Computational approaches for innovative antiepileptic drug discovery. (2nd October 2016)

• Record Type: Journal Article
• Authors: Talevi, Alan
• Is Part Of: Expert opinion on drug discovery. Volume 11:Number 10(2016:Oct.)
• Page Start: 1001
• Page End: 1016
• Publication Date: 2016-10-02
• Subjects: Epilepsy -- refractory epilepsy -- network pharmacology -- systems biology -- multi-target agents -- hybrid molecules -- phenotypic screening -- QSAR -- drug repurposing -- drug design; 615.1
• DOI: 10.1080/17460441.2016.1216965
• Languages: English
• ISSNs: 1746-0441

Abstract

ABSTRACT: Introduction : Despite the approval of a large number of antiepileptic agents over the past 25 years, there has been no significant improvement in efficacy of treatments, with one third of patients suffering from intractable epilepsy. This scenario has prompted the search for innovative drug discovery solutions. While network pharmacology and explanations of the drug resistance phenomena have been proposed to drive the search for more efficacious therapeutic solutions, such alternative approaches have not fully taken hold within the antiepileptic drug discovery community so far. Areas covered : Herein, the author discusses the impact that network pharmacology and the current hypotheses of refractory epilepsy and drug repurposing could have if integrated with anti-epileptic computer-aided discovery. Expert opinion : With many complex diseases, the advancement in the understanding of disorder pathophysiology in addition to the contribution of systems biology have rapidly translated into the discovery of novel drug candidates. However, antiepileptic drug developers have fallen a little behind in this regard, with fewer examples of computer-aided antiepileptic drug design and network-based approximations appearing in scientific literature. New generation single-target agents have so far shown limited success in terms of enhanced efficacy; in contrast, multi-target agents could possibly demonstrate improved safety and efficacy.