Pharmacophore modeling for the identification of small-molecule inhibitors of TACE

Recent developments and strategies for the discovery of TACE inhibitors

INTRODUCTION

TNF-α plays a central role in certain autoimmune diseases as well as in inflammation. The current strategy for excluding TNF-α from circulation is to selectively inhibit TNF-α converting enzyme (TACE), an enzyme that cleaves mTNF-α to active TNF-α. Various TACE inhibitors have been discovered by using different strategies to control inflammatory diseases, cancer, and cardiac hypertrophy.

AREAS COVERED

The present article summarizes the design and discovery of novel TACE inhibitors that have been reported in the literature since 2012 onwards. It also includes some reports concerning the new role that TACE plays in cancer and cardiac hypertrophy.

EXPERT OPINION

So far, undertaken studies that have looked to design and develop small TACE inhibitors have been discouraging due to the failure of any TACE inhibitors to hit the market. However, some of the latest developments, such as with tartrate-based inhibitors, has given hope to the potentiality of a viable novel selective TACE inhibitor therapeutic in the future. Indeed, some of the novel peptidomimetics and monoclonal antibodies have great potential to pave the way for an effective and safe therapy by selectively inhibiting TACE enzyme.

In silico target fishing and pharmacological profiling for the isoquinoline alkaloids of Macleaya cordata (Bo Luo Hui)

Background

Some isoquinoline alkaloids from Macleaya cordata (Willd). R. Br. (Bo Luo Hui) exhibited antibacterial, antiparasitic, antitumor, and analgesic effects. The targets of these isoquinoline alkaloids are undefined. This study aims to investigate the compound–target interaction network and potential pharmacological actions of isoquinoline alkaloids of M. cordata by reverse pharmacophore database screening.

Methods

The targets of 26 isoquinoline alkaloids identified from M. cordata were predicted by a pharmacophore-based target fishing approach. Discovery Studio 3.5 and two pharmacophore databases (PharmaDB and HypoDB) were employed for the target profiling. A compound–target interaction network of M. cordata was constructed and analyzed by Cytoscape 3.0.

Results

Thirteen of the 65 predicted targets identified by PharmaDB were confirmed as targets by HypoDB screening. The targets in the interaction network of M. cordata were involved in cancer (31 targets), microorganisms (12 targets), neurodegeneration (10 targets), inflammation and autoimmunity (8 targets), parasitosis (5 targets), injury (4 targets), and pain (3 targets). Dihydrochelerythrine (C6) was found to hit 23 fitting targets. Macrophage migration inhibitory factor (MIF) hits 15 alkaloids (C1–2, C11–16, C19–25) was the most promising target related to cancer.

Conclusion

Through in silico target fishing, the anticancer, anti-inflammatory, and analgesic effects of M. cordata were the most significant among many possible activities. The possible anticancer effects were mainly contributed by the isoquinoline alkaloids as active components.