Issue 12, 2020

3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-b]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Abstract

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and becomes a new target for anticancer drugs. In recent years, small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamide LSD1 inhibitors using molecular docking, and three-dimensional quantitative structure–activity relationships (3D-QSAR). Comparative molecular field analysis (CoMFA q2 = 0.783, r2 = 0.944, rpred2 = 0.851) and comparative molecular similarity indices analysis (CoMSIA q2 = 0.728, r2 = 0.982, rpred2 = 0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

Graphical abstract: 3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-b]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Supplementary files

Article information

Article type
Paper
Submitted
02 dec 2019
Accepted
01 feb 2020
First published
18 feb 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 6927-6943

3D-QSAR, molecular docking, and molecular dynamics simulation study of thieno[3,2-b]pyrrole-5-carboxamide derivatives as LSD1 inhibitors

Y. Xu, Z. He, H. Liu, Y. Chen, Y. Gao, S. Zhang, M. Wang, X. Lu, C. Wang, Z. Zhao, Y. Liu, J. Zhao, Y. Yu and M. Yang, RSC Adv., 2020, 10, 6927 DOI: 10.1039/C9RA10085G

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