®Google Scholar
• Brandt C, Nozadze M, Heuchert N, et al. Disease-modifying effects of phenobarbital and the NKCC1 inhibitor bumetanide in the pilocarpine model of temporal lobe epilepsy. J Neurosci. 2010;30:8602–8612. doi:10.1523/JNEUROSCI.0633-10.2010.
   PubMed Web of Science ®Google Scholar
• Schrör K, Rauch BH. Aspirin and lipid mediators in the cardiovascular system. Prostaglandins Other Lipid Mediat. 2015;121:17–23. doi:10.1016/j.prostaglandins.2015.07.004.
   PubMed Web of Science ®Google Scholar
• Romano M, Cianci E, Simiele FM, et al. Lipoxins and aspirin-triggered lipoxins in resolution of inflammation. Eur J Pharmacol. 2015;760:49–63. doi:10.1016/j.ejphar.2015.03.083.
   PubMed Web of Science ®Google Scholar
• Paul-Clark MJ, Van Cao T, Moradi-Bidhendi N, et al. 15-Epi-lipoxin A4-mediated induction of nitric oxide explains how aspirin inhibits acute inflammation. J Exp Med. 2004;200:69–78. doi:10.1084/jem.20040566.
   PubMed Web of Science ®Google Scholar
• Milan JI. On ‘polypharmacy’ and multi-target agents, complementary strategies for improving the treatment of depression: a comparative appraisal. Int J Neuropsychopharmacol. 2014;17:1009–1037. doi:10.1017/S1461145712001496.
   PubMed Web of Science ®Google Scholar
• Silver LL. Challenges of antibacterial discovery. Clin Microbiol Rev. 2011;24:71–109. doi:10.1128/CMR.00030-10.
   PubMed Web of Science ®Google Scholar
• Morphy R, Rankovic Z. Designed multiple ligands. An emerging drug discovery paradigm. J Med Chem. 2005;48:6523–6543. doi:10.1021/jm058225d.
   PubMed Web of Science ®Google Scholar
• Dominguez JL, Fernández-Nieto F, Castro M, et al. Computer-aided structure-based design of multitarget leads for Alzheimer´s disease. J Chem Inf Model. 2015;55:135–148. doi:10.1021/ci500555g.
   PubMed Web of Science ®Google Scholar
• Fang J, Li Y, Liu R, et al. Discovery of multitarget-directed ligands against Alzheimer’s disease through systematic prediction of chemical–protein interactions. J Chem Inf Model. 2015;55:149–164. doi:10.1021/ci500574n.
   PubMed Web of Science ®Google Scholar
• Milan MJ. Dual- and triple-acting agents for treating core and co-morbid symptoms of major depression: novel concepts, new drugs. Neurotherapeutics. 2009;6:53–77. doi:10.1016/j.nurt.2008.10.039.
   PubMed Web of Science ®Google Scholar
• Makke Y, Hmaimess G, Nasreddine W, et al. Paradoxical exacerbation of myoclonic-astatic seizures by levetiracetam in myoclonic astatic epilepsy. BMC Pediatr. 2015;15:6. doi:10.1186/s12887-015-0330-y.
   PubMed Web of Science ®Google Scholar
• Bektaş G, Çalışkan M, Aydın A, et al. Aggravation of atonic seizures by rufinamide: a case report. Brain Dev. 2016;38:654–657. pii: S0387-7604(16)00031-0.
   PubMed Web of Science ®Google Scholar
• Gavatri NA, Livingston JH. Aggravation of epilepsy by anti-epileptic drugs. Dev Med Child Neurol. 2006;48:394–398. doi:10.1017/S0012162206000843.
   PubMed Web of Science ®Google Scholar
• Shorvon S. The concept of symptomatic epilepsy and the complexities of assigning cause in epilepsy. Epilepsy Behav. 2014;31:1–8. doi:10.1016/j.yebeh.2013.11.001.
   PubMed Web of Science ®Google Scholar
• Shorvon S. The causes of epilepsy: changing concepts of etiology of epilepsy over the past 150 years. Epilepsia. 2011;52:1033–1044. doi:10.1111/j.1528-1167.2011.03051.x.
   PubMed Web of Science ®Google Scholar
• Talevi A, Bruno-Blanch LE. On the development of new antiepileptic drugs for the treatment of pharmacoresistant epilepsy: different approaches to different hypothesis. In: Rocha L, Cavalheiro EA, editors. Pharmacoresistance in epilepsy: from genes and molecules to promising therapies. New York: Springer-Verlag; 2013.
   Google Scholar
• Vezzani A, French J, Bartfai T, et al. The role of inflammation in epilepsy. Nat Rev Neurol. 2011;7:31–40. doi:10.1038/nrneurol.2010.178.
   PubMed Web of Science ®Google Scholar
• Vezzani A, Friedman A, Dingledine RJ. The role of inflammation in epileptogenesis. Neuropharmacology. 2013;69:16–34. doi:10.1016/j.neuropharm.2012.04.004.
   PubMed Web of Science ®Google Scholar
• Haghikia A, Ladage K, Hinkerohe D, et al. Implications of antiinflammatory properties of the anticonvulsant drug levetiracetam in astrocytes. J Neurosci Res. 2008;86:1781–1788. doi:10.1002/jnr.21639.
   PubMed Web of Science ®Google Scholar
• Gómez CD, Buijs RM, Sitges M. The anti-seizure drugs vinpocetine and carbamazepine, but not valproic acid, reduce inflammatory IL-1β and TNF-α expression in rat hippocampus. J Neurochem. 2014;130:770–779. doi:10.1111/jnc.12784.
   PubMed Web of Science ®Google Scholar
• Ximenes JC, de Oliveira Gonçalves D, Siqueira RM, et al. Valproic acid: an anticonvulsant drug with potent antinociceptive and anti-inflammatory properties. Naunym Schmiedebergs Arch Pharmacol. 2013;386:575–587. doi:10.1007/s00210-013-0853-4.
   PubMed Web of Science ®Google Scholar
• Vuilleumier P, Jallon P. Epilepsy and psychiatric disorders: epidemiological data. Rev Neurol. 1998;154:305–317.
   PubMed Web of Science ®Google Scholar
• Dalmagro CL, Velasco TR, Bianchin MM, et al. Psychiatric comorbidity in refractory focal epilepsy: a study of 490 patients. Epilepsy Behav. 2012;25:593–597. doi:10.1016/j.yebeh.2012.09.026.
   PubMed Web of Science ®Google Scholar
• Bialer M. Why are antiepileptic drugs used for nonepileptic conditions? Epilepsia. 2012;53(Suppl. 7):26–33. doi:10.1111/j.1528-1167.2012.03712.x.
   PubMed Web of Science ®Google Scholar
• Faroog MU, Bhatt A, Majid A, et al. Levetiracetam for managing neurologic and psychiatric disorders. Am J Health Syst Pharm. 2009;66:541–561. doi:10.2146/ajhp070607.
   PubMed Web of Science ®Google Scholar
• Kaufman KR. Antiepileptic drugs in the treatment of psychiatric disorders. Epilepsy Behav. 2011;21:1–11. doi:10.1016/j.yebeh.2011.03.011.
   PubMed Web of Science ®Google Scholar
• Eddy CM, Rickards HE, Cavanna AE. Behavioral adverse effects of antiepileptic drugs in epilepsy. J Clin Psychopharmacol. 2012;32:362–375. doi:10.1097/JCP.0b013e318253a186.
   PubMed Web of Science ®Google Scholar
• Coyle H, Clough P, Cooper P, et al. Clinical experience with perampanel: focus on psychiatric adverse effects. Epilepsy Behav. 2014;41:193–196. doi:10.1016/j.yebeh.2014.09.072.
   PubMed Web of Science ®Google Scholar
• Kaufman KR, Bisen V, Zimmerman A, et al. Apparent dose-dependent levetiracetam-induced de novo major depression with suicidal behavior. Epilepsy Behav Case Rep. 2013;1:110–112. doi:10.1016/j.ebcr.2013.07.002.
   PubMedGoogle Scholar
• Molokwu OA, Ezeala-Adikaibe BA, Onwuekwe IO. Levetiracetam-induced rage and suicidality: two case reports and review of literature. Epilepsy Behav Case Rep. 2015;4:79–81. doi:10.1016/j.ebcr.2015.07.004.
   PubMedGoogle Scholar
• Mula M, Sander JW. Suicide risk in people with epilepsy taking antiepileptic drugs. Bipolar Disord. 2013;15:622–627. doi:10.1111/bdi.12091.
   PubMed Web of Science ®Google Scholar
• García Escrivá A, López Hernández N, Llorca V, et al. Efecto de la lacosamida sobre la calidad de vida del paciente con epilepsia. Rev Neurol. 2014;59:145–152.
   PubMed Web of Science ®Google Scholar
• Moseley BD, Cole D, Iwuora O, et al. The effects of lacosamide on depression and anxiety in patients with epilepsy. Epilepsy Res. 2015;110:115–118. doi:10.1016/j.eplepsyres.2014.12.007.
   PubMed Web of Science ®Google Scholar
• Sedighi B, Seifaddini R, Iranmanesh F, et al. Antiepileptic drugs and mental health status of patients with epilepsy. Iranian J Pharmacol Ther. 2013;12:66–70.
   Google Scholar
• Hassan MZ, Khan SA, Amir M. Design, synthesis and evaluation of N-(substituted benzothiazol-2-yl)amides as anticonvulsant and neuroprotective. Eur J Med Chem. 2012;58:206–213. doi:10.1016/j.ejmech.2012.10.002.
   PubMed Web of Science ®Google Scholar
• Yogeeswari P, Sriram D, Sahitya P, et al. Synthesis and anticonvulsant activity of 4-(2-(2,6-dimethylphenylamino)-2-oxoethylamino)-N-(substituted)butanamides: a pharmacophoric hybrid approach. Bioorg Med Chem Lett. 2007;17:3712–3715. doi:10.1016/j.bmcl.2007.04.032.
   PubMed Web of Science ®Google Scholar
• Wang Y, Jones PJ, Batts TW, et al. Ligand-based design and synthesis of novel sodium channel blockers from a combined phenytoin-lidocaine pharmacophore. Bioorg Med Chem. 2009;17:7064–7072. doi:10.1016/j.bmc.2008.10.031.
   PubMed Web of Science ®Google Scholar
• Morphy R, Kay C, Rankovic Z. From magic bullets to designed multiple ligands. Drug Discov Today. 2004;9:641–651. doi:10.1016/S1359-6446(04)03163-0.
   PubMed Web of Science ®Google Scholar
• Sturm N, Desaphy J, Quinn RJ, et al. Structural insights into the molecular basis of the ligand promiscuity. J Chem Inf Model. 2012;52:2410–2421. doi:10.1021/ci300196g.
   PubMed Web of Science ®Google Scholar
• Ma X, Shi Z, Tan C, et al. In silico approaches to multi-target drug design: computer-aided multi-target drug design, multi-target virtual screening. Pharm Res. 2010;27:739–749. doi:10.1007/s11095-010-0065-2.
   PubMed Web of Science ®Google Scholar
• Talevi A. Tailored multi-target agents. Applications and design considerations. Curr Pharm Des. 2016;22:3164–3170. doi:10.2174/1381612822666160308141203.
   PubMed Web of Science ®Google Scholar
• Wager TT, Hou X, Verhoest PR, et al. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci. 2010;1:435–449. doi:10.1021/cn100008c.
   PubMed Web of Science ®Google Scholar
• Talevi A. Multi-target pharmacology: possibilities and limitations of the “skeleton key approach” from a medicinal chemist perspective. Frontiers Pharmacol. 2015;6:205. doi:10.3389/fphar.2015.00205.
   PubMed Web of Science ®Google Scholar
• Kuntz ID, Chen K, Sharp KA, et al. The maximal affinity of ligands. Proc Natl Acad Sci. 1999;96:9997–10002.
   PubMed Web of Science ®Google Scholar
• Hopkins AL, Keserú GM, Leeson PD, et al. The role of ligand efficiency metrics in drug discovery. Nat Rev Drug Discov. 2014;13:105–121. doi:10.1038/nrd4163.
   PubMed Web of Science ®Google Scholar
• Cases M, Mestres J. A chemogenomic approach to drug discovery: focus on cardiovascular diseases. Drug Discov Today. 2009;14:479–485. doi:10.1016/j.drudis.2009.02.010.
   PubMed Web of Science ®Google Scholar
• Hu Y, Gupta-Ostermann D, Bajorath J. Exploring compound promiscuity patterns and multi-target activity spaces. Comput Struct Biotechnol. 2014;9:e201401003.
   PubMedGoogle Scholar
• Azzaoui K, Hamon H, Faller B, et al. Modeling promiscuity based on in vitro safety pharmacology profiling data. ChemMedChem. 2007;2:874–880. doi:10.1002/cmdc.200700036.
   PubMed Web of Science ®Google Scholar
• Leeson PD, Springthorpe B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov. 2007;6:881–890. doi:10.1038/nrd2445.
   PubMed Web of Science ®Google Scholar
• Yang Y, Chen H, Nilsson I, et al. Investigation of the relationship between topology and selectivity for druglike molecules. J Med Chem. 2010;53:7709–7714. doi:10.1021/jm1008456.
   PubMed Web of Science ®Google Scholar
• De Juan D, Pazos F, Valencia A. Emerging methods in protein co-evolution. Nat Rev Gen. 2013;14:249–261. doi:10.1038/nrg3414.
   PubMed Web of Science ®Google Scholar
• Qu XA, Rajpal DK. Applications of Connectivity Map in drug discovery and development. Drug Discov Today. 2012;17:1289–1298. doi:10.1016/j.drudis.2012.07.017.
   PubMed Web of Science ®Google Scholar
• Lamb J, Crawford ED, Peck D, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and, disease. Science. 2006;313:1929–1935. doi:10.1126/science.1132939.
   PubMed Web of Science ®Google Scholar
• Elliot RC, Miles MF, Lowestein DH. Overlapping microarray profiles of dentate gyrus gene expression during development- and epilepsy-associated neurogenesis and axon outgrowth. J Neurosci. 2003;23:2218–2227.
   PubMed Web of Science ®Google Scholar
• Newton SS, Collier EF, Hunsberger J, et al. Gene profile of electroconvulsive seizures: induction of neurotrophic and angiogenic factors. J Neurosci. 2003;23:10841–10851.
   PubMed Web of Science ®Google Scholar
• Hunsberger JG, Bennett AH, Selvanayagam E, et al. Gene profiling the response to kainic acid induced seizures. Mol Brain Res. 2005;141:95–112. doi:10.1016/j.molbrainres.2005.08.005.
   PubMedGoogle Scholar
• Hendriksen H, Datson NA, Ghijsen WE, et al. Altered hippocampal gene expression prior to the onset of spontaneous seizures in the rat post-status epilepticus model. Eur J Neurosci. 2001;14:1475–1484.
   PubMed Web of Science ®Google Scholar
• Borges K, Shaw R, Dingledine R. Gene expression changes after seizure preconditioning in the three major hippocampal cell layers. Neurobiol Dis. 2007;26:66–77. doi:10.1016/j.nbd.2006.12.001.
   PubMed Web of Science ®Google Scholar
• Theilhaber J, Rakhade SN, Sudhalter J, et al. Gene expression profiling of a hypoxic seizure model of epilepsy suggests a role for mTOR and Wnt signaling in epileptogenesis. PLoS ONE. 2013;8:e74428. doi:10.1371/journal.pone.0074428.
   Google Scholar
• Mazzuferi M, Kumar G, van Eyll J, et al. Nrf2 defense pathway: experimental evidence for its protective role in epilepsy. Ann Neurol. 2013;74:560–568. doi:10.1002/ana.23940.
   PubMed Web of Science ®Google Scholar
• Carmona-Aparicio L, Pérez-Cruz C, Zavala-Tecuapetla C, et al. Overview of Nrf2 as therapeutic target in epilepsy. Int J Mol Sci. 2015;16:18348–18367. doi:10.3390/ijms160818348.
   PubMed Web of Science ®Google Scholar
• McClelland S, Flynn C, Dubé C, et al. Neuron-restrictive silencer factor-mediated hyperpolarization-activated cyclic nucleotide gated channelopathy in experimental temporal lobe epilepsy. Ann Neurol. 2011;70:454–464. doi:10.1002/ana.22479.
   PubMed Web of Science ®Google Scholar
• Johnson MR, Behmoaras J, Bottolo L, et al. Systems genetics identifies Sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus. Nat Commun. 2015;6:6031. doi:10.1038/ncomms7031.
   PubMed Web of Science ®Google Scholar
• Csernely P, Korcsmárosa T, Kissa HJM, et al. Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review. Pharmacol Ther. 2013;138:333–408. doi:10.1016/j.pharmthera.2013.01.016.
   PubMed Web of Science ®Google Scholar
• Agoston V, Csermely P, Pongor S. Multiple weak hits confuse complex systems: a transcriptional regulatory network as an example. Phys Rev E Stat Nonlin Soft Matter Phys. 2005;71:051909. doi:10.1103/PhysRevE.71.051909.
   Google Scholar
• Zheng H, Fridkin M, Youdim M. From single target to multitarget/network therapeutics in Alzheimer’s therapy. Pharmaceuticals. 2014;7:113–135. doi:10.3390/ph7020113.
   Google Scholar
• Lipton SA. Paradigm shift in neuroprotection by NMDA receptor blockade: memantine and beyond. Nat Rev Drug Discov. 2006;5:160–170. doi:10.1038/nrd1958.
   PubMed Web of Science ®Google Scholar
• Rammes G, Rupprecht R, Ferrari U, et al. The N-methyl-D-aspartate receptor channel blockers memantine, MRZ 2/579 and other amino-alkyl-cyclohexanes antagonise 5-HT(3) receptor currents in cultured HEK-293 and N1E-115 cell systems in a non-competitive manner. Neurosci Lett. 2001;306:81–84.
   PubMed Web of Science ®Google Scholar
• Aracava T, Pereira EF, Maelicke A, et al. Memantine blocks alpha7* nicotininc acetylcholine receptors more potently than N-methyl-D-aspartate receptors in rat hippocampal neurons. J Pharmacol Exp Ther. 2005;312:1195–1205. doi:10.1124/jpet.104.077172.
   PubMed Web of Science ®Google Scholar
• Seeman P, Caruso C, Lasaga M. Memantine agonist action at dopamine D2High receptors. Synapse. 2008;62:149–153. doi:10.1002/syn.20472.
   PubMed Web of Science ®Google Scholar
• Rundfeldt C, Löscher W. The pharmacology of imepitoin: the first partial benzodiazepine receptor agonist developed for the treatment of epilepsy. CNS Drugs. 2013;28:29–43. doi:10.1007/s40263-013-0129-z.
   Web of Science ®Google Scholar
• Stables JP, Kupferberg HJ The NIH Anticonvulsant Drug Development (ADD) program: preclinical anticonvulsant screening project. [Cited 2016 Mar]. Available from: http://www.ninds.nih.gov/research/asp/addadd_review.pdf.
   Google Scholar
• Löscher W. Critical review of current animal models of seizures and epilepsy used in the discovery and development of new antiepileptic drugs. Seizure. 2011;20:359–368. doi:10.1016/j.seizure.2011.01.003.
   PubMed Web of Science ®Google Scholar
• Klitgaard H, Matagne A, Nicolas JM, et al. Brivaracetam: rationale for discovery and preclinical profile of a selective SV2A ligand for epilepsy treatment. Epilepsia. 2016;57:538–548. doi:10.1111/epi.13340.
   PubMed Web of Science ®Google Scholar
• Langer T, Bryant SD. 3D quantitative structure-property relationships. In: Wermuth CG, editor. The practice of medicinal chemistry. 3rd ed. London: Academic Press; 2008.
   Google Scholar
• Sippl W. 3D QSAR: applications, recent advances, and limitations. In: Puzyn T, Leszczynski J, Cronin MT, editors. Recent advances in QSAR studies. Methods and applications. 1st ed. Dordrecht: Springer; 2010.
   Google Scholar
• Roy K, Kar S, Das RN. Background of QSAR and historical developments. In: Roy K, Kar S, Das RN, editors. Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment. 1st ed. London: Academic Press; 2015.
   Google Scholar
• Nikolic K, Agbaba D. QSAR study and design of novel organoselenium and α-tocopherol derivatives with enhanced chemotherapeutic activity. Lett Drug Des Discov. 2009;6:228–235. doi:10.2174/157018009787847882.
   Web of Science ®Google Scholar
• Bello-Ramírez AM, Buendía-Orozco J, Nava-Ocampo AA. A QSAR analysis to explain the analgesic properties of aconitum alkaloids. Fundam Clin Pharmacol. 2003;17:575–580.
   PubMed Web of Science ®Google Scholar
• Patel SR, Gangwal R, Sangamwar AT, et al. Synthesis, biological evaluation and 3D-QSAR study of hydrazide, semicarbazide and thiosemicarbazide derivatives of 4-(adamantan-1-yl)quinoline as anti-tuberculosis agents. Eur J Med Chem. 2014;85:255–267. doi:10.1016/j.ejmech.2014.07.100.
   PubMed Web of Science ®Google Scholar
• Richard AM, Benigni R. AI and SAR approaches for predicting chemical carcinogenicity: survey and status report. SAR QSAR Environ Res. 2002;13:1–19. doi:10.1080/10629360290002055.
   PubMed Web of Science ®Google Scholar
• Shen M, LeTiran A, Xiao Y, et al. Quantitative structure−activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods. J Med Chem. 2002;45:2811–2823.
   PubMed Web of Science ®Google Scholar
• Tasso SM, Moon SCH, Bruno-Blanch LE, et al. Characterization of anticonvulsant profile of valpromide derivatives. Bioorg Med Chem. 2004;12:3857–3869. doi:10.1016/j.bmc.2004.05.003.
   PubMed Web of Science ®Google Scholar
• Talevi A, Bellera CL, Castro EA, et al. 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. 2007;21:527–538. doi:10.1007/s10822-007-9136-9.
   PubMed Web of Science ®Google Scholar
• Talevi A, Enrique AV, Bruno-Blanch LE. Anticonvulsant activity of artificial sweeteners: a structural link between sweet-taste receptor T1R3 and brain glutamate receptors. Bioorg Med Chem Lett. 2012;22:4072–4074. doi:10.1016/j.bmcl.2012.04.076.
   PubMed Web of Science ®Google Scholar
• Sutherland JJ, Weaver DF. Development of quantitative structure−activity relationships and classification models for anticonvulsant activity of hydantoin analogues. J Chem Inf Model. 2003;43:1028–1036.
   Web of Science ®Google Scholar
• Gavernet L, Domínguez-Cabrera MJ, Bruno-Blanch LE, et al. 3D QSAR design of novel antiepileptic sulfmides. Bioorg Med Chem. 2007:1556–1567. doi:10.1016/j.bmc.2006.06.010.
   PubMed Web of Science ®Google Scholar
• Gavernet L, Talevi A, Castro EA. A combined virtual screening 2D and 3D QSAR methodology for the selection of new anticonvulsant candidates from a natural product library. QSAR Comb Sci. 2008;27:1120–1129. doi:10.1002/qsar.200730055.
   Google Scholar
• Di Ianni ME, Enrique AV, Palestro PH, et al. Several new diverse anticonvulsant agents discovered in a virtual screening campaign aimed at novel antiepileptic drugs to treat refractory epilepsy. J Chem Inf Model. 2012;52:3325–3330. doi:10.1021/ci300423q.
   PubMed Web of Science ®Google Scholar
• Speck-Planche A, Cordeiro MN. Multitasking models for quantitative structure-biological effect relationships: current status and future perspectives to speed up drug discovery. Expert Opin Drug Discov. 2015;10:245–256. doi:10.1517/17460441.2015.1006195.
   PubMed Web of Science ®Google Scholar
• Liu Q, Zhou H, Liu L, et al. Multi-target QSAR modeling in the analysis and design of HIV-HCV co-inhibitors: an in-silico study. BMC Bioinformatics. 2011;12:294. doi:10.1186/1471-2105-12-294.
   PubMed Web of Science ®Google Scholar
• Kwan P, Brodie MJ. Potential role of drug transporters in the pathogenesis of medically intractable epilepsy. Epilepsia. 2005;46:224–235. doi:10.1111/j.0013-9580.2005.31904.x.
   PubMed Web of Science ®Google Scholar
• Remy S, Beck H. Molecular and cellular mechanisms of pharmacoresistance in epilepsy. Brain. 2006;129(Pt 1):18–35. doi:10.1093/brain/awh682.
   PubMed Web of Science ®Google Scholar
• Schmidt D, Löscher W. Drug resistance in epilepsy: putative neurobiologic and clinical mechanisms. Epilepsia. 2005;46:858–877. doi:10.1111/j.1528-1167.2005.54904.x.
   PubMed Web of Science ®Google Scholar
• Löscher W, Klotz U, Zimprich F, et al. The clinical impact of pharmacogenetics on the treatment of epilepsy. Epilepsia. 2009;50:1–23. doi:10.1111/j.1528-1167.2008.01716.x.
   PubMed Web of Science ®Google Scholar
• Rogawski MA, Johnson MR. Intrinsic severity as a determinant of antiepileptic drug refractoriness. Epilepsy Curr. 2008;8(5):127–130. doi:10.1111/j.1535-7511.2008.00272.x.
   PubMedGoogle Scholar
• Zhang C, Kwan P, Zuo Z, et al. The transport of antiepileptic drugs by P-gp. Adv Drug Deliv Rev. 2012;64:930–942. doi:10.1016/j.addr.2011.12.003.
   PubMed Web of Science ®Google Scholar
• Stépien KM, Tomaszewski M, Tomaszewska J, et al. The multidrug transporter P-glycoprotein in pharmacoresistance to antiepileptic drugs. Pharmacol Rep. 2012;64:1011–1019.
   PubMed Web of Science ®Google Scholar
• Römermann K, Helmer R, Löscher W. The antiepileptic drug lamotrigine is a substrate of mouse and human breast cancer resistance protein (ABCG2). Neuropharmacology. 2015;93:7–14. doi:10.1016/j.neuropharm.2015.01.015.
   PubMed Web of Science ®Google Scholar
• Nakanishi H, Yonezawa A, Matsubara K, et al. Impact of P-glycoprotein and breast cancer resistance protein on the brain distribution of antiepileptic drugs in knockout mouse models. Eur J Pharmacol. 2013;710:20–28. doi:10.1016/j.ejphar.2013.03.049.
   PubMed Web of Science ®Google Scholar
• Uchida Y, Ohtsuki S, Katsukura Y, et al. Quantitative targeted absolute proteomics of human blood-brain barrier transporters and receptors. J Neurochem. 2011;117:333–345. doi:10.1111/j.1471-4159.2011.07208.x.
   PubMed Web of Science ®Google Scholar
• Kwan P, Arzimanoglou A, Berg AT, et al. Definition of drug resistant epilepsy: consensus proposal by the ad hoc task force of the ILAE commission on therapeutic strategies. Epilepsia. 2010;51:1069–1077. doi:10.1111/j.1528-1167.2009.02397.x.
   PubMed Web of Science ®Google Scholar
• Kobow K, El-Osta A, Blumcke I. The methylation hypothesis of pharmacoresistance in epilepsy. Epilepsia. 2013;54(Suppl. S2):41–47. doi:10.1111/epi.12183.
   PubMed Web of Science ®Google Scholar
• Schmidt D, Löscher W. New developments in antiepileptic drug resistance: an integrative view. Epilepsy Curr. 2009;9:47–52. doi:10.1111/j.1535-7511.2008.01289.x.
   PubMed Web of Science ®Google Scholar
• Talevi A, Bruno-Blanch LE. Efflux-transporters at the blood-brain barrier: therapeutic opportunities. In: Montenegro PA, Juárez SM, editors. The blood-brain barrier: new research. New York: Nova Science Publishers; 2012.
   Google Scholar
• Potschka H, Luna-Munguia H. CNS transporters and drug delivery in epilepsy. Curr Pharm Des. 2014;20:1435–1452. doi:10.2174/13816128113199990461.
   Google Scholar
• Potschka H. Role of CNS efflux drug transporters in antiepileptic drug delivery: overcoming CNS efflux drug transport. Adv Drug Deliv Rev. 2012;64:943–952. doi:10.1016/j.addr.2011.12.007.
   PubMed Web of Science ®Google Scholar
• Rosillo-de la Torre A, Luna-Bárcenas G, Orozco-Suárez S, et al. Pharmacoresistant epilepsy and nanotechnology. Front Biosci (Elite Ed). 2014;6:329–340.
   PubMedGoogle Scholar
• Bennewitz MF, Saltzman WM. Nanotechnology for delivery of drugs to the brain for epilepsy. Nanotherapeutics. 2009;6:323–336. doi:10.1016/j.nurt.2009.01.018.
   PubMed Web of Science ®Google Scholar
• Ecker GF, Stockner T, Chiba P. Computational models for prediction of interactions with ABC-transporters. Drug Discov Today. 2008;13:311–317. doi:10.1016/j.drudis.2007.12.012.
   PubMed Web of Science ®Google Scholar
• Chen L, Li Y, Yu H, et al. Computational models for predicting substrates or inhibitors of P-glycoprotein. Drug Discov Today. 2012;17:343–351. doi:10.1016/j.drudis.2011.11.003.
   PubMed Web of Science ®Google Scholar
• Pinto M, Digles D, Ecker GF. Computational models for predicting the interaction with ABC transporters. Drug Discov Today Technol. 2014;12:e69–e77. doi:10.1016/j.ddtec.2014.03.007.
   Google Scholar
• Couyoupetrou M, Gantner ME, Di Ianni ME, et al. Computer-aided recognition of ABC transporters substrates and its application to the development of new drugs for refractory epilepsy. Mini-Rev Med Chem. forthcoming 2016.
   Google Scholar
• Levatić J, Ćurak J, Karlj M, et al. Accurate models for P-gp drug recognition induced from a cancer cell line cytotoxicity screen. J Med Chem. 2013;56:5691–5708. doi:10.1021/jm400328s.
   PubMed Web of Science ®Google Scholar
• BioZyne. P-gp susbtrate specificity modeling. [Cited 2016 Jul]. Available from: http://pgp.biozyne.com/.
   Google Scholar
• Bikadi Z, Hazai I, Malik D, et al. Predicting P-glycoprotein-mediated drug transport based on support vector machine and three-dimensional crystal structure of P-glycoprotein. PLoS One. 2011;6:e25815. doi:10.1371/journal.pone.0025815.
   PubMed Web of Science ®Google Scholar
• Althotas virtual laboratory. [cited 2016 Jul]. Available from: http://pgp.althotas.com/.
   Google Scholar
• Zhang L, Balimane P, Johnson S, et al. Development of an in silico model for predicting efflux substrates in Caco-2 cells. Int J Pharm. 2007;343:98–105. doi:10.1016/j.ijpharm.2007.05.017.
   PubMed Web of Science ®Google Scholar
• Talevi A, Bellera C, Di Ianni M, et al. An integrated drug development approach applying topological descriptors. Curr Comput Aided Drug Des. 2011;8:172–181. doi:10.2174/157340912801619076.
   Web of Science ®Google Scholar
• Polanski J, Bak A, Gieleciak R, et al. Modeling robust QSAR. J Chem Inf Model. 2006;46:2310–2318. doi:10.1021/ci050314b.
   PubMed Web of Science ®Google Scholar
• Penzotti JE, Lamb ML, Evensen E, et al. A computational ensemble pharmacophore model for identifying substrates of P-glycoprotein. J Med Chem. 2002;45:1737–1740. doi:10.1021/jm0255062.
   PubMed Web of Science ®Google Scholar
• Li WX, Li L, Eksterowicz J, et al. Significance analysis and multiple pharmacophore models for differentiating P-glycoprotein substrates. J Chem Inf Model. 2007;47:2429–2438. doi:10.1021/ci600423u.
   PubMed Web of Science ®Google Scholar
• Svetnik V, Wang T, Tong C, et al. Boosting: an ensemble learning tool for compound classification and QSAR modeling. J Chem Inf Model. 2005;45:786–799. doi:10.1021/ci0500379.
   PubMed Web of Science ®Google Scholar
• Cao DS, Huang JH, Yan J, et al. Kernel k-nearest neighbor algorithm as a flexible SAR modeling tool. Chemom Intell Lab Systems. 2012;114:19–23. doi:10.1016/j.chemolab.2012.01.008.
   Web of Science ®Google Scholar
• Gantner ME, Di Ianni ME, Ruiz ME, et al. Development of conformation independent computational models for the early recognition of breast cancer resistance protein substrates. Biomed Res Int. 2013;2013:863592. doi:10.1155/2013/863592.
   PubMed Web of Science ®Google Scholar
• Di Ianni ME, Talevi A, Castro EA, et al. Development of a highly specific ensemble of topological models for early identification of P-glycoprotein substrates. J Chemometr. 2011;25:313–322. doi:10.1002/cem.1376.
   Web of Science ®Google Scholar
• Leong MK, Chen HB, Shih YH. Prediction of promiscuous P-glycoprotein inhibition using a novel machine learning scheme. PLoS ONE. 2012;7:e33829. doi:10.1371/journal.pone.0033829.
   PubMedGoogle Scholar
• Zhu H, Tropsha A, Foruches D, et al. Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis. J Chem Inf Model. 2008;48:766–784. doi:10.1021/ci700443v.
   PubMed Web of Science ®Google Scholar
• Arrowsmith J, Harrison R. Drug repositioning: the business case and current strategies to repurpose shelved candidates and marketed drugs. In: Barratt MJ, Frail DE, editors. Drug repositioning: bringing new life to shelved assets and existing drugs. NJ: Wiley & Sons; 2012.
   Google Scholar
• Ashburn TT, Thor KB. Drug repositioning: identifying and developing new uses for existing drugs. Nat Rev Drug Discov. 2004;3:673–683. doi:10.1038/nrd1468.
   PubMed Web of Science ®Google Scholar
• Spina E, Preugi G. Antiepileptic drugs: indications other than epilepsy. Epileptic Disord. 2004;6:57–75.
   PubMed Web of Science ®Google Scholar
• Rogawski MA, Löscher W. The neurobiology of antiepileptic drugs for the treatment of nonepileptic conditions. Nat Med. 2004;10:685–695. doi:10.1038/nm1074.
   PubMed Web of Science ®Google Scholar
• Ettinger AB, Argoff CE. Use of antiepileptic drugs for nonepileptic conditions: psychiatric disorders and chronic pain. Neurotherapeutics. 2007;4:75–83. doi:10.1016/j.nurt.2006.10.003.
   PubMed Web of Science ®Google Scholar
• Moch S. Therapeutic uses of antiepileptic drugs in non-epileptic disorders. South Afr Pharm J. 2010;77:18–27.
   Google Scholar
• Łukawski K, Janowska A, Jakubus T, et al. Interactions between angiotensin AT1 receptor antagonists and second-generation antiepileptic drugs in the test of maximal electroshock. Fundam Clin Pharmacol. 2014;28:277–283. doi:10.1111/fcp.12023.
   PubMed Web of Science ®Google Scholar
• Łukawski K, Janowska A, Jakubus T, et al. Angiotensin AT1 receptor antagonists enhance the anticonvulsant actin of valproate in the mouse model of maximal electroshock. Eur J Pharmacol. 2010;640:172–177. doi:10.1016/j.ejphar.2010.04.053.
   PubMed Web of Science ®Google Scholar
• Łukawski K, Janowska A, Jakubus T, et al. Combined treatment with gabapentin and drugs affecting the renin-angiotensin system against electroconvulsions in mice. Eur J Pharmacol. 2013;706:92–97. doi:10.1016/j.ejphar.2013.02.054.
   PubMed Web of Science ®Google Scholar
• Pushpa VH, Padmaja Shetty K, Suresha RN, et al. Evaluation and comparison of anticonvulsant activity of telmisartan and olmesartan in experimentally induced animal models of epilepsy. J Clin Diagn Res. 2014;8:HC08–HC11.
   Google Scholar
• Piñero J, Queralt-Rosinach N, Bravo A, et al. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database (Oxford). 2015;2015:bay028. doi:10.1093/database/bav028.
   Web of Science ®Google Scholar
• Davis AP, Murphy CG, Johnson R, et al. The Comparative Toxicogenomics Database: update 2013. Nucleic Acids Res. 2013;41:D11–D14. doi:10.1093/nar/gks994.
   Google Scholar
• Hamosh A, Scott AF, Amberger JS, et al. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 2005;41:D514–D517.
   Google Scholar
• Gutiérrez-SAcristán A, Grosdidier S, Valverde O, et al. PsyGeNET: a knowledge platform on psychiatric disorders and their genes. Bionformatics. 2015;31:3075–3077. doi:10.1093/bioinformatics/btv301.
   Google Scholar
• Pearson WR. An introduction to sequence similarity (“Homology”) searching. Curr Protoc Bioinformatics. 2013;42:3.1.1–3.1.8.
   Google Scholar
• Gibrat JF, Madej T, Bryant SH. Surprising similarities in structure comparison. Curr Opin Struct Biol. 1996;6:377–385.
   PubMed Web of Science ®Google Scholar
• Madej T, Lanczycki CJ, Zhang D, et al. MMDB and VAST+: tracking structural similarities between macromolecular complexes. Nucleic Acid Res. 2014;42:D297–D303. doi:10.1093/nar/gkt1208.
   Web of Science ®Google Scholar
• Haupt VJ, Daminelli S, Schroeder M. Drug promiscuity in PDB: protein binding site similarity is key. Plos One. 2013;8:e65894. doi:10.1371/journal.pone.0065894.
   PubMed Web of Science ®Google Scholar
• Konc J, Janežič D. Binding site comparison for function prediction and pharmaceutical discovery. Curr Opin Struct Biol. 2013;25:34–39. doi:10.1016/j.sbi.2013.11.012.
   PubMed Web of Science ®Google Scholar
• Zhuo W, Zhang L, Zhu Y, et al. Valproic acid, an inhibitor of class I histone deacetylases, reverses acquired erlotinib-resistance of lung adenocarcinoma cells: a Connectivity Mapping analysis and an experimental study. Am J Cancer Res. 2015;5:2202–2211.
   PubMed Web of Science ®Google Scholar
• Dudley JT, Sirota M, Shenoy M, et al. Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Sci Transl Med. 2011;3:96ra76. doi:10.1126/scitranslmed.3002648.
   PubMed Web of Science ®Google Scholar
• Talevi A, Bruno-Blanch LE. Virtual screening: an emergent, key methodology for drug development in an emergent continent. A bridge towards patentability. In: Castro EA, Haghi AK, editors. Advanced methods and applications in chemoinformatics. Research progress and new applications. Hershey: IGI Global; 2011.
   Google Scholar
• Law V, Knox C, Dioumbou Y, et al. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acid Res. 2014;42:D1091–D1109. doi:10.1093/nar/gkt1068.
   PubMed Web of Science ®Google Scholar
• Novick PA, Ortiz OF, Poelman J, et al. SWEETLEAD: an in silico database of approved drugs, regulated chemicals, and herbal isolates for computer-aided drug discovery. PLoS ONE. 2013;8:e79568. doi:10.1371/journal.pone.0079568.
   PubMed Web of Science ®Google Scholar
• Talevi A. The importance of bioactivation in computer-guided drug repositioning. Why the parent drug is not always enough. Curr Top Med Chem. 2016;16:2078–2087. doi:10.2174/1568026616666160216155043.
   PubMed Web of Science ®Google Scholar
• Oprea TI, Overington JP. Computational and practical aspects of drug repositioning. Assay Drug Dev Technol. 2015;13:299–306. doi:10.1089/adt.2015.29011.tiodrrr.
   PubMed Web of Science ®Google Scholar
• Zawilska JB, Wojcieszak J, Olejniczak AB. Prodrugs: a challenge for the drug development. Pharmacol Rep. 2013;65:1–14.
   PubMed Web of Science ®Google Scholar
• Wu L, Ai N, Liu Y, et al. Relating anatomical therapeutic indications by the ensemble similarity of drug sets. J Chem Inf Model. 2013;53:2154–2160. doi:10.1021/ci400155x.
   PubMed Web of Science ®Google Scholar
• Keiser KL, Roth LB, Armbruster BN, et al. Relating protein pharmacology by ligand chemistry. Nature Biotechnol. 2007;25:197–20.
   PubMed Web of Science ®Google Scholar
• Keiser MJ, Irwin JJ, Laggner CH, et al. Predicting new molecular targets for known drugs. Nature. 2009;462:175–181. doi:10.1038/nature08506.
   PubMed Web of Science ®Google Scholar
• Liu R, Singh N, Tawa GJ, et al. Exploiting large-scale drug-protein interaction information for computational drug repurposing. BMC Bioinformatics. 2014;15:210. doi:10.1186/1471-2105-15-210.
   PubMed Web of Science ®Google Scholar
• Cheng F, Liu C, Jiang J, et al. Prediction of drug-target interactions and drug repositioning via network-based inference. PLoS Comput Biol. 2012;8:e1002503. doi:10.1371/journal.pcbi.1002503.
   PubMed Web of Science ®Google Scholar
• Chen B, Ding Y, Wild DJ. Assessing drug target association using semantic linked data. PloS Comput Biol. 2012;8:e1002574. doi:10.1371/journal.pcbi.1002574.
   PubMed Web of Science ®Google Scholar
• Talevi A, Enrique AE, Bruno-Blanch LE. Anticonvulsant activity of artificial sweeteners: a structural link between sweet-taste receptor T1R3 and brain glutamate receptors. Bioorg Med Chem Lett. 2012;22:4072–4074. doi:10.1016/j.bmcl.2012.04.076.
   PubMed Web of Science ®Google Scholar
• Di Ianni ME, Enrique AV, Del Valle ME, et al. Is there a relationship between sweet taste and seizures? Anticonvulsant and proconvulsant effects of non-nutritive sweeteners. Comb Chem High Throughput Screen. 2015;18:335–345.
   PubMed Web of Science ®Google Scholar
• Di Ianni ME, Del Valle ME, Enrique AV, et al. Computer-aided identification of anticonvulsant effect of natural nonnutritive sweeteners stevioside and rebaudioside A. Assay Drug Dev Technol. 2015;13:313–318. doi:10.1089/adt.2015.29010.meddrrr.
   PubMed Web of Science ®Google Scholar
• Köhler K, Hillebrecht A, Schulze Wischeler J, et al. Saccharin inhibits carbonic anhydrases: possible explanation for its unpleasant metallic aftertaste. Angew Chem Int Ed Engl. 2007;46:7697–7699. doi:10.1002/anie.200701189.
   PubMed Web of Science ®Google Scholar