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Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology

Department of Bioinformatics, Institute of Biomedical Chemistry, 10 Building 8, Pogodinskaya Street, Moscow 119121, Russia

E-mail Address: [email protected]

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Sergey Ivanov

Department of Bioinformatics, Institute of Biomedical Chemistry, 10 Building 8, Pogodinskaya Street, Moscow 119121, Russia

E-mail Address: [email protected]

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Sandeep Kumar

Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala 147002, Punjab, India

E-mail Address: [email protected]

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Rajesh Goel

Department of Pharmaceutical Sciences and Drug Research, Punjabi University, Patiala 147002, Punjab, India

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, and

Vladimir Poroikov

Department of Bioinformatics, Institute of Biomedical Chemistry, 10 Building 8, Pogodinskaya Street, Moscow 119121, Russia

E-mail Address: [email protected]

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https://doi.org/10.1142/S0219720018400024Cited by:11 (Source: Crossref)

Abstract

Epilepsy is the fourth most common neurological disease after migraine, stroke, and Alzheimer’s disease. Approximately one-third of all epilepsy cases are refractory to the existing anticonvulsants. Thus, there is an unmet need for newer antiepileptic drugs (AEDs) to manage refractory epilepsy (RE). Discovery of novel AEDs for the treatment of RE further retards for want of potential pharmacological targets, unavailable due to unclear etiology of this disease. In this regard, network pharmacology as an area of bioinformatics is gaining popularity. It combines the methods of network biology and polypharmacology, which makes it a promising approach for finding new molecular targets. This work is aimed at discovering new pharmacological targets for the treatment of RE using network pharmacology methods. In the framework of our study, the genes associated with the development of RE were selected based on analysis of available data. The methods of network pharmacology were used to select 83 potential pharmacological targets linked to the selected genes. Then, 10 most promising targets were chosen based on analysis of published data. All selected target proteins participate in biological processes, which are considered to play a key role in the development of RE. For 9 of 10 selected targets, the potential associations with different kinds of epilepsy have been recently mentioned in the literature published, which gives additional evidence that the approach applied is rather promising.

Keywords:

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