Discovery of novel insomnia leads from screening traditional Chinese medicine database

Abstract

Insomnia is a prominent modern disease that affects an increasing population. Undesirable side effects of commercial drugs highlight the need to develop novel insomnia drugs. Virtual screening of traditional chinese medicine Database@Taiwan (TCM Database@Taiwan) identified 2-O-Caffeoyl tartaric acid (1), 2-O-Feruloyl tartaric acid (2), and Mumefural (3) as potential agonists for both gamma-amino butyric acid (GABA) or benzodiazepine (BZ) binding sites. The TCM candidates exhibited higher affinity than GABA and Zolpidem, a phenomenon that could be attributed to higher quantity of stabilizing H-bonds. Efficacy profiles using support vector machines and pharmacophore contour also suggest drug potential of the TCM candidates. Fragments added to the de novo derivatives 3a, 3b, 3c for GABA binding site, and 1a, 2a, and 3d for BZ binding site contributed to new binding sites and structural stability, further optimizing binding to GABA or BZ binding sites. Increased opening of the ion channel by candidate ligands provide strong support for their potential biological functions. The dual binding properties of the TCM candidates present a unique opportunity to develop twin-targeting drugs with less side effects. Derivative structures can be used as starting points for developing high affinity GABA_A receptor agonists with specificity towards GABA binding site and BZ binding site.

Keywords:

• insomnia
• γ-amino butyric acid (GABA)
• traditional chinese medicine (TCM)
• molecular dynamics (MD)

Acknowledgements

The research was supported by grants from the National Science Council of Taiwan (NSC101-2325-B-039-001), Asia University (100-asia-56, asia100-cmu-2, 101-asia-59), China Medical University (DMR-101-094, DMR-102-105), and China Medical University Hospital (DMR-102-001, DMR-102-003, DMR-102-051). This study is also supported in part by Taiwan Department of Health Clinical Trial and Research Center of Excellence (DOH102-TD-B-111-004) and Taiwan Department of Health Cancer Research Center of Excellence (DOH102-TD-C-111-005). We are grateful to Asia University and the National Center of High-performance Computing for computer time and facilities, and indebted to Dr. Tu-Liang Lin for developing and granting access to the ligand pathway simulation program LigandPath.