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Updated: Jun 22, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Interface-driven structural evolution on diltiazem as novel uPAR inhibitors: from in silico design to in vitro
Song Xie1,2, Yang Zhou2, Hao Zhu1
1School of Pharmacy, Nantong University, Nantong, 226001, Jiangsu, China.
Abstract:
The urokinase-type plasminogen activator receptor (uPAR) emerges as a key target for anti-metastasis owing to its pivotal role in facilitating the invasive and migratory processes of cancer cells. Recently, we identified the uPAR-targeting anti-metastatic ability of diltiazem (22), a commonly used antihypertensive agent. Fine-tuning the chemical structures of known hits represents a vital branch of drug development. To develop novel anti-metastatic drugs, we performed an interface-driven structural evolution strategy on 22. The uPAR-targeting and anti-cancer abilities of this antihypertensive drug wereidentified by us recently. Based on in silico strategy, including extensive molecular dynamics (MD) simulations, hierarchical binding free energy predictions, and ADMET profilings, we designed, synthesized, and identified three new diltiazem derivatives (221-8, 221-57, and 221-68) as uPAR inhibitors. Indeed, all of these three derivatives exhibited uPAR-depending inhibitory activity against PC-3 cell line invasion at micromolar level. Particularly, derivatives 221-68 and 221-8 showed enhanced uPAR-dependent inhibitory activity against the tumor cell invasion compared to the original compound. Microsecond timesclae MD simulations demonstrated the optimized moiety of 221-68 and 221-8 forming more comprehensive interactions with the uPAR, highlighting the reasonability of our strategy. This work introduces three novel uPAR inhibitors, which not only pave the way for the development of effective anti-metastatic therapeutics, but also emphasize the efficacy and robustness of an in silico-based lead compound optimization strategy in drug design.
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