Cancer remains one of the most pressing challenges to global healthcare, exerting a significant impact on patient life expectancy. Cancer metastasis is a critical determinant of the lethality and treatment resistance of cancer. The urokinase-type plasminogen activator receptor (uPAR) shows great potential as a target for anticancer and antimetastatic therapies. In this work, we aimed to identify potential uPAR inhibitors by structural dynamics-based virtual screenings against a natural product library on four representative apo-uPAR structural models recently derived from long-timescale molecular dynamics (MD) simulations. Fifteen potential inhibitors (NP1-NP15) were initially identified through molecular docking, consensus scoring, and visual inspection. Subsequently, we employed MD-based molecular mechanics-generalized Born surface area (MM-GBSA) calculations to evaluate their binding affinities to uPAR. Structural dynamics analyses further indicated that all of the top 6 compounds exhibited stable binding to uPAR and interacted with the critical residues in the binding interface between uPAR and its endogenous ligand uPA, suggesting their potential as uPAR inhibitors by interrupting the uPAR-uPA interaction. We finally predicted the ADMET properties of these compounds. The natural products NP5, NP12, and NP14 with better binding affinities to uPAR than the uPAR inhibitors previously discovered by us were proven to be potentially orally active in humans. This work offers potential uPAR inhibitors that may contribute to the development of novel effective anticancer and antimetastatic therapeutics.Communicated by Ramaswamy H. Sarma.
Keywords: Antimetastasis; MD simulation; inhibitor; uPAR; virtual screening.