Identifying the novel inhibitors of lysine-specific demethylase 1 (LSD1) combining pharmacophore-based and structure-based virtual screening

Abstract

Lysine-specific demethylase 1 (LSD1) has been reported to connect with a range of solid tumors. Thus, the exploration of LSD1 inhibitors has emerged as an effective strategy for cancer treatment. In this study, we constructed a pharmacophore model based on a series of flavin adenine dinucleotide (FAD)-competing inhibitors bearing triazole − dithiocarbamate scaffold combining docking, structure–activity relationship (SAR) study, and molecular dynamic (MD) simulation. Meanwhile, another pharmacophore model was also constructed manually, relying on several speculated substrate-competing inhibitors and reported putative vital interactions with LSD1. On the basis of the two pharmacophore models, multi-step virtual screenings (VSs) were performed against substrate-binding pocket and FAD-binding pocket, respectively, combining pharmacophore-based and structure-based strategy to exploit novel LSD1 inhibitors. After bioassay evaluation, four compounds among 21 hits with diverse and novel scaffolds exhibited inhibition activity at the range of 3.63–101.43 μM. Furthermore, substructure-based enrichment was performed, and four compounds with a more potent activity were identified. After that, the time-dependent assay proved that the most potent compound with IC₅₀ 2.21 μM inhibits LSD1 activity in a manner of time-independent. In addition, the compound exhibited a cellular inhibitory effect against LSD1 in MGC-803 cells and may inhibit cell migration and invasion by reversing EMT in cultured gastric cancer cells. Considering the binding mode and SAR of the series of compounds, we could roughly deem that these compounds containing 3-methylxanthine scaffold act through occupying substrate-binding pocket competitively. This study presented a new starting point to develop novel LSD1 inhibitors.

Graphical Abstract

Keywords:

• LSD1 inhibitors
• virtual screening
• pharmacophore modeling
• docking
• drug discovery

Acknowledgements

We acknowledge the Zhengzhou University Supercomputing Center and College of Physics Engineering for the computational support. We were especially grateful to Dr. Yi-Chao Zheng for the biological experiments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Project No. 81430085, No. 81773562 and No. 21372206 for H.-M.L.; No. 21403200 for L.-N.D.]; National Key Research Program of Proteins [No. 2016YFA0501800, for H.-M.L., No. 2017YFD0501401, for Y.-C.Z.]; Key Research Program of Henan Province [No. 161100310100, for H.-M.L.]; Science and Technology Innovation Talents of Henan Provincial Education Department [19IRTSTHN001, by W. Z]; Lina acknowledged the financial aid for International training of high-level talents in Henan (2017) from Henan Administration of Foreign Experts Affairs.