Virtual screening and mechanism research of anti-tumor active ingredients from Sarcandra glabra targeting VEGFR-2
Year: 2026
Type: preprint
Abstract: In this study, computer-aided drug design techniques were employed to screen antitumor active ingredients from Sarcandra glabra that target vascular endothelial growth factor receptor-2 (VEGFR-2), and to elucidate the binding mode and druggability potential of promising candidate compounds for this target protein. Molecular docking was performed with the Surflex-dock module in SYBYL-X2.1 software, and ligands exhibiting high binding affinity were screened using a TotalScore threshold of greater than 6. Lipinski’s Rule of Five combined with the SwissADME platform was applied for preliminary druglikeness screening. SwissADME and Discovery Studio 2019 Client were further utilized to predict ADME-T pharmacokinetic and toxic properties. Molecular dynamics simulations of Sarcaglaboside C, the optimal compound obtained through comprehensive screening, were performed via GROMACS software to evaluate its binding stability with VEGFR-2. Meanwhile, surface plasmon resonance (SPR) assays were carried out to verify the binding capacity between the compound and VEGFR-2 at the in-vitro molecular level. The results showed that Sarcaglaboside C exhibited strong binding affinity toward VEGFR-2 protein, with a kinetic-fitted KD of 3.06 μM and a steady-state-fitted KD of 8.09 μM. Additional molecular-docking analysis characterized its interaction pattern, revealing that multiple hydroxyl groups of this compound could form hydrogen-bond interactions with amino-acid residues of VEGFR-2. Taken together, Sarcaglaboside C, a terpenoid compound derived from Sarcandra glabra, can stably bind to VEGFR-2 protein. These findings suggest that this compound possesses antitumor potential by targeting VEGFR-2 and may serve as a lead compound for follow-up structural-optimization investigations.
Source: Research Square
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7222931787