Antiepileptic drug discovery: does mechanism of action matter?

Single-Target Versus Multi-Target Drugs Versus Combinations of Drugs With Multiple Targets: Preclinical and Clinical Evidence for the Treatment or Prevention of Epilepsy

Rationally designed multi-target drugs (also termed multimodal drugs, network therapeutics, or designed multiple ligands) have emerged as an attractive drug discovery paradigm in the last 10-20 years, as potential therapeutic solutions for diseases of complex etiology and diseases with significant drug-resistance problems. Such agents that modulate multiple targets simultaneously are developed with the aim of enhancing efficacy or improving safety relative to drugs that address only a single target or to combinations of single-target drugs. Although this strategy has been proposed for epilepsy therapy >25 years ago, to my knowledge, only one antiseizure medication (ASM), padsevonil, has been intentionally developed as a single molecular entity that could target two different mechanisms. This novel drug exhibited promising effects in numerous preclinical models of difficult-to-treat seizures. However, in a recent randomized placebo-controlled phase IIb add-on trial in treatment-resistant focal epilepsy patients, padsevonil did not separate from placebo in its primary endpoints. At about the same time, a novel ASM, cenobamate, exhibited efficacy in several randomized controlled trials in such patients that far surpassed the efficacy of any other of the newer ASMs. Yet, cenobamate was discovered purely by phenotype-based screening and its presumed dual mechanism of action was only described recently. In this review, I will survey the efficacy of single-target vs. multi-target drugs vs. combinations of drugs with multiple targets in the treatment and prevention of epilepsy. Most clinically approved ASMs already act at multiple targets, but it will be important to identify and validate new target combinations that are more effective in drug-resistant epilepsy and eventually may prevent the development or progression of epilepsy.

Potential role of selected antiepileptics used in neuropathic pain as human GABA transporter isoform 1 (GAT1) inhibitors-Molecular docking and pharmacodynamic studies

The chemical interaction of nine antiepileptic drugs (tiagabine, gabapentin, pregabalin, lamotrigine, zonisamide, valproic acid, valpromide, vigabatrin, progabide) and two endogenous metabolites (4-aminobutanoic acid, 4-hydroxybutanoic acid) with a model of human GABA transporter 1 (hGAT1) is described using the molecular docking method. To establish the role of hGAT1 in chronic pain, tiagabine, a selective hGAT1 inhibitor, was assessed in the in vivo experiments for its antiallodynic properties in two mouse models of neuropathic pain. Docking analyses performed in this study provided the complex binding energies, specific hydrogen bond components, and hydrogen bond properties such as energies, distances and angles. The data of the docking studies strongly support the assumption that the antiepileptic and analgesic actions of the studied drugs can be at least in part related to the strength of their chemical interactions with hGAT1. In vivo experiments with tiagabine confirmed the involvement of hGAT1 in the regulation of the mechanical nociceptive threshold in neuropathic pain.

Design and comparative anticonvulsant activity assessment of CNS-active alkyl-carbamoyl imidazole derivatives

A novel series of carbamoyl derivatives of alkylimidazole has been designed and their anticonvulsant activity was comparatively evaluated in the mice- and rats-maximal-electroshock (MES), subcutaneous-metrazol (scMet) seizure tests and the mice-6Hz psychomotor (6Hz) models. The ten new designed molecules contain in their chemical structure imidazole, alkyl side-chain and carbamate as three potential active moieties. In spite of the close structural features of the carbamoyl imidazole derivatives only compounds 7, 8, 13 and 16 were active at the MES test with ED50 values ranging from 12 to 20mg/kg coupled with high protective index (PI=TD50/ED50) values of 4.1-7.3 after ip administration to rats. A similar phenomenon was observed in mice where compounds 7, 8, 9, 12 had MES-ED50 values of 14-26mg/kg. Compounds 7 and 13 also demonstrated anticonvulsant activity in the 6Hz model with ED50 values of 32 and 44mg/kg, respectively. As the most active entities, compounds 7, 8 followed by 13 and 16, thus offer an optimal efficacy-safety profile and consequently, might be promising candidates for development as new antiepileptics.

Systems biology, complexity, and the impact on antiepileptic drug discovery

The number of available anticonvulsant drugs increased in the period spanning over more than a century, amounting to the current panoply of nearly two dozen so-called antiepileptic drugs (AEDs). However, none of them actually prevents/reduces the post-brain insult development of epilepsy in man, and in no less than a third of patients with epilepsy, the seizures are not drug-controlled. Plausibly, the enduring limitation of AEDs' efficacy derives from the insufficient understanding of epileptic pathology. This review pinpoints the unbalanced reductionism of the analytic approaches that overlook the intrinsic complexity of epilepsy and of the drug resistance in epilepsy as the core conceptual flaw hampering the discovery of truly antiepileptogenic drugs. A rising awareness of the complexity of epileptic pathology is, however, brought about by the emergence of nonreductionist systems biology (SB) that considers the networks of interactions underlying the normal organismic functions and of SB-based systems (network) pharmacology that aims to restore pathological networks. By now, the systems pharmacology approaches of AED discovery are fairly meager, but their forthcoming development is both a necessity and a realistic prospect, explored in this review.

Systems biology impact on antiepileptic drug discovery

Systems biology (SB), a recent trend in bioscience research to consider the complex interactions in biological systems from a holistic perspective, sees the disease as a disturbed network of interactions, rather than alteration of single molecular component(s). SB-relying network pharmacology replaces the prevailing focus on specific drug-receptor interaction and the corollary of rational drug design of "magic bullets", by the search for multi-target drugs that would act on biological networks as "magic shotguns". Epilepsy being a multi-factorial, polygenic and dynamic pathology, SB approach appears particularly fit and promising for antiepileptic drug (AED) discovery. In fact, long before the advent of SB, AED discovery already involved some SB-like elements. A reported SB project aimed to find out new drug targets in epilepsy relies on a relational database that integrates clinical information, recordings from deep electrodes and 3D-brain imagery with histology and molecular biology data on modified expression of specific genes in the brain regions displaying spontaneous epileptic activity. Since hitting a single target does not treat complex diseases, a proper pharmacological promiscuity might impart on an AED the merit of being multi-potent. However, multi-target drug discovery entails the complicated task of optimizing multiple activities of compounds, while having to balance drug-like properties and to control unwanted effects. Specific design tools for this new approach in drug discovery barely emerge, but computational methods making reliable in silico predictions of poly-pharmacology did appear, and their progress might be quite rapid. The current move away from reductionism into network pharmacology allows expecting that a proper integration of the intrinsic complexity of epileptic pathology in AED discovery might result in literally anti-epileptic drugs.