Quantitative structure–activity relationship models for compounds with anticonvulsant activity

ABSTRACT

Introduction: Third-generation antiepileptic drugs have seemingly failed to improve the global figures of seizure control and can still be regarded as symptomatic treatments. Quantitative structure–activity relationships (QSAR) can be used to guide hit-to-lead and lead optimization projects and applied to the large-scale virtual screening of chemical libraries.

Areas covered: In this review, the authors cover reports on QSAR models related to antiepileptic drugs and drug targets in epilepsy, analyzing whether they refer to classic or non-classic QSAR and if they apply QSAR as a descriptive or predictive approach, among other considerations. The article finally focuses on a more detailed discussion of those predictive studies which include some sort of experimental validation, i.e. papers in which the reported models have been used to identify novel active compounds which have been tested in vitro and/or in vivo.

Expert opinion: There are significant opportunities to apply the QSAR methodology to assist the discovery of more efficacious antiepileptic drugs. Considering the intrinsic complexity of the disorder, such applications should focus on state-of-the-art approximations (e.g. systemic, multi-target and multi-scale QSAR as well as ensemble and deep learning) and modeling the effects on novel drug targets and modern screening tools.

KEYWORDS:

• Epilepsy
• Antiepileptic drugs
• Drug Discovery
• Drug design
• Molecular Descriptors
• QSAR
• Systemic QSAR
• Virtual Screening
• Phenotypic Virtual Screening
• Target-focused approximations
• Phenotypic response

Article highlights

• The term epilepsy describes a wide range of disorders, characterized by an enduring predisposition to experience unprovoked seizures, whose semiology varies across different epilepsy types. Most of the epilepsies that present a genetic component are polygenic, and many epilepsy types can be regarded as complex disorders.

• Despite many new antiepileptic treatments have been approved in the last decades, no clear improvement in the global figures of seizure-free patients has been observed. About one-third of the patients still suffer from refractory epilepsy.

• Quantitative structure–activity relationships have become a cornerstone in the drug discovery and Medicinal Chemistry fields, where they can be used to explain the differences in activities of congeneric series, identify novel active scaffolds and drive the design of new compounds.

• QSAR applications can be classified as classic and non-classic QSAR. Classic QSAR is highly influenced by the target-focused drug discovery paradigm, and the correspondent molecular descriptors are prompt to immediate mechanistic interpretation. In contrast, more abstract and less interpretable descriptors could be advantageous to screen chemically diverse libraries and model complex, phenotypic responses.

• Being a complex disorder, it is possible that a polypharmacology approach could be best suited to discover more efficacious treatments. Accordingly, QSAR models oriented to phenotypic responses (systemic QSAR) and multi-output models such as those provided by multi-target or multi-scale QSAR may prove useful to find improved therapeutic solutions.

This box summarizes the key points contained in the article.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer Disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

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Additional information

Funding

The authors are supported by the Argentinian National Council of Scientific and Technical Research and the University of La Plata.